Applied Machine Learning Engineer

Job Description: Quartermaster is on the lookout for a dynamic and innovative Applied Machine Learning Engineer to join our team. In this multifaceted role, you will engage in a variety of machine learning and perception projects that enhance our edge-intelligent maritime systems. The ideal candidate will be adept at tackling diverse challenges, from develop…

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 unexpected behaviors, and enhance robotic systems.At Foxglove, we provide the observability, visualization, and data infrastructure that enable robotics and autonomous systems teams to efficiently ingest, store, query, replay, and analyze extensive volumes of multimodal sensor data from live systems and production fleets.About the RoleWe are seeking a talented Applied Machine Learning Engineer with strong infrastructure insights to design, deploy, and scale the machine learning systems that power our data platform. In this impactful role, you will be responsible for optimizing production ML infrastructure—from enhancing inference pipeline throughput to establishing training and evaluation workflows. You will focus on high-priority challenges, such as developing retrieval applications for petabyte-scale multimodal robotics data, utilizing cutting-edge models to create high-performance search and data mining products, and fostering an internal ML flywheel for rapid iteration. This is a hands-on, application-driven position rather than a research-focused role.Key ResponsibilitiesDeploy and manage inference infrastructure for production ML workloads, focusing on model serving, scalability, and cost efficiency.Build and oversee vector database integrations and embedding applications to facilitate semantic search across various multimodal robotics data types (image, video, point cloud, and time series).Design and implement evaluation and training infrastructure to enhance model performance rapidly.Lead cloud architecture decisions and tools to optimize inference latency, throughput, cost, and reliability at scale.Collaborate closely with product engineers to deliver application-driven ML features that empower developers at the forefront of robotics and physical AI, steering clear of prototype experiments.Identify appropriate off-the-shelf solutions for production and determine when to build versus buy.

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.

Join the Applied Physics team as a Machine Learning Specialist at our Advanced Propulsion Laboratory in New York! We are looking for a driven and talented individual to engage in pioneering research within dynamic and evolving fields. Key Responsibilities: Investigate and analyze advanced Machine Learning algorithms tailored to specific challenges. Develop, train, and validate algorithms for targeted problem areas. Assist in integrating these algorithms into comprehensive programmatic systems that depend on such technologies. Work collaboratively in a multidisciplinary team environment to achieve research objectives. Engage in both independent and joint research initiatives while collaborating with a diverse range of scientists within and outside the Laboratory. Publish findings in peer-reviewed journals and present at conferences, seminars, and meetings. Travel as necessary to coordinate with collaborators and conduct site visits.

About Cantina Labs:Cantina Labs is at the forefront of social AI, innovating a comprehensive suite of cutting-edge, real-time models that redefine expression, personality, and realism. Our mission is to breathe life into characters, revolutionizing storytelling, connection, and creativity. The Cantina platform, our flagship social AI offering, is just the beginning of our journey.Join us in shaping the future of AI and its impact on human creativity and social interactions!About the Role:We are seeking an Applied Machine Learning Engineer to construct and enhance the data pipelines that support our extensive video generation models. This position emphasizes the collection of significant video data, the preparation of high-quality training samples, and the development of robust preprocessing, filtering, and parsing workflows. You will manage annotation pipelines across platforms like MTurk and oversee the entire lifecycle of training data, from raw ingestion to polished, model-ready samples that directly enhance our model's quality. This role sits at the critical intersection of data engineering and machine learning research, essential for transforming complex real-world data into the driving force behind our models.What You’ll Do:Develop and maintain scalable data pipelines for large video generation models, encompassing data ingestion, filtering, preprocessing, and dataset curation, utilizing tools such as AWS S3 and DynamoDB.Design and execute annotation workflows on platforms such as MTurk and Prolific, focusing on task design, quality control, and label validation.Train and enhance smaller supporting models used for data filtering, quality assessment, preprocessing, and other components of the machine learning pipeline.Collaborate closely with research and engineering teams to transform experimental workflows into scalable and repeatable systems that facilitate model training and evaluation.Ensure data quality throughout the pipeline by identifying bottlenecks, failure modes, and low-quality sources, and continuously refine tools and processes.Create internal tools and automation to streamline dataset preparation, launch annotation jobs, monitor outputs, and support model development comprehensively.Lead larger pipeline projects from inception to completion, including new dataset creation initiatives or enhancements to labeling and preprocessing infrastructure.

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.

At ExtraHop, our mission is to safeguard and empower the connected enterprise. We provide unparalleled visibility into the infrastructure that underpins businesses, lives, and communities, ensuring the integrity of networks, data, systems, and processes. Organizations depend on ExtraHop to illuminate cyber threats, vulnerabilities, and network performance challenges that existing security and IT tools fail to detect. Our insights enable organizations to investigate effectively, respond to threats swiftly, and maintain seamless operations.With a deep sense of social and moral responsibility, we strive to excel in our field, creating a secure environment where everyone can flourish. If this resonates with you, we are eager to connect and explore the next phase of your career.Position SummaryExtraHop is on the lookout for a Senior Engineering Manager to spearhead the Applied Machine Learning team responsible for developing behavioral detection capabilities within the ExtraHop Network Detection and Response (NDR) platform.This dynamic team focuses on creating machine learning systems that process large-scale network telemetry, highlighting significant behavioral signals for Security Operations Center (SOC) analysts. The role lies at the crossroads of applied machine learning, cybersecurity, and high-volume time-series data.As the Senior Engineering Manager, you will direct the applied machine learning strategy for behavioral detection within our product. You will lead a talented team dedicated to designing, evaluating, and operationalizing models to identify anomalous or suspicious patterns in intricate network activity. This position combines technical leadership, scientific rigor, and product influence, ensuring that our machine learning capabilities convert into actionable security insights.

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.

At PermitFlow, we are transforming the future of construction across America. As a pioneering applied AI firm, we address one of the most significant information challenges in the construction industry: comprehending what can be built, where, and how. Our innovative AI-driven agents empower the nation’s most rapidly growing construction companies to navigate the complexities of permitting, licensing, inspections, and project closeouts—thereby expediting housing, clean-energy, and infrastructure development nationwide.The construction sector, valued at $1.6 trillion, faces substantial delays, resource wastage, and unrealized opportunities. PermitFlow has successfully provided enhanced speed, accuracy, and visibility to over $20 billion in development projects, aiding contractors in minimizing compliance time, mitigating project risks, and scaling operations with assurance.As the U.S. enters a new capital expenditure supercycle encompassing data centers, factories, housing, and renewable energy, becoming a part of PermitFlow means constructing the AI infrastructure that underpins every construction project and propels the upcoming wave of reindustrialization.We have raised over $90 million, recently completing our Series B funding round, backed by prestigious investors such as Accel, Kleiner Perkins, Initialized, Y Combinator, Felicis, and Altos Ventures, with support from industry leaders at OpenAI, Google, Procore, ServiceTitan, Zillow, PlanGrid, and Uber.Our headquarters are located in New York City, offering a hybrid work schedule (3 days in the office per week). Preference will be given to candidates based in NYC or those willing to relocate.

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).

About Us:At Fireworks AI, we are pioneering the future of generative AI infrastructure. Our platform is recognized for delivering the highest-quality models with the fastest and most scalable inference capabilities in the industry. Proudly benchmarked as a leader in LLM inference speed, we are at the forefront of innovation with projects like function calling and multimodal models. As a Series C company valued at $4 billion, we are supported by prestigious investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. Our team comprises ambitious builders, many of whom hail from Meta PyTorch and Google Vertex AI.The Role:As an Applied Machine Learning Engineer, you will play a crucial role in bridging the gap between advanced AI research and practical applications. Your responsibilities will include developing, fine-tuning, and operationalizing machine learning models that deliver significant business value and enhance user experiences. This hands-on engineering position demands a blend of deep technical expertise and a strong customer-centric approach to create scalable AI solutions.Key Responsibilities:Customer Success: Collaborate with the Go-To-Market (GTM) team, including Account Executives and Solutions Architects, to ensure seamless integration and successful deployment of machine learning solutions.Demo / Proof of Concept (PoC): Develop and present engaging PoCs that showcase the capabilities of our AI technology.Application Build: Design, develop, and deploy end-to-end AI-powered applications customized to meet customer needs.Platform Features / Bug Fixes: Contribute to the internal machine learning platform by adding features and resolving issues.New Model Enablements: Integrate and enable new machine learning models within the existing platform or client environments.Performance Optimizations: Enhance the performance, efficiency, and scalability of deployed models and applications.Partnership Enablement: Collaborate closely with partners to facilitate joint AI solutions and ensure effective collaboration.

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.