Applied Research Engineer - Transforming AI in Enterprises

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…

tvScientific seeks a Machine Learning Platform Engineer to help shape the company’s advertising technology. This position can be based in San Francisco, CA, or performed remotely from anywhere in the United States. Role overview This role focuses on building and refining machine learning models that drive the core of tvScientific’s advertising platform. The work combines technical skill with creative problem-solving to support the platform’s effectiveness. What you will do Develop and optimize machine learning models to enhance advertising performance Collaborate with team members to deliver solutions that balance innovation, scalability, and reliability Apply technical expertise to address challenges at the intersection of technology and creative thinking Location Candidates may work from San Francisco, CA, or remotely within the US.

Join Our Team as a Senior Applied Scientist!At Gridware, we are on a mission to revolutionize grid management through innovative technology. Based in San Francisco, we are pioneering a cutting-edge approach known as Active Grid Response (AGR). This initiative focuses on enhancing the reliability and safety of the electrical grid by monitoring its electrical, physical, and environmental parameters. Our advanced platform leverages high-precision sensors to identify potential issues early, facilitating proactive maintenance and minimizing outages. Backed by leading climate-tech and Silicon Valley investors, we are poised to make a significant impact in the energy sector. For more insights on our work, visit www.Gridware.io.Role Overview:We are looking for a talented Senior Applied Scientist with a strong background in machine learning and digital signal processing (DSP). In this role, you will be responsible for designing sophisticated models that operate on diverse time-series sensor data within resource-constrained environments. Your work will involve developing algorithms that optimize for accuracy while adhering to strict power and memory constraints, thereby advancing Gridware’s edge intelligence capabilities. This position requires a blend of applied research, model optimization, and close collaboration with hardware and firmware teams to implement low-level solutions.

Become a part of Two Dots as we strive to create a more robust financial ecosystem.In our fast-paced world, every time an individual seeks a mortgage, car loan, or apartment lease, they present financial documents that contribute to their financial profile. The accuracy of these profiles plays a crucial role in stabilizing the economy.At Two Dots, we are innovating a system that evaluates consumers in a consistent and fair manner. Our mission is to detect fraud that often goes unnoticed and to identify value in unconventional applications that might be overlooked.Please note that all full-time employees are required to work from our headquarters located in San Francisco, CA.Role Overview:We are seeking our second Machine Learning Engineer to collaborate closely with our CTO and Staff ML Engineer. In this position, you will be responsible for designing, developing, and deploying machine learning solutions, particularly focusing on fine-tuning multimodal large language models (LLMs) to address real-world challenges. The right candidate will possess a fervor for building and implementing advanced ML applications, aiming to enhance our automation rates for application approvals/denials and elevate our fraud detection capabilities, ultimately driving business impact and client satisfaction.Key Responsibilities:Independently design, develop, and deploy machine learning models.Examine extensive datasets to reveal insights and patterns that guide product development and enhance personalized customer experiences.Continuously assess and refine the performance of deployed models to ensure they fulfill business objectives and scalability needs.Keep abreast of the latest developments in machine learning, AI, data science, and engineering, applying this knowledge to enhance our products and services.Desirable Traits:3+ years of experience in a Machine Learning or Data Engineering role, with a strong command of Python and ML frameworks like PyTorch.Demonstrated ability to enhance models for key information extraction, including named entity recognition and financial document classification.Experience with active learning and HITL-driven workflows; collaborating with large labeling and quality teams is advantageous.Exceptional problem-solving skills, with the ability to think critically and creatively.

Join Our Integrity TeamAt OpenAI, our Integrity team is committed to safeguarding our innovative technologies against various adversarial threats. As we advance our platforms, we prioritize their integrity and security.We are at the forefront of defending our systems against financial exploitation, large-scale attacks, and other forms of misuse that could compromise user experience and operational stability.Your Role as a Machine Learning EngineerAs a Machine Learning Engineer in OpenAI's Applied Group, you will collaborate with some of the brightest minds in AI. Your mission will be to deploy cutting-edge models in production environments, transforming research breakthroughs into practical solutions that enhance the safety and trustworthiness of our platform. If you’re passionate about fine-tuning LLMs and developing machine learning models, this position offers you a chance to make a significant impact.Key Responsibilities:Innovate and Deploy: Design and implement advanced machine learning models that address real-world challenges. Translate OpenAI’s research from ideation to execution, crafting AI-driven applications with a measurable impact.Collaborate with Experts: Partner closely with researchers, software engineers, and product managers to tackle complex business problems and deliver AI-enhanced solutions. Be part of an energetic team where creativity flourishes.Optimize and Scale: Create scalable data pipelines, enhance model performance and accuracy, and ensure readiness for production. Contribute to projects that leverage state-of-the-art technology and innovative methodologies.Learn and Lead: Keep abreast of the latest developments in machine learning and AI. Participate in code reviews, share insights, and lead by example to uphold high engineering standards.Make a Difference: Oversee and maintain deployed models to ensure they consistently deliver value. Your contributions will significantly influence the positive impact of AI on individuals, businesses, and society.

About KastleKastle is revolutionizing consumer lending with an innovative AI operating system, beginning with mortgages. We collaborate with leading mortgage lenders across America to enhance their contact center and compliance operations through AI-powered voice agents. Supported by Y Combinator, Commerce Ventures, and industry experts from Snapdocs, Google, and WePay, we are reshaping the lending landscape using cutting-edge AI technologies.About the RoleAs a Senior Applied AI Engineer, you will play a vital role in establishing the technical backbone of Kastle's AI platform. Your responsibilities will include fine-tuning large language models, crafting AI workflows for highly regulated enterprises, and ensuring that our voice agents facilitate accurate, compliant, and effective interactions with borrowers.This position is ideal for an engineer who is passionate about applied AI, eager to tackle real-world challenges, and excited to contribute to the foundation of an early-stage AI startup.What You'll DoAI Model Integration: Fine-tune and deploy LLMs for real-time voice interactions with borrowers.Prompt Engineering: Develop and refine prompt strategies to enhance AI performance and compliance.Evaluate LLMs and AI Agents: Create high-quality evaluations using proprietary datasets to benchmark AI agent performance and conduct experiments.Custom AI Solutions: Train and implement domain-specific AI models tailored for consumer lending.Scalability & Compliance: Guarantee that AI solutions adhere to regulatory standards (FDCPA, RESPA, TILA) while scaling efficiently.Data Pipelines & APIs: Construct robust AI-driven workflows that seamlessly integrate with loan servicing platforms.Continuous Optimization: Monitor performance metrics and consistently enhance agent quality and borrower experience.What We're Looking For2+ years of experience in building and deploying ML/AI systems in production environments.Strong proficiency in Python and deep learning frameworks such as TensorFlow and PyTorch.Experience with LLM orchestration frameworks (e.g., LangChain, LlamaIndex, or similar).Proven track record of delivering AI products that users rely on.Strong product mindset with the capability to translate business requirements into AI solutions.Excellent communication skills for effective collaboration across teams.

Join Our Team as an iOS EngineerAt Speak, we are on a mission to transform language learning for everyone.Language learning can significantly enhance lives by connecting individuals to new cultures, career opportunities, and communities. With over two billion people globally striving to learn a language, the traditional approach of one-on-one tutoring remains challenging to access at scale and has seen little innovation in recent years. Speak aims to change this by developing a human-level, AI-driven tutor that fits in your pocket—a conversation-first platform that empowers learners to engage in dialogue, receive real-time feedback, and progress through meticulously crafted lessons. Our goal is to provide a complete journey from novice to confident speaker in multiple languages.Launched in South Korea in 2019, Speak has quickly established itself as the leading language learning app, now catering to learners across various markets and offering support for over 15 languages. As a premier AI company, we have secured over $150 million in venture funding from notable investors, including OpenAI, Accel, Founders Fund, and Khosla Ventures. Our diverse team is spread across San Francisco, Seoul, Tokyo, Taipei, and Ljubljana.About the RoleAs a Mobile iOS Engineer on Speak’s engineering team, you'll play a pivotal role in enhancing our content delivery, conducting A/B testing on monetization features, and facilitating the launch of new markets and languages. You'll work closely with backend engineers, as well as our Product and Design partners, and be responsible for deploying product features to millions of users.Your ResponsibilitiesEnhance the “freemium” experience to boost user conversions.Assist in the launch of new markets and languages.Implement various paywall tests, including pricing strategies, design modifications, delayed paywalls, and special offers.Refine our speech-to-text capabilities.Enhance our audio and video streaming functionalities.Your Qualifications3+ years of experience in mobile engineering, ideally within a dynamic startup environment.Proficiency in Swift, with a solid grasp of mobile architectures such as MVC and MVVM.Bonus: Experience with SwiftUI and mobile streaming technologies.

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.

About Mariana MineralsMariana Minerals is a pioneering software-driven, vertically integrated minerals company dedicated to supplying the essential minerals that fuel modern energy, artificial intelligence, and defense technologies. We are transforming the minerals supply chain by leveraging extensive industry knowledge alongside cutting-edge software, automation, and data-centric decision-making.The RoleAs we build the critical minerals supply chain from the ground up, we seek a highly skilled Senior Machine Learning Engineer to help drive our autonomous operations.Unlike traditional software companies, we are a mining company that develops our own software solutions. Mariana designs, builds, commissions, and operates our own mines and refineries, where we create proprietary chemical processes. Currently, we are producing battery-grade lithium salts from real oil and gas wastewater at our facilities. Our first commercial-scale lithium production facility, Lithium One, is set to commence initial production in the first half of 2027.In your role as a Senior Machine Learning Engineer, you will spearhead the design and implementation of machine learning systems that directly optimize the operations of our mineral refining facilities and guide significant investment and operational decisions. Your contributions will be visible in tangible metrics such as recovery rates, energy consumption, reagent usage, and equipment uptime.The TechThis position involves some of the most compelling applied AI work available today.Our internal platform, PlantOS, utilizes the same reinforcement learning frameworks that power self-driving cars and humanoid robots, adapted for the autonomous and short-interval control of mineral refining circuits. Our models dynamically adjust operating parameters in real time, optimizing for lithium recovery, reagent consumption, energy efficiency, and equipment uptime simultaneously.The working environment is complex and ever-changing; variations in wastewater compositions, ore grades, and aging equipment require the system to adapt continuously. The ultimate objective is to achieve fully autonomous refining operations—when you implement your solutions here, you will witness the physics of the process evolve.What You’ll DoCollaborate closely with Mariana’s process chemistry and engineering teams to develop innovative, data-driven models of core chemical unit operations.Train and deploy reinforcement learning models to optimize operational processes.

Join the Lightfield TeamAt Lightfield, we are revolutionizing the CRM landscape with our AI-native platform that seamlessly integrates your email, calendar, and meetings. Our innovative solution captures every interaction, transforming it into organized insights—accounts, tasks, follow-ups, and much more—ensuring nothing falls through the cracks.We are committed to reimagining CRM from the ground up. Rather than imposing rigid systems, Lightfield adapts to the actual workflows of companies, automating processes and providing actionable insights that catalyze growth. We are creating the CRM solution we envisioned: fast, intelligent, and genuinely beneficial.Supported by esteemed investors like Greylock, Lightspeed, and Coatue, our team is composed of veterans from Tome, a generative AI presentation tool used by over 25 million people, as well as industry giants like Llama, Instagram, Facebook Messenger, Pinterest, Google, and Salesforce.Your RoleAs a pivotal member of Lightfield's AI/ML team, you will spearhead the development of experiences that sit at the heart of our product, crafting applications that truly impress our customers.The current focus is on constructing a robust, domain-specific AI that excels beyond generic large language models (LLMs). We are excited by the challenge of innovating new AI products that empower professionals in their endeavors, and we are eager to expand our AI/ML team to meet this ambition.Key ResponsibilitiesLead the creation of machine learning product development infrastructure, emphasizing scalability and innovation in collaboration and versioning, particularly for LLM training and prompting.Develop and sustain a platform utilized by various teams working on ML products, guaranteeing its scalability, efficiency, and user-friendliness.Work closely with internal teams to integrate ML solutions and establish best practices for software engineering in an AI-focused development environment.Contribute to building a top-tier AI/ML engineering team by recruiting and mentoring new talent.Tackle and resolve complex technological challenges in software engineering at scale, particularly related to AI systems.Who You AreYou possess a Bachelor's or Master's degree in Computer Science, Engineering, AI, or a related field.You have over 6 years of experience in software engineering, with a specialization in ML infrastructure.You demonstrate a robust understanding of deep learning frameworks and cloud services.

Plaud Inc. is a San Francisco-based company focused on building AI-powered tools for professionals. Since its launch in 2023, Plaud’s note-taking platform has attracted over 1.5 million users worldwide. The company aims to enhance human intelligence by creating infrastructure and interfaces that help people capture, extract, and apply insights from speech, audio, visuals, and thought. Plaud’s approach blends hardware and software to support collaboration between humans and AI. The company places a strong emphasis on data security, complying with standards such as SOC 2, HIPAA, GDPR, ISO27001, ISO27701, and EN18031. For more information, visit Plaud.ai or connect on Instagram, X, Facebook, LinkedIn, and YouTube.

About SentryAt Sentry, we recognize that poor software experiences are all too common, and we are determined to change that. Our mission is to empower developers to create better software more efficiently, allowing everyone to reconnect with the joy of technology.With over $217 million in funding and a community of more than 100,000 organizations, including industry giants like Disney, Microsoft, and Atlassian, we are pioneering performance and error monitoring solutions. Our tools enable companies to spend less time addressing bugs and more time innovating.Sentry promotes a hybrid work environment across our global hubs, designating Mondays, Tuesdays, and Thursdays as in-office collaboration days. If you are passionate about creating solutions that enhance the digital experience, we invite you to join us in developing the next generation of software monitoring tools.About the RoleAs a Staff Machine Learning Engineer within Sentry’s AI/ML team, you will take the lead in developing advanced models and agents that enhance our products' intelligence and functionality. This pivotal role involves integrating AI and machine learning into our core offerings, including issue triage and resolution, as well as predictive analytics for application performance monitoring. Your contributions will enable organizations worldwide to derive actionable insights from their software, helping them to create superior products at an accelerated pace.In This Role You WillCreate cutting-edge agentic AI systems for triaging, debugging, and resolving real-world production challenges.Utilize Sentry’s extensive dataset of errors, spans, and profiles to inform your work.Lead the charge on significant AI/ML initiatives within the organization.You Will Thrive in This Role If YouAre motivated by making a meaningful impact and enjoy high-stakes, visible projects.Have a passion for building and will embrace the opportunity to be a founding member of the AI/ML team.Excel in cross-functional collaboration, working alongside developers and product teams to create features.

About UsAt Preference Model, we are revolutionizing the future of AI by developing the next generation of training data. While current models demonstrate great power, their effectiveness is limited in diverse applications due to many tasks being out of distribution. We create reinforcement learning environments where models can face real-world research and engineering challenges, allowing them to iterate and learn via realistic feedback loops.Our founding team, hailing from Anthropic's data team, has a rich background in building data infrastructure, tokenizers, and datasets that power Claude. We collaborate with leading AI labs to accelerate AI’s transformative potential and are proudly backed by a16z.About the RoleWe are looking for skilled Machine Learning Engineers to join our efforts in constructing distributed training infrastructure for our reinforcement learning initiatives. Your responsibilities will include:Designing and implementing scalable distributed training infrastructure utilizing PyTorch and Ray.Developing automation tools for monitoring, debugging, and recovery in distributed training environments.Ensuring the reliability, security, and performance of infrastructure to meet the high demands of large-scale machine learning workloads.About YouWe seek individuals with the following qualifications and traits:Required Technical Skills:Experience in building and managing ML infrastructure at scale.Expertise in PyTorch and distributed training paradigms.Hands-on experience with Ray.Familiarity with at least one modern RL training framework such as verl, NeMo-RL, ART, Atropos, or similar.Proficiency in Python and systems programming.Experience with container orchestration tools (Kubernetes), and infrastructure as code methodologies (Terraform).What Makes You Successful:Strong systems thinking with an ability to design for scalability.Exceptional debugging skills across the entire technology stack.A collaborative mindset and strong communication skills to effectively liaise with researchers and engineers.Self-motivated and capable of solving problems independently while taking ownership of projects.

Join Strava as a Senior Machine Learning Engineer and contribute to our mission of helping athletes perform better. In this role, you will design and implement advanced machine learning algorithms to enhance the Strava experience for millions of users globally. You will collaborate with cross-functional teams to drive innovation and ensure our technology remains at the forefront of the industry.

At Lyft, we are driven by our mission to connect and serve our communities. We strive to foster a workplace where every team member feels valued and has the opportunity to excel. With over half a billion rides and counting, Lyft is tackling complex challenges on a grand scale, utilizing cutting-edge AI and Machine Learning technologies to enhance customer experiences. The Artificial Intelligence, Machine Learning, and Operations Research Platforms team (AIMLOR) is on the lookout for a Senior Machine Learning Engineer who will play a pivotal role in constructing AI Platform components that empower essential AI applications across Lyft. Mastery in Generative AI and platform development is crucial for this position. You will contribute to our platform that facilitates real-time, online, and offline AI and ML model execution, development, and iteration. Collaborating with a team of talented Machine Learning and Software Engineers, you will work on intricate problems and define solutions that make a direct impact on our systems throughout the organization. If you are enthusiastic about building an AI Platform at scale with applications spanning every aspect of our company, we want to hear from you. If you are a creative thinker with a strong background in AI and machine learning systems and are passionate about leveraging data to solve business challenges in a dynamic, innovative, and collaborative environment, we invite you to apply.

About SesameAt Sesame, we envision a future where computers possess lifelike qualities, enabling them to see, hear, and interact with us in natural and human-like ways. We are dedicated to creating innovative voice agents that seamlessly integrate into our daily lives. Our talented team comprises founders from Oculus and Ubiquity6, along with seasoned professionals from Meta, Google, and Apple, boasting extensive expertise in both hardware and software development. Join us as we redefine the boundaries of technology and create a world where computers come to life.About the RoleAs a Machine Learning Scientist at Sesame, you will play a pivotal role in advancing our product goals through innovative research. We seek a detail-oriented individual with a strong background in Natural Language Processing (NLP), Speech Recognition, and/or Computer Vision, particularly with a focus on deep learning methodologies. You will stay abreast of the latest research and leverage your creativity and intuition to devise novel solutions tailored to our unique applications.Responsibilities:Contribute to the design and enhancement of machine learning models across diverse modalities.Engage with the complete ML stack, including model architecture, data curation, evaluation metrics, and training and inference infrastructure, while conducting research and experimentation.Identify and adopt promising techniques from existing literature, while innovating new methods as necessary to meet our distinct objectives.Required Qualifications:Demonstrated ability to work independently in environments characterized by high ambiguity.Published research in NLP, Speech Recognition, or Computer Vision focused on large-scale deep learning projects.Proficient understanding of cutting-edge advancements in artificial intelligence.Bachelor’s degree or higher in Computer Science or a related field.Preferred Qualifications:Master’s or PhD degree is preferred.Experience working on product development.Familiarity with startup environments.Sesame is committed to fostering a workplace that values, respects, and empowers everyone. We welcome applicants from diverse backgrounds, embracing all aspects of identity, race, gender, orientation, and ability. We also provide reasonable accommodations for individuals with disabilities — please contact careers@sesame.com for assistance.

About PoesisPoesis is a pioneering AI-native investment manager that is transforming the landscape of U.S. equities through innovative foundation models. We are developing cutting-edge AI systems designed to predict market trends and exceed the performance of traditional investment managers. This exciting work represents frontier research that is validated in real-world scenarios. Your contributions will play a crucial role in influencing investment strategies and enhancing portfolio outcomes.Location & WorkstyleLocated in the vibrant San Francisco Bay Area, near Stanford, we support a Hybrid work model, requiring several days on-site each week.Relocation assistance is available.About the RoleAs a Founding Machine Learning Engineer, you will be the first full-time ML hire at Poesis, responsible for translating research and data into scalable production models. You will develop the initial ML pipelines from the ground up, managing everything from data ingestion and preprocessing to model training, validation, and signal generation. This role is ideal for a hands-on professional who excels in coding, designing experiments, and quickly delivering validated results.You will collaborate closely with the CEO and Chief Scientist, taking ownership of both the implementation process and iterative improvements. As the system scales, you will help transition it into a full production platform and establish best practices for future team members.ResponsibilitiesDesign, develop, and maintain the foundational ML infrastructure for Poesis’ investment platform.Create reproducible pipelines for data ingestion, feature engineering, and model training.Establish backtesting and evaluation frameworks with defined performance metrics.Provide regular, detailed reports on model accuracy, feature significance, and overall portfolio impact.Work closely with the Chief Scientist to refine model hypotheses and assess production readiness.Ensure high code quality through version control, testing, reproducibility, and thorough documentation.Develop robust backtesting frameworks and model validation tools, incorporating walk-forward evaluation and risk management controls.Integrate with leading financial data providers such as Bloomberg, FactSet, Refinitiv, and CapIQ.Implement foundational MLOps practices, including model versioning, CI/CD, monitoring, and documentation.Define and refine “demo-able” workflows that link model outputs to investment decision-makers.

Company OverviewAt Echo Neurotechnologies, we are a pioneering startup in the Brain-Computer Interface (BCI) domain, committed to spearheading advancements through state-of-the-art hardware engineering and AI innovations. Our vision is to create transformative technologies that empower individuals living with disabilities, enhancing their autonomy and overall quality of life.Team CultureBecome part of a passionate and dedicated team where your expertise is valued. In our dynamic early-stage environment, you will have the chance to influence key decisions that lead to significant, long-term impacts. We prioritize continuous learning and development, encouraging cross-functional collaboration where your contributions play a crucial role in our success.Job SummaryWe are on the lookout for a skilled Applied AI Scientist to join our innovative team. The successful candidate will harness machine learning (ML) and artificial intelligence (AI) methodologies to analyze extensive datasets of time-series data and their accompanying metadata, crafting sophisticated encoding and decoding models to decode brain activity. This work will not only propel scientific advancements but also translate into impactful solutions for patients with physical disabilities.Key ResponsibilitiesDevelop models for brain data and metadata to derive insights from both existing and future datasets, establishing high-performance inference and translation pipelines.Design and implement cutting-edge transformers and other ML models to translate brain signals into control commands for digital devices.Stay abreast of the latest AI methodologies, rapidly evaluating their applicability and effectiveness through prototypical assessments with company datasets.Collaborate effectively within a small team to refine models, design the data-science platforms, and integrate ML models into our product applications.Ensure that all code, analysis pipelines, and results are versioned, well-documented, and highly interpretable for maximum reproducibility.Assist in creating documentation for our Quality Management System, specifically related to ML implementations that will be incorporated into medical products.

Preference Model creates new types of training data to help artificial intelligence systems improve beyond their current limits. The team specializes in building reinforcement learning environments that test both research and engineering abilities, giving models the chance to learn from realistic feedback. Founded by former members of Anthropic’s data division, Preference Model draws on experience building data infrastructure, tokenizers, and datasets for Claude. The company partners with top AI labs and is backed by a16z. Role overview This entry-level machine learning engineer position is based in San Francisco and is intended for recent graduates. The focus is on building and maintaining the infrastructure that powers Preference Model’s reinforcement learning training pipeline. The team is small, so each engineer takes responsibility for their projects. Deep production experience is not required, but strong technical fundamentals, curiosity about reinforcement learning, and the ability to learn quickly are essential. What you will do Develop and scale distributed training systems with PyTorch Design automation for monitoring, debugging, and recovery during large-scale training runs Collaborate with researchers to turn RL training experiments into dependable infrastructure Enhance performance and reliability for GPU and TPU workloads Requirements Recent graduate (BS, MS, or PhD) in Computer Science, Machine Learning, or a related field Interest in reinforcement learning and AI infrastructure

Join Orchard as a Machine Learning Engineer and play a pivotal role in transforming data into actionable insights. In this dynamic position, you will leverage your expertise in machine learning algorithms and data analysis to develop innovative solutions that enhance our products and services.We are looking for a proactive team player who thrives in a fast-paced environment and possesses strong problem-solving skills. You will collaborate with cross-functional teams, engage with large datasets, and contribute to the design and implementation of machine learning models.