Machine Learning Engineer - Imitation & Reinforcement Learning for Robotics

Whatnot is looking for a Machine Learning Engineer focused on Growth to strengthen data-driven decisions and support platform expansion. This position is based in San Francisco, CA. Role overview This role centers on developing machine learning solutions that help drive growth and refine user experiences. The work involves analyzing large and complex data sets, building predictive models, and implementing algorithms to improve platform performance. Collaboration Machine Learning Engineers in this role work closely with cross-functional teams. Expect to partner with colleagues across product, engineering, and analytics to translate business needs into technical solutions. Key responsibilities Analyze data to uncover trends and insights that inform product direction Develop and deploy predictive models to support growth initiatives Implement algorithms that optimize platform performance and user experience

About MercorAt Mercor, we're revolutionizing the future of work. We collaborate with top AI labs and enterprises to deliver the human insights crucial for AI development.Our extensive talent network trains cutting-edge AI models, much like educators nurture students: by imparting invaluable knowledge, experience, and context that transcends mere code. Currently, over 30,000 specialists in our network collectively generate more than $2 million daily.Mercor is pioneering a new category of work where expertise fuels AI progress. Achieving this vision requires a dynamic, fast-paced, and deeply dedicated team. You’ll collaborate with researchers, operators, and AI companies at the forefront of transforming systems that redefine society.As a profitable Series C company valued at $10 billion, we operate on-site five days a week in our offices located in San Francisco, NYC, or London.About the RoleIn your role as a Machine Learning Engineer on the growth team, you will develop the infrastructure that powers Mercor’s hiring engine: from indexing and global discovery to cross-platform sourcing and engagement, real-time scoring and personalization, and high-throughput conversion pipelines that transform interest into hires.What You Will Build:Low-latency ranking and matching pipelines that process thousands of signals.Global off-platform people search, job distribution, and ad/acquisition infrastructure.Production ML and feature infrastructure for personalization and incentive modeling.Real-time event and data pipelines, high-throughput APIs, and observability for mission-critical services.Who We Are Looking For: We seek engineers with a strong background in building distributed backends or ML infrastructure, demonstrated ownership of large-scale matching, indexing, recommender, or search systems; robust instincts for production, and experience with high-throughput services, monitoring, and reliability.Why Join Us: If you are looking for backend work that combines ML, distributed systems, and real revenue impact, the Growth team is where you belong.Tech Stack: Python, Go, embeddings, fine-tuning, RAG, Kafka, Postgres, Redis, Elasticsearch, Kubernetes, Terraform

About Pinterest:At Pinterest, we strive to empower individuals worldwide to explore creative ideas, envision new possibilities, and curate lasting memories. Our mission is to inspire everyone to craft a life they love, and this journey begins with the talented people behind our platform.Join us in a career that fuels innovation for millions, transforms passion into growth, celebrates diverse experiences, and embraces the flexibility to perform at your best. Crafting a career you cherish? It’s entirely possible.We are seeking a visionary Director of Machine Learning to spearhead the ML function within our Growth organization. This leader will outline the long-term ML vision, strategy, and operational framework that drives user engagement and growth across Pinterest's platforms.You will manage several teams of machine learning engineers and managers, addressing essential Growth challenges such as activation, retention, notifications, SEO, paid acquisition, and lifecycle personalization. Your role will blend deep technical expertise with strong leadership and product intuition to implement industry-leading practices in recommendation systems, ranking algorithms, experimentation, deep learning, and generative AI. As the Director of Machine Learning for Growth, you will oversee the health, performance, and evolution of our ML ecosystems, ensuring our technology meets the business and product requirements vital for making Pinterest an engaging and inspiring platform for everyone. This entails:Collaborating with senior Product, Data Science, and Engineering leaders to define and execute a multi-year strategy for Pinterest’s Growth systems.Establishing a cohesive ML architecture and roadmap for Growth that leverages shared platforms while enabling rapid iteration.Building, nurturing, and retaining a world-class team of machine learning leaders and engineers.Serving as a prominent thought partner and advocate for Growth ML among executives and cross-functional stakeholders.You will also cultivate a healthy and inclusive community where ML practitioners across Growth can learn best practices, collaborate efficiently, and align with our technical direction.

Whatnot is looking for a Machine Learning Engineer focused on Growth to help shape the platform’s direction. This position is based in San Francisco, CA. Role overview This role centers on developing and applying machine learning solutions that support user experience improvements and drive business growth. Expect to work on projects that directly impact how users interact with the platform and contribute to key growth initiatives. What you will do Design and build machine learning models tailored to growth-related challenges Collaborate with teams to deliver solutions that improve user engagement Apply technical expertise to solve complex problems in a growing company Who this role suits This position is well-suited for engineers who are eager to take on new challenges and enjoy working in an environment where their work has a visible impact on business outcomes.

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.

Join Handshake as a Machine Learning Engineer I, where you will have the opportunity to work on cutting-edge machine learning projects that drive our innovative solutions. Collaborate with a talented team to develop algorithms and models that enhance our product offerings and improve user experiences.

Join Our Innovative Team at HiveHive is at the forefront of cloud-based AI solutions, revolutionizing how organizations understand, search for, and generate content. Trusted by many of the world's largest and most groundbreaking companies, we empower developers with premier pre-trained AI models that handle billions of API requests monthly. Our turnkey software applications leverage proprietary AI models and datasets, driving transformative advancements in content moderation, brand protection, sponsorship measurement, and context-based ad targeting.With over $120M in funding from prominent investors like General Catalyst, 8VC, Glynn Capital, Bain & Company, and Visa Ventures, Hive is rapidly expanding. Our dynamic team of over 250 employees operates from our San Francisco, Seattle, and Delhi offices. If you are passionate about shaping the future of AI, we invite you to explore opportunities with us!About the Machine Learning Engineer RoleAs we strive to achieve our ambitious vision, we seek exceptional machine learning engineers to join our team. We are looking for enthusiastic developers who are eager to remain at the cutting edge of deep learning technology, designing and deploying state-of-the-art neural network models into production. Our ideal candidates thrive in working with large-scale datasets and demonstrate a keen interest in mastering new technologies across the machine learning spectrum. We value individuals who are proactive and take ownership of their projects, contributing innovative ideas and practical implementations. Experience in building machine learning applications from the ground up and designing scalable, maintainable data pipelines is essential.

Join our dynamic Personalization team at Boomtrain as a Machine Learning Engineer. We are in search of a skilled engineer who will play a pivotal role in developing and enhancing our recommendation systems that cater to a variety of customers.In this role, you will collaborate with a talented team dedicated to designing and implementing innovative models and systems that deliver personalized recommendations. You will have the opportunity to work on complex engineering challenges and contribute to generating hundreds of millions of recommendations daily.This position offers a unique chance to engage in end-to-end project work and make a significant impact on our personalization initiatives.Key Responsibilities:Research and propose advanced recommendation and optimization models to enhance our personalization systems.Develop and maintain offline model generation pipelines.Design and maintain online recommendation serving systems.

OverviewPulse is revolutionizing data infrastructure by addressing the critical challenge of extracting accurate, structured information from complex documents on a large scale. Our innovative approach to document understanding integrates intelligent schema mapping with advanced extraction models, outperforming traditional OCR and parsing methods.As a dynamic and rapidly growing team of engineers based in San Francisco, we empower Fortune 100 companies, Y Combinator startups, public investment firms, and growth-oriented businesses. With the backing of top-tier investors, we are on an exciting growth trajectory.What sets our technology apart is our cutting-edge multi-stage architecture:Layout comprehension with specialized component detection modelsLow-latency OCR models designed for targeted data extractionAdvanced algorithms for determining reading order in complex formatsProprietary table structure recognition and parsing capabilitiesFine-tuned vision-language models for interpreting charts, tables, and figuresIf you are passionate about the convergence of computer vision, natural language processing, and data infrastructure, your contributions at Pulse will directly influence our customers and shape the future of document intelligence.

Join Handshake as an Associate Machine Learning Engineer and embark on an exciting journey in the world of artificial intelligence and machine learning. In this role, you will collaborate with a talented team to develop innovative solutions that leverage cutting-edge technologies. You'll have the opportunity to contribute to real-world projects, enhancing your skills while driving impactful results.

Charter:Join us as a pivotal member of a groundbreaking team dedicated to revolutionizing the field of toxicology by developing advanced AI systems that will replace traditional lab and animal experiments.What We Seek:We are on the lookout for exceptional individuals who can inspire those around them and drive the team towards greatness. Our ideal candidate is someone with high agency—able to identify priorities and take action. We value unique passions and hobbies that may seem niche but reveal a deep commitment and curiosity when explored. Candidates should approach challenges with both intentionality and a sense of wonder, embodying the spirit of exploration akin to an immigrant in a new land or a self-taught coder. A strong desire to learn and grow, coupled with technical excellence and a commitment to mastering one’s craft, is essential. We want those who are willing to tackle daunting challenges and derive satisfaction from the journey as much as the outcome.Your Responsibilities:Establish the foundational end-to-end ML/AI system, including wetlab data generation, data cleaning/processing, model architecture, training, inference, and deployment strategies.Lead innovative research and development initiatives focused on elucidating the interplay between chemistry and biology.Design and scale large models that are pretrained on paired chemistry and biological imagery.Conduct applied research aimed at optimizing, aggregating, and pooling embeddings.Become a thought leader in emerging and underexplored domains, such as molecular graph representations and generative diffusion for biological applications.Develop entrepreneurial skills alongside engineering expertise by creating impactful solutions that deliver substantial value for scientists.Deliver outstanding technology and products that redefine industry standards.Preferred Attributes:...

Position: Machine Learning EngineerAbout Us:At UnitX, we are pioneering the development of cutting-edge physical AI systems designed to automate repetitive visual tasks within manufacturing environments. Our dynamic startup thrives on a diverse team of experts from renowned institutions such as Stanford, MIT, and Google. To date, we have successfully implemented over 1,000 mission-critical AI systems across more than 190 of the world's top manufacturing production lines. Annually, our AI inspection systems oversee the quality of products valued at $15 billion.Join us for a unique opportunity to contribute to groundbreaking computer vision technologies that are transforming global manufacturing efficiency.Your Responsibilities:Design and implement innovative algorithms to analyze raw sensor data for defect detection, focusing on pixel-level precision in high-resolution image and 3D data segmentation.Develop robust software solutions that operate continuously on production lines, executing our algorithms in real-time with decision-making latency under 20ms.Create metrics and tools for comprehensive model performance evaluation, enhancing system visibility and interpretability.Research and explore novel methodologies, pushing the boundaries of AI technology, including Stable Diffusion and SAM, to deliver critical applications in manufacturing.Who You Are:Bachelor's degree in Computer Science, Mathematics, Physics, or a related technical discipline, or equivalent experience showcasing solid mathematical foundations.A minimum of 2 years of experience developing machine learning models focused on computer vision applications in production settings.Deep understanding of Deep Learning theories and practical applications, with proficiency in frameworks such as PyTorch or TensorFlow. Strong Python programming skills for creating efficient, maintainable solutions within extensive codebases.Excellent communication and decision-making abilities, able to articulate experimental rationale and judiciously navigate between exploration and exploitation strategies.Demonstrated resilience and adaptability in complex, uncertain environments.Preferred Qualifications:Experience with large-scale data processing and algorithm optimization.Familiarity with tools for machine learning and data visualization.

Airbnb began in 2007 with two hosts and three guests in San Francisco. Since then, the platform has grown to over 5 million hosts and more than 2 billion guests worldwide. Airbnb connects people with unique places to stay and experiences, building authentic community connections across nearly every country. The team: Growth Platform Engineering The Growth Platform team focuses on driving sustainable, long-term growth for Airbnb. The team’s mission centers on building an agentic system and supporting capabilities to help all Airbnb offerings grow, both now and in the future. Efforts include delivering personalized and relevant content and product experiences to users, both on and off the Airbnb platform. The team is working toward a future where AI identifies opportunities, creates campaigns, personalizes experiences, and optimizes outcomes with minimal human input. This journey moves through a maturity curve: AI-assisted, agentic, and ultimately autonomous systems, always with human oversight to ensure brand safety, quality, and compliance. Growth Platform Engineering is tightly integrated with the Airbnb product, enhancing the customer journey and enabling new ways for users to engage. The platform supports a range of digital marketing channels, landing pages, email, push notifications, SMS, and digital advertising, as well as the machine learning and data infrastructure that powers these efforts. What you will do Develop AI-driven solutions to shape the future of Airbnb’s agentic growth platform, using the latest AI methodologies. Lead and mentor engineers through brainstorming, design, and implementation of AI products and features, from initial concept to deployment. Work at the intersection of technical depth, architectural innovation, and mentorship as a Senior Staff Engineer. Collaborate with cross-functional teams to build scalable systems that operate globally. Help evolve the foundational elements of Airbnb’s AI-powered growth systems.

Join Hive as a Senior Machine Learning Engineer and help shape the future of AI! We are seeking passionate individuals who excel at developing and deploying cutting-edge deep learning models. In this role, you will work with large-scale datasets to create innovative machine learning solutions, collaborating closely with a talented team of engineers to push the boundaries of artificial intelligence. Ideal candidates will have a proven track record of building and scaling machine learning projects from conception to production, along with a strong commitment to continuous learning and personal ownership in their work.

Company Overview At Specter, we are pioneering a software-defined "control plane" designed to enhance the real-world perception of physical assets. Our mission begins with safeguarding American businesses by providing them with comprehensive insights into their physical environments.To achieve this, we are developing a robust hardware-software ecosystem leveraging multi-modal wireless mesh sensing technology. This innovation allows us to significantly reduce the cost and time involved in sensor deployment by a factor of ten. Ultimately, our platform aims to serve as the perception engine for businesses, facilitating real-time visibility and autonomous management of their operational perimeters.Our co-founders, Xerxes and Philip, are deeply committed to empowering our partners in the rapidly evolving landscape of physical AI and robotics. We are a dynamic, rapidly expanding team comprised of talent from Anduril, Tesla, Uber, and the U.S. Special Forces.Position Overview Specter is seeking a dedicated Machine Learning Infrastructure Engineer to construct and optimize the ML systems that drive real-time perception and inference capabilities across our edge-cloud platform. This position will involve overseeing the training, deployment, and enhancement of computer vision and sensor fusion models, aimed at enabling autonomous monitoring and decision-making for our clients' physical assets.Key Responsibilities Include:Design and implement scalable ML training pipelines for computer vision applications, including object detection, tracking, classification, and segmentation.Develop efficient model serving infrastructures to facilitate real-time inference on edge devices with limited computational and power resources.Optimize models for deployment on embedded hardware, employing techniques such as quantization, pruning, TensorRT, ONNX, and CoreML.Create continuous training and evaluation systems to enhance model performance through feedback loops derived from production data.Establish data pipelines for the ingestion, labeling, versioning, and management of extensive multi-modal sensor datasets, including video, radar, lidar, and thermal data.Implement model monitoring frameworks, A/B testing methodologies, and performance analytics for deployed perception systems.Collaborate with perception researchers to transition models from research environments to scalable production across thousands of edge nodes.Construct tools and infrastructure for distributed training, hyperparameter optimization, and experiment tracking.

Join Reducto as a Machine Learning Evaluation Engineer where you will play a critical role in assessing and enhancing machine learning models. You will collaborate closely with data scientists and engineers to ensure our systems are efficient and accurate, bringing innovative solutions to challenging problems in the machine learning space.

Saris AI, based in San Francisco with teams in Montreal and Toronto, develops advanced agentic AI systems for the banking industry. The company focuses on automating complex workflows that require long-context reasoning, integration with legacy systems, and strict compliance. With live AI agents already supporting real customer operations, Saris AI is expanding quickly and seeking technical leaders who want to shape the future of work in banking. Role overview This is a hands-on leadership position within the core engineering team in San Francisco. The Machine Learning Engineering Lead will guide machine learning systems from initial concept through scaling, helping define both the technical vision and the supporting infrastructure. What you will do Oversee the ML/AI function end to end, setting technical direction and standards across the company. Design and supervise development of multi-modal, agentic AI systems that power live customer workflows. Build and manage evaluation frameworks, datasets, and metrics to improve agent performance. Drive productionization of ML systems with an emphasis on reliability, scalability, and compliance. Recruit, develop, and mentor a high-performing ML team, fostering strong practices in modeling, experimentation, and deployment. Requirements 8+ years of experience in machine learning or AI engineering, including time as a technical lead or manager. Proven track record leading ML projects from concept to production deployment. Expertise with large language models (LLMs) and/or agentic systems, especially in customer-facing products. Strong grasp of ML fundamentals: deep learning, transformers, model evaluation, and trade-offs. Hands-on experience scaling ML systems in production, with a focus on monitoring, iteration, and reliability. Ability to lead engineering teams, influence architecture, and set technical direction. Comfort working in early-stage, ambiguous, and rapidly changing environments.

About Scribd:At Scribd Inc. (pronounced 'scribbed'), we're on a mission to ignite human curiosity. Join our innovative team as we craft a diverse world of stories and knowledge, democratizing the exchange of ideas and empowering collective intelligence through our four flagship products: Everand, Scribd, Slideshare, and Fable.This job posting is for an exciting, open position within our organization.We foster a culture where authenticity and boldness thrive, facilitating open debates and commitments as we embrace the unexpected. Every team member is empowered to take initiative, prioritizing the needs of our customers.In terms of workplace structure, we prioritize a balance between personal flexibility and communal connections. Our Scribd Flex initiative allows employees, in collaboration with their managers, to determine their daily work styles that best suit their individual needs while promoting intentional in-person interactions to enhance collaboration and company culture. Therefore, occasional in-person attendance is mandatory for all employees, regardless of their location.What do we seek in our new team members? We value 'GRIT'—the intersection of passion and perseverance toward long-term goals. At Scribd Inc., we believe in harnessing the potential that GRIT unlocks and encourage each employee to adopt a GRIT-driven approach to their work. This means we are looking for individuals who can set and achieve Goals, deliver Results in their responsibilities, contribute Innovative ideas, and positively impact the broader Team through collaboration and a positive attitude.About Our Machine Learning Team:Our Machine Learning team is pivotal in developing the platform and product applications that drive personalized discovery, recommendations, and generative AI functionalities across Scribd, Slideshare, and Everand. The ML team operates on the Orion ML Platform, providing essential ML infrastructure such as a feature store, model registry, model inference systems, and embedding-based retrieval (EBR). Our Machine Learning Engineers collaborate closely with the Product team to integrate machine learning into user-facing features, including real-time personalization and AskAI LLM-powered experiences.

Join Middesk as a Machine Learning Engineer and contribute to cutting-edge projects that leverage machine learning to drive business insights. You will collaborate with a dedicated team of data scientists and engineers, developing algorithms and models that enhance our product offerings and improve user experience.