Applied Machine Learning Engineer

Join us at Foxglove, where we are revolutionizing the robotics industry by building robust data infrastructure for real-world applications.As robotics transitions from research environments to practical implementations in factories, warehouses, vehicles, and field operations, data becomes essential for engineers to troubleshoot failures, understand unexpecte…

Quartermaster seeks an Applied Machine Learning Engineer based in California. The position centers on building and enhancing machine learning models that support and improve the company’s products and services. Regular collaboration with teams from various departments is a key part of this role. Responsibilities Design and implement machine learning models for practical, real-world use cases Partner with colleagues across different teams to understand product requirements and turn them into technical solutions Tune and refine existing models to boost their performance and reliability

Are you driven by a passion for solving complex AI challenges and eager to play a pivotal role in revolutionizing enterprise automation? Join Kognitos as we shape the future of software development!Your Contributions Will Include:Optimizing Resource Utilization: Create cutting-edge strategies to enhance resource efficiency in training and fine-tuning machine learning models, ensuring optimal performance without compromising on resource usage.Developing Intelligent Workflows: Innovate workflows that empower AI to reason, plan, and execute tasks consistently, reducing errors and unexpected outcomes.Integrating Multimodal Language Models: Engage in multimodal projects that blend text, images, and various data formats to develop robust, enterprise-ready automation solutions.Enterprise-Scale AI Solutions: Deliver AI systems that address enterprise needs, targeting a reduction of operational costs by 30% through widespread adoption.Key Responsibilities:Design and implement machine learning models with a focus on intelligent workflows and reliable task execution.Refine AI systems for multimodal applications, effectively tackling real-world challenges faced by enterprises.Pioneer new fine-tuning methodologies to enhance resource utilization and model efficacy.Ensure alignment of AI systems with regulatory standards while delivering consistent business outcomes.Collaborate with diverse teams, including product management, engineering, and business stakeholders, to drive impactful solutions.Stay abreast of the latest advancements in AI research, integrating cutting-edge developments into Kognitos’ platform.Qualifications:A Bachelor's, Master's, or Ph.D. in Computer Science, Machine Learning, or a related discipline.Demonstrated experience in developing and deploying machine learning models in production settings.Expertise in fine-tuning techniques for large-scale models and resource optimization.Strong intuition and experience with Large Language Models (LLMs).Familiarity with multimodal language models and their applications in enterprise environments.

About UsAt Applied Compute, we specialize in creating Specific Intelligence solutions for enterprises, developing agents that learn continuously from an organization’s processes, data, expertise, and objectives. We recognize a significant gap between the capabilities of AI models in isolation and their practical applications in real-world business contexts. Our systems often fall short because they lack adaptability to feedback. To address this, we are building a continual learning infrastructure that captures context, memory, and decision-making processes throughout the enterprise, enabling specialized agents to effectively execute real tasks.What Excites Us: We operate at a unique intersection where our product team constructs the platform that fuels a new generation of digital coworkers. Our research team pushes the boundaries of post-training and reinforcement learning, creating innovative product experiences. Our applied research engineers collaborate closely with clients to deploy models into production. This blend of strong product focus, deep research, and hands-on customer engagement is crucial for integrating AI into the enterprise. We are product-driven, research-informed, and actively engaged with our clients.Our Team: Our diverse team consists of engineers, researchers, and operators, many of whom are former founders. We have built RL infrastructure at leading organizations like OpenAI and Scale AI, and developed systems at Together, Two Sigma, and Watershed. We proudly serve Fortune 50 clients alongside companies like DoorDash, Mercor, and Cognition. Our work is supported by renowned investors, including Benchmark, Sequoia, and Lux.Who Thrives in Our Environment: We seek individuals eager to apply cutting-edge research and complex systems to tackle real-world challenges. You should be adept at quickly adapting to new environments, whether it’s a fresh codebase, a client’s data architecture, or an unfamiliar problem domain. A genuine enjoyment of customer interactions—listening, empathizing, and understanding how tasks are accomplished within their organizations—is essential. Those with entrepreneurial backgrounds, extensive side projects, or demonstrated end-to-end ownership typically excel in our company.

Join Our Team at MacroscopeAt Macroscope, we are dedicated to being the definitive source of truth for any software development company. Our mission is to empower leaders with clarity and provide engineers with the time they need to innovate.We enable leaders to gain insights into the evolution of their products and codebases—tracking changes, understanding team contributions, and identifying progress—all grounded in the ultimate source of truth: the code itself.Founded by experienced entrepreneurs who have successfully built and sold multiple companies, and held executive positions in public tech firms, we are backed by top-tier venture capital firms such as Lightspeed Venture Partners, Thrive Capital, Google Ventures, and Adverb.The RoleWe are seeking a Senior Applied Machine Learning Engineer who will be responsible for designing, developing, and optimizing the ML and AI systems that drive our core offerings. You will have full ownership of the systems, overseeing everything from data collection and evaluation to model experimentation and large-scale production deployment.This cross-functional position entails leading the ML/AI lifecycle for one of our most vital features: AI Code Review. Collaborating closely with our co-founders, you will make pivotal decisions that shape our product's development—ranging from building high-quality datasets to interpreting experimental results and enhancing model performance architecture. Additionally, you will play a significant role in crafting and implementing software that seamlessly integrates our models with our backend applications and user experience, offering a unique opportunity to influence our product's evolution significantly.Technology Stack: Typescript/React (frontend), Golang (backend), Temporal, Google Cloud (GCP), Postgres, Terraform, and custom-built AST "code walkers" in several programming languages including Golang, Typescript, Swift, Python, and Rust.

About Nooks.ai:Nooks is a cutting-edge AI Sales Assistant Platform (ASAP) designed to streamline sales processes, allowing representatives to concentrate on building relationships and closing deals. Our innovative platform has empowered thousands of sales professionals to achieve their targets, saving clients countless hours and generating substantial revenue. Trusted by sales teams at industry leaders like Hubspot, Rippling, and Toast, Nooks is transforming the sales landscape.Backed by over $70M in investments from top-tier venture capital firms, including Kleiner Perkins, Nooks has experienced remarkable growth, achieving a 4x and 3x increase in ARR over the past two years. We are on an ambitious trajectory to triple our growth once again this year.For more information, visit Nooks.ai.The RoleNote: Job title will be aligned with candidate experience.We are seeking a passionate Applied Machine Learning Engineer to join our dynamic team, tackling exciting technical challenges in the emerging field of AI-powered real-time collaboration. This role is pivotal in integrating machine learning features into the Nooks platform. The ideal candidate will have hands-on experience in a business where machine learning plays a central role.Key responsibilities will involve training production models to enhance their accuracy for specific sales applications, while aligning our technical strategy with performance, cost, and feasibility factors.Examples of Engineering Challenges You Might EncounterThese examples are illustrative; prior experience in all areas is not required. We hope you find some of these challenges intriguing!Real-time Audio AI & Precision/Recall/Latency Trade-offs (Algorithms & Models)Utilizing audio data, transcription, silence detection, and multiple signals to discern if a live call is a voicemail, a human, or a dial tree. Managing latency alongside precision/recall trade-offs is crucial for prompt human detection, involving advanced techniques like LLM embeddings, few-shot learning, data labeling, and continuous performance monitoring.Intelligent Call Funnels & Playbooks (Data Wrangling, Backend Engineering, GPT-3, UX)Analyzing the conversational flow to optimize call funnels and playbook strategies, focusing on data visibility and user experience.

About UsAt Speak, our mission is to revolutionize language learning.Learning a new language can transform lives by unlocking opportunities in diverse cultures, careers, and communities. With over two billion individuals around the globe striving to learn a language, we recognize that traditional one-on-one tutoring remains difficult to access at scale and has seen little innovation over recent decades. Speak is pioneering an AI-driven, human-level tutor accessible right from your pocket, providing a conversation-first experience where learners can practice speaking, receive immediate feedback, and progress through meticulously crafted lessons. Our goal is to facilitate a comprehensive journey from beginner to proficient speaker across various languages.Launched in South Korea in 2019, Speak has quickly become the leading language learning app in the region, now reaching learners across numerous markets and offering instruction in 15+ languages. Supported by over $150 million in venture capital from prestigious investors such as OpenAI, Accel, Founders Fund, and Khosla Ventures, our team is distributed across San Francisco, Seoul, Tokyo, Taipei, and Ljubljana.Role OverviewWe are seeking a skilled Machine Learning Engineer specializing in speech to join our innovative team. In this role, you will take charge of the entire modeling pipeline for speech recognition, encompassing training, experimentation, deployment, and ongoing monitoring. Collaborating closely with Product teams, you will design cutting-edge learning experiences and assess the effectiveness of production models on our users. As part of a nimble and dynamic team, you'll contribute as both a developer and a thought partner on projects related to ASR, assessments, pronunciation improvements, content personalization, and more. This is an exhilarating opportunity to be part of an ML team focused on crafting personalized learning experiences that will transform language education for millions worldwide.

We are seeking a talented Applied Machine Learning Engineer with a comprehensive understanding of the generative media landscape. You should possess an up-to-date knowledge of emerging methodologies and be capable of identifying gaps in the current market. Your role will involve innovating and developing machine learning models that enhance user experiences, requiring both novel training techniques and the fine-tuning of existing models with fresh datasets.

Founded in 2009 in the heart of Silicon Valley by visionaries Marc Andreessen and Ben Horowitz, Andreessen Horowitz (commonly known as a16z) is a premier venture capital firm dedicated to supporting innovative entrepreneurs who are shaping the future through technology. We pride ourselves on being stage agnostic, investing in technology companies from seed to venture and growth stages across diverse sectors including AI, bio + healthcare, consumer, crypto, enterprise, fintech, games, and initiatives contributing to American dynamism. Currently managing $90B across multiple funds, a16z is at the forefront of technological innovation.Our team is characterized by a profound respect for entrepreneurs and the intricate process of building companies; we understand the founder's journey firsthand. Our portfolio boasts industry leaders such as Anduril, Airbnb, Coinbase, Cursor, Databricks, Deel, Figma, GitHub, Roblox, SpaceX, and Stripe. We are committed to empowering founders and their teams to make a significant impact on the world.

Join Perplexity as an Applied Machine Learning Engineer and be at the forefront of innovation in artificial intelligence. You will design, develop, and refine advanced AI models that enhance user experiences globally. Your expertise in machine learning will allow you to create scalable solutions for user personalization, query comprehension, and content discovery, catering to the curiosity of millions.Key ResponsibilitiesUtilize cutting-edge ML and LLM techniques to address challenges in:Personalization (LLM memory, context summarization, retrieval, and ranking);Query Understanding (intent modeling, rewriting, agentic decomposition);Content Discovery (feed ranking and surfacing).Conduct thorough evaluations of LLM/ML models through offline and online methods, designing comprehensive experiments and metrics that yield insights into quality and impact.Manage the full model lifecycle from research to deployment, including data analysis, modeling, evaluation, A/B testing, and iterative enhancements.Collaborate with cross-functional teams, including engineers, PMs, data scientists, and designers, to ensure AI implementations yield significant product enhancements.Stay updated on ML/AI advancements by assessing and integrating new research and algorithms into the product lifecycle.Preferred QualificationsOver 5 years of experience in developing and deploying robust ML/AI models for large-scale, user-centric or data-driven applications.Extensive knowledge in deep learning frameworks (PyTorch, TensorFlow, JAX), LLMs, information retrieval, content summarization, recommendation systems, NLP, and ranking.Proficient software engineering skills (Python, production-level codebases, collaborative development).Comprehensive experience across the entire ML lifecycle: data analysis, feature engineering, model development, evaluation, and ongoing monitoring/improvement.Effective collaborator and communicator; thrives in fast-paced, cross-functional environments.Inquisitive, motivated by user/product impact, and passionate about advancing applied ML and AI.Bachelor's, Master's, or PhD in Computer Science, Engineering, or a related field (or equivalent experience).

SentiLink is at the forefront of transforming identity verification and risk management, enabling both institutions and individuals to conduct transactions with confidence. We are committed to revolutionizing the outdated and inefficient identity verification landscape in the United States, offering solutions that are ten times faster, more intelligent, and more precise.Our rapid growth reflects the significant traction we've garnered, with our real-time APIs successfully verifying hundreds of millions of identities, especially within the financial services sector, while swiftly expanding into other markets. SentiLink enjoys the backing of top-tier investors such as Craft Ventures, Andreessen Horowitz, NYCA, and Max Levchin.We have received accolades from major publications including TechCrunch, CNBC, Bloomberg, Forbes, Business Insider, PYMNTS, and American Banker, and have consistently ranked on the Forbes Fintech 50 list since 2023. Notably, we made history by being the first company to implement the eCBSV and provided testimony before the United States House of Representatives regarding the future of identity verification.SentiLink promotes a flexible working environment, offering various work arrangements ranging from fully remote to in-office. As a digital-first organization, we emphasize strong collaboration across teams in the U.S. and India. Our offices are located in cities including Austin, San Francisco, New York City, Seattle, Los Angeles, and Chicago in the U.S., along with Gurugram (Delhi) and Bengaluru in India. If you are near any of these locations, we encourage regular in-office engagement. Some positions are designed to be hybrid or in-office. For instance, our engineering team in India primarily operates from our Gurugram office.

P-1380 Join Databricks as a Senior Applied AI Engineer, where you will harness the power of machine learning, scheduling, and optimization algorithms to enhance the efficiency and performance of our engineering systems and infrastructure. Our Applied AI team tackles some of the most challenging and fascinating issues in the industry, ensuring that Databricks infrastructure and products operate at peak performance and cost efficiency. This role is critical, as our customers depend on us to deliver the most optimized workloads. Your Impact: Develop comprehensive systems from the ground up within a dynamic team of seasoned professionals. Influence the direction of our applied machine learning investment areas by collaborating with engineering and product teams across the organization. Lead the design and implementation of advanced AI models and systems that enhance the capabilities and performance of Databricks' products, infrastructure, and services. Architect and deploy robust, scalable machine learning infrastructure, including data storage, processing, model training, serving components, and monitoring systems to facilitate seamless integration of AI/ML models into production environments. Explore innovative modeling techniques in the realm of machine learning for systems. Contribute to the wider AI community by publishing research, presenting at conferences, and actively engaging in open-source projects, thereby strengthening Databricks' reputation as an industry leader.

About UsAt Applied Compute, we are pioneering the development of Specific Intelligence for enterprises, creating agents that continuously learn from a company’s processes, data, expertise, and objectives. Our mission is to bridge the gap between isolated AI capabilities and their effective application within real business environments. Traditional AI systems often fall short as they lack the ability to adapt based on feedback. Our innovative continual learning layer captures context, memory, and decision-making processes across the enterprise, enabling specialized agents to engage in meaningful work.What Excites Us: We operate at the exciting intersection of product development and cutting-edge research. Our product team designs the platform that empowers a new generation of digital coworkers, while our research team drives advancements in post-training and reinforcement learning to enhance user experiences. As an applied research engineer, you will work directly with clients to implement models in production, combining robust product development with deep research insights to facilitate AI integration in enterprises.Meet Our Team: Our diverse team consists of engineers, researchers, and operators, many of whom are former founders. We have previously built reinforcement learning infrastructure at OpenAI, established data foundations at Scale AI, and contributed to significant systems at companies like Together, Two Sigma, and Watershed. We collaborate with Fortune 50 clients, including DoorDash, Mercor, and Cognition, and are proud to be backed by reputable investors such as Benchmark, Sequoia, and Lux.Who Thrives Here: We seek individuals who are passionate about applying innovative research and complex systems to solve real-world challenges. You should feel comfortable navigating new environments rapidly—be it a fresh codebase, a client’s data architecture, or an unfamiliar problem domain. A genuine enjoyment for customer interaction, empathy, and a deep understanding of their operational workflows are essential. Candidates with entrepreneurial backgrounds, extensive side projects, or a proven track record of end-to-end ownership typically excel in our environment.

About NationGraphAt NationGraph, we are revolutionizing the accessibility and usability of public sector data for businesses targeting municipalities, state agencies, educational institutions, and specialized districts. Our advanced data intelligence engine extracts actionable insights from millions of public sector sources, empowering organizations to make informed decisions. Established in 2024, our mission is to democratize information, ensuring that public data is genuinely accessible to everyone. Discover more at nationgraph.comOur TeamComprises seasoned entrepreneurs who have successfully built, scaled, and exited multiple companies.Developed robust software infrastructure capable of processing billions in transactions.Supported by top-tier venture capitalists and seasoned operating partners with a track record of investing in and nurturing iconic brands.Role OverviewDesign and implement end-to-end machine learning pipelines.Extract and mine data from various online sources through large-scale web crawling and scraping techniques to enhance our models and insights.Convert unstructured text data into structured knowledge using natural language processing (NLP), entity recognition, and bespoke models.Develop and refine text classification models to systematically organize intricate datasets.Enhance retrieval-augmented generation (RAG) systems utilized in our product offerings.Drive our data strategy by identifying and integrating new data sources.Tackle open-ended technical challenges, fostering a culture of learning and collaboration within the team.Primarily utilize Python and SQL for development.QualificationsA strong quantitative background in fields such as computer science, physics, mathematics, or engineering.Solid foundation in mathematics and statistics.A PhD in a quantitative discipline.Expertise in Python programming.Proactive ownership mentality with the ability to address complex technical challenges to create commercial value.A genuine enthusiasm for continuous learning, growth, and uncovering insights from complex datasets.Strong problem-solving, communication, and collaboration abilities in a dynamic work environment.

About Applied IntuitionApplied Intuition, Inc. is at the forefront of advancing physical AI technology. Established in 2017 and currently valued at $15 billion, this Silicon Valley powerhouse is creating the essential digital framework that will infuse intelligence into every moving machine worldwide. Our solutions serve key sectors including automotive, defense, trucking, construction, mining, and agriculture, focusing on three main areas: tools and infrastructure, operating systems, and autonomy. Our trusted solutions are utilized by 18 of the top 20 global automakers and the United States military along with its allies. Our headquarters is located in Sunnyvale, California, with additional offices in Washington, D.C., San Diego, Ft. Walton Beach, Florida, Ann Arbor, Michigan, London, Stuttgart, Munich, Stockholm, Bangalore, Seoul, and Tokyo. Find out more at applied.co.We prioritize in-office collaboration, expecting our employees to work from their Applied Intuition office five days a week, while also embracing flexibility. Employees are trusted to manage their schedules, which may include occasional remote work, starting the day with morning meetings from home, or leaving early for family commitments.Hear from an Engineer:About the roleWe are searching for a talented software engineer specializing in perception for autonomous vehicles or mobile robotics. Your role will involve enhancing perception modules within our autonomous vehicle framework, including the development of 4D world representations to facilitate seamless autonomy. You will also lead the design and implementation of computer vision and machine learning strategies that empower self-driving vehicles to navigate effectively.In this dynamic and customer-centric team environment, you will not only contribute your engineering skills but also gain insights into best practices within the evolving autonomy sector. Our fast-paced culture encourages innovation and collaboration.

Join Our MissionAt insitro, we are at the forefront of transforming drug development through the power of machine learning. Our pioneering ChemML Platform leverages advanced AI techniques to expedite small molecule discovery, from initial hit identification to lead optimization. By utilizing some of the most extensive datasets in the industry, we are able to design innovative drugs targeting novel AI-derived compounds swiftly.Billions of proprietary binding affinity measurementsHundreds of thousands of ADMET and In Vivo PK measurementsExperimental data generated through our AI-driven DMTL optimization cyclesWe are seeking an Applied Machine Learning Scientist who will actively engage with our ChemML platform to drive design across various therapeutic programs. This is a unique opportunity to apply cutting-edge machine learning techniques to make a tangible impact in drug discovery. The role reports to the Senior Manager, Molecular Machine Learning and offers a flexible hybrid work model (2 days in the office per week) or remote work arrangement (1 week in-office per quarter).

SentiLink is at the forefront of delivering cutting-edge identity and risk management solutions, providing both individuals and institutions the ability to transact with assurance. We are revolutionizing identity verification within the United States, replacing outdated, inefficient, and costly practices with solutions that are ten times faster, smarter, and more precise.Our rapid growth is a testament to our innovative approach; our real-time APIs have successfully verified hundreds of millions of identities, initially focusing on the financial sector and quickly expanding into various new markets. SentiLink enjoys the support of prestigious investors including Craft Ventures, Andreessen Horowitz, NYCA, and Max Levchin.We are proud to have received accolades from TechCrunch, CNBC, Bloomberg, Forbes, Business Insider, PYMNTS, and American Banker, and we have been featured in the Forbes Fintech 50 list every year since 2023. Notably, we made history as the first company to deploy the eCBSV and have testified before the United States House of Representatives regarding the future of identity verification.SentiLink accommodates a flexible work environment, ranging from fully remote positions to in-office roles. As a digital-first company, we emphasize collaboration across teams in the U.S. and India. We have physical locations in Austin, San Francisco, New York City, Seattle, Los Angeles, and Chicago in the U.S., alongside offices in Gurugram (Delhi) and Bengaluru in India. For those near our offices, we encourage regular office attendance. Certain roles, such as our engineering team in India, are designed to be primarily in-office.Role Overview:As a Senior Applied ML Scientist at SentiLink, you will be instrumental in developing our core products: advanced models aimed at identifying fraudulent activities while enhancing our expanding array of financial risk solutions. Your expertise as a seasoned researcher will be essential, making you the authoritative figure in your domain. You will frequently engage in high-impact projects that necessitate a profound understanding of the field, critical analytical skills, and robust technical capabilities. Collaboration with various teams across the organization will be key as you investigate new fraud types, innovate product offerings, and conduct analyses to support our sales and marketing efforts.

About UsAt Sila, we are at the forefront of revolutionizing battery technology. Our mission is to facilitate the global shift towards clean energy by engineering innovative lithium-ion battery materials that enhance energy density while minimizing size and weight. Our advancements result in powerful, compact batteries that foster innovation in consumer electronics and accelerate the widespread adoption of electric vehicles, thereby reducing our reliance on fossil fuels. Every day, we tackle one of the most critical challenges of our time, pushing the boundaries of what’s possible. Are you ready to join a team committed to transforming the world?Who You AreYou are passionate about creating intelligent systems that enhance manufacturing operations, enabling factories to understand current conditions, anticipate future events, and react proactively. You thrive on solving complex technical challenges that have tangible operational impacts. You can distill ambiguous manufacturing issues into functional systems that are utilized by engineering and operations teams.You are adept at navigating software, data, engineering principles, and manufacturing frameworks. You are experienced in managing noisy production data, imperfect systems, and complex failure patterns. You don't just focus on visibility; you design actionable systems.We seek an individual with a track record of building and implementing systems that transform operational processes.Build Manufacturing Intelligence SystemsCreate internal production systems that aggregate plant telemetry, live data feeds, event logs, quality assessments, maintenance records, and operational context for enhanced manufacturing predictions and responsive actions.Analyze raw data to reconstruct equipment and process behaviors, highlighting significant deviations from expected outcomes.Design systems that detect process drifts, categorize fault patterns, and assess operational risks before failures or quality losses occur.Convert raw manufacturing indicators into dependable services and applications that boost uptime, yield, and execution speed.Develop Models That MatterConstruct and implement machine learning models for anomaly detection, fault classification, process monitoring, quality forecasting, and related manufacturing applications.Create models that interlink recipe conditions, process parameters, and equipment behavior.

About Applied IntuitionApplied Intuition, Inc. is at the forefront of advancing physical AI technology. Established in 2017 and currently valued at $15 billion, this Silicon Valley-based company is building the essential digital infrastructure to infuse intelligence into every moving machine worldwide. We cater to industries such as automotive, defense, trucking, construction, mining, and agriculture through three primary sectors: tools and infrastructure, operating systems, and autonomy. Our solutions are trusted by 18 of the top 20 global automakers, along with the United States military and its allies, to deliver exceptional physical intelligence. Our headquarters is located in Sunnyvale, California, with additional offices across Washington, D.C.; San Diego; Ft. Walton Beach, Florida; Ann Arbor, Michigan; London; Stuttgart; Munich; Stockholm; Bangalore; Seoul; and Tokyo. Discover more at applied.co.We are an in-office company, expecting our employees to primarily work from their Applied Intuition office five days a week. We understand the importance of flexibility and trust our employees to manage their schedules responsibly. This may include occasional remote work, starting the day with morning meetings from home before heading to the office, or leaving earlier when needed to accommodate family commitments.About the RoleWe are in search of a skilled software engineer with extensive experience in optimizing machine learning models and deploying them in production-grade embedded runtime environments. Your expertise will span the entire ML framework stack, including PyTorch, JAX, ONNX, TensorRT, CUDA, XLA, and Triton.At Applied Intuition, You Will:Lead ML performance optimization across various technologies for both on-road and off-road ADAS/AD stacks aimed at deployment on a range of embedded computing platforms.Devise compute usage strategies to enhance efficiency and minimize latency of model inference for compute boards chosen by our customers.Engage in model pruning and quantization, ensuring successful deployment on memory-constrained platforms.Collaborate closely with ML engineers and software developers to identify and optimize efficient model architecture solutions.Establish methodologies to...

About Applied IntuitionApplied Intuition, Inc. is at the forefront of advancing physical AI technologies. Established in 2017 and currently valued at $15 billion, our Silicon Valley-based company is dedicated to creating the essential digital infrastructure that empowers intelligence across all moving machines globally. Our solutions serve critical sectors including automotive, defense, trucking, construction, mining, and agriculture, focusing on three main domains: tools and infrastructure, operating systems, and autonomy. Trusted by 18 of the top 20 global automakers, as well as the U.S. military and its allies, Applied Intuition is committed to delivering unparalleled physical intelligence solutions. Our headquarters is located in Sunnyvale, California, complemented by offices in Washington, D.C.; San Diego; Ft. Walton Beach, Florida; Ann Arbor, Michigan; London; Stuttgart; Munich; Stockholm; Bangalore; Seoul; and Tokyo. For more information, visit applied.co.We prioritize in-office collaboration and expect our employees to work primarily from our Applied Intuition office five days a week. However, we value flexibility and trust our team members to manage their schedules responsibly. This may include occasional remote work, starting the day with morning meetings from home before heading to the office, or leaving early when necessary to accommodate personal commitments.About the RoleAs an Engineering Manager on our Machine Learning Platform team, you will lead an exceptional group of engineers dedicated to building the infrastructure that enables Physical AI at scale. Your team will oversee three pivotal areas: Training & Inference Orchestration, where we develop frameworks to efficiently schedule and execute extensive tasks across thousands of GPUs; GPU Cluster Architecture, where we design and expand what will become the industry's largest GPU cluster for Physical AI; and Performance Optimization, where we maximize hardware utilization, throughput, and cost efficiency for large-scale training and inference workloads. You will collaborate at the intersection of systems engineering and machine learning, working directly with stack development and research teams to eliminate bottlenecks and expedite the transition from experimentation to production.