Machine Learning Engineer - Imitation & Reinforcement Learning for Robotics

Be Part of the Future of Autonomous RoboticsAt Bedrock Robotics, we are pioneering the transition of AI from theoretical frameworks to practical applications in the built environment. Our team is comprised of seasoned professionals who have been instrumental in the success of innovative companies such as Waymo, Segment, and Uber Freight. We are at the forefr…

About FaireFaire is a transformative online wholesale marketplace, driven by the conviction that local businesses are the future. Independent retailers around the globe generate more revenue than massive corporations like Walmart and Amazon combined, yet individually, they remain small. At Faire, we harness technology, data, and machine learning to connect this vibrant community of entrepreneurs. Think of your favorite local boutique — we empower them to discover and sell the best products from around the world. With our innovative tools and insights, we aim to level the playing field, enabling small businesses to thrive against larger competitors.By championing the growth of independent businesses, Faire positively impacts local economies on a global scale. We’re in search of intelligent, resourceful, and passionate individuals to join us in fueling the shop local movement. If you value community, we invite you to be part of ours.About this RoleAs the Senior Staff Machine Learning Platform Engineer, you will spearhead the technical vision and evolution of Faire's ML platform. You will establish standards, influence organization-wide architecture, and lead intricate, cross-functional initiatives that enhance data science velocity at scale. This position is crucial for adapting ML workflows to leverage modern AI productivity tools. You will not only develop models but also design the systems that enable those models to empower tens of thousands of small retailers in competing and growing their local businesses.

PhD Internship: Machine Learning EngineerAbout HandshakeAt Handshake, we are revolutionizing career development in the AI economy. With a network of over 20 million skilled professionals and partnerships with 1,600 educational institutions and 1 million employers, including all Fortune 50 companies, Handshake is the go-to platform for career exploration, hiring, and skill enhancement. Join us as we help individuals transition from freelance opportunities to internships and full-time roles, connecting talent with opportunities at every career stage.Our unique position in the market has catalyzed impressive growth, with projections indicating that we will triple our ARR by 2025.Why You Should Join Handshake Now:Contribute to the evolution of careers in the AI economy on a global scale, making a tangible impact.Collaborate with top AI labs, Fortune 500 companies, and prestigious educational institutions.Play a key role in building a fast-growing business targeting multi-billion-dollar revenues.Position OverviewAs a Machine Learning Engineering Intern, you will be instrumental in crafting intelligent product experiences that assist students in discovering and securing opportunities. Your responsibilities will encompass search algorithms, recommendations, and matching systems that enhance job exploration on Handshake.This internship will provide you with practical experience in developing, assessing, and deploying machine learning models within a production environment, as well as insights into the design, optimization, and maintenance of large-scale ML systems.This is a paid, full-time summer internship with two cohort options:May 18 – August 7, 2026June 15 – September 4, 2026Key Responsibilities:Collaborate with experienced engineers and data scientists to develop machine learning models that enhance product features and improve user experience.Engage in experimentation, model evaluation, and performance monitoring.Participate in technical discussions, brainstorming sessions, and team reviews.Document methodologies and findings to facilitate knowledge sharing and long-term improvements to systems.QualificationsEssential Qualifications:Currently pursuing a PhD in Computer Science, Data Science, Machine Learning, or a related field.Strong programming skills in Python and familiarity with machine learning libraries (e.g., TensorFlow, PyTorch).Experience with data analysis and statistical modeling.Excellent problem-solving abilities and analytical thinking.Strong communication skills and ability to work collaboratively in a team environment.

About Prophecy As a pioneer in AI-native data preparation and analysis, Prophecy is reshaping the way leading enterprises transform data chaos into actionable insights. We are introducing the AI-native data lifecycle (generate, refine, deploy), where our top-tier AI agents collaborate seamlessly with human expertise through visual and document interfaces. This innovative approach enables comprehensive data analysis, transformation, and preparation, delivering trusted insights at an enterprise scale. Don’t miss the opportunity to be part of this journey—join Prophecy and contribute to the next data revolution.

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.

Join tvScientific as a Senior Machine Learning Engineer and be at the forefront of developing and deploying innovative machine learning solutions that drive advertising efficiency. Your expertise will contribute to building cutting-edge algorithms and systems that enhance our clients' marketing strategies.In this role, you will collaborate with cross-functional teams to translate business requirements into technical specifications, and develop scalable models that leverage large datasets. Your passion for machine learning and data science will help shape the future of advertising technology.

At Patreon, we are a dynamic media and community platform empowering over 300,000 creators to offer exclusive content and experiences to their most dedicated fans. Our platform provides creators with diverse tools to connect with their audience and sustain a thriving business through options like paid memberships, community interactions, live video streams, and direct sales to fans.Our mission is clear: to fund the creative class. We take pride in being at the forefront of this movement, having:Generated over $10 billion for creators since our inception.Facilitated more than 100 million free memberships for fans who are not yet ready to pay.Currently supporting over 25 million paid memberships on our platform.We are committed to enhancing our creator platform and expanding our talented team within the creator economy, and we are seeking a Senior Machine Learning Engineer to join us in this mission.This position is located in San Francisco or New York and requires in-office attendance for 2 days per week in a hybrid work model.

About Our Company:At Scribd Inc. (pronounced “scribbed”), we are dedicated to igniting human curiosity. Join us in crafting a universe of stories and knowledge, where we democratize the flow of ideas and information, empowering collective expertise through our innovative products: Everand, Scribd, Slideshare, and Fable.This job posting represents a fully approved, open role within our organization.We cultivate a culture where our employees can express their authentic selves and take bold steps; where we engage in healthy debate and commit to our decisions while adapting to the unexpected; and where every team member is encouraged to take initiative as we focus on our customers.In terms of workplace structure, we value a blend of individual flexibility and community engagement. With our flexible work benefit, Scribd Flex, employees can collaborate with their managers to determine the work style that best accommodates their personal needs. A key aspect of Scribd Flex emphasizes intentional in-person interactions to strengthen collaboration, culture, and connection. Therefore, occasional in-person attendance is necessary for all Scribd Inc. employees, regardless of their location.What qualities do we seek in our new team members? We hire for “GRIT.” In essence, GRIT embodies the intersection of passion and perseverance towards long-term objectives. At Scribd Inc., we are motivated by the potential that this can unlock, and we encourage each employee to adopt a GRIT-ty approach in their work. Tactically, GRIT is a practical acronym that outlines the standards we uphold for ourselves and each other. This means we are searching for candidates who can set and achieve Goals, deliver Results within their job functions, contribute Innovative ideas and solutions, and positively influence the broader Team through collaboration and a proactive attitude.About Our TeamThe Search team drives personalized discovery across Scribd’s suite of products, providing tailored and engaging suggestions to millions of users. We operate at the crossroads of large-scale data, advanced machine learning, and product innovation—working collaboratively across brands and platforms to enhance user experiences in reading, listening, and learning. Our diverse team consists of frontend, backend, and ML engineers who partner closely with product managers, data scientists, and analysts.About the RoleWe are seeking a Senior Machine Learning Engineer to join our Search team, where you will play a pivotal role in enhancing our algorithms and improving user experiences.

About Liquid AIFounded as a spin-off from MIT CSAIL, Liquid AI specializes in creating versatile AI systems designed for optimal performance across various deployment platforms, including data center accelerators and on-device hardware. Our technology emphasizes low latency, minimal memory consumption, privacy, and dependability. We collaborate with leading enterprises in sectors such as consumer electronics, automotive, life sciences, and financial services. As we experience rapid growth, we are on the lookout for exceptional talent to join our team.The OpportunityThe Data team at Liquid AI drives the development of our Liquid Foundation Models, focusing on pre-training, vision, audio, and emerging modalities. With the stagnation of public data sources, the effectiveness of our models increasingly relies on specially curated datasets. We are seeking engineers with a machine learning mindset who can efficiently gather, filter, and synthesize high-quality data at scale.At Liquid AI, we regard data as a research challenge rather than an infrastructural issue. Our engineers conduct experiments, design ablations, and assess how data-related decisions impact model quality. We will align you with a team where you can experience rapid growth and make a significant impact, be it in pre-training, post-training reinforcement learning, vision-language, audio, or multimodal applications.While we prefer candidates in San Francisco and Boston, we are open to considering other locations.What We're Looking ForWe are in search of a candidate who:Thinks like a researcher and executes like an engineer: You should be able to formulate hypotheses, conduct experiments, and evaluate results. Our engineers produce research-level code while our researchers implement production systems.Learns quickly and adapts: You will be working in rapidly evolving modalities, so the ability to quickly grasp new domains and thrive in ambiguity is essential.Prioritizes data quality: We hold data quality in high regard; tasks such as filtering, deduplication, augmentation, and evaluation are key responsibilities, not afterthoughts.Solves problems autonomously: Data engineers operate within training groups (pre-training and multimodal). While collaboration is crucial, we expect ownership and self-direction.The WorkDevelop and maintain data processing, filtering, and selection pipelines at scale.Establish pipelines for pretraining, midtraining, supervised fine-tuning, and preference optimization datasets.Design synthetic data generation systems utilizing large language models (LLMs), structured prompting, and domain-specific generative techniques.

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 our innovative DashPass team at DoorDash as a Senior Machine Learning Engineer, where you'll play a pivotal role in harnessing AI and advanced machine learning to revolutionize subscriber personalization strategies. In this dynamic position, you will lead the design and development of large-scale ML systems that enhance user engagement and retention across the DashPass subscriber journey. Your expertise in causal inference modeling and incentive optimization will drive impactful decisions, ensuring our subscribers receive tailored rewards and promotions that resonate with their preferences. Collaborate closely with cross-functional teams to create experiments and production ML systems that directly influence growth metrics. This is a unique opportunity to be at the forefront of personalization efforts that will shape the future of our offerings.

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

Why Join Achira?Become part of an elite team comprising scientists, machine learning researchers, and engineers dedicated to transforming the predictability of the physical microcosm and revolutionizing drug discovery.Explore uncharted territories: we are on a mission to innovate next-generation model architectures that merge AI with chemistry.Engage in large-scale operations: harness massive computational resources, extensive datasets, and ambitious objectives.Take ownership of significant projects from inception to deployment on large-scale infrastructures.Thrive in a culture that values precision, speed, execution, and a proactive mindset.About the PositionAt Achira, we are committed to developing state-of-the-art foundation models that tackle the most complex challenges in simulation for drug discovery and beyond. Our atomistic foundation simulation models (FSMs) serve as world models of the physical microcosm, incorporating machine learning interaction potentials (MLIPs), neural network potentials (NNPs), and various generative models.We are seeking a Machine Learning Research Engineer (MLRE) who excels at the intersection of advanced machine learning and rigorous research methodologies. Collaborate closely with our research scientists to design and enhance intelligent training systems that propel us beyond contemporary architectures into a new era of ML-driven molecular modeling.Your mission is clear yet ambitious: to establish the foundational frameworks for training atomistic simulation models at scale. This entails a deep dive into architecture, data, optimizers, losses, training metrics, and representation learning, all while constructing high-performance systems that maximize the potential of our models. In this role, you will be instrumental in creating a blueprint for pretraining FSMs similar to today’s large-scale generative AI systems, making a significant impact on drug discovery.At Achira, you will have the chance to pioneer models that comprehend and simulate the physical world at an atomic level, achieving unprecedented speed and accuracy.

About Wispr FlowAt Wispr Flow, we are revolutionizing the way people interact with technology, making it as simple and intuitive as conversing with a friend.As the leading voice dictation platform, Wispr Flow outpaces traditional keyboards by offering unparalleled accuracy and understanding right from the first interaction. Our solution is context-aware and personalized, functioning seamlessly across devices, whether on desktop or mobile.Looking ahead to 2026, we are not just stopping at dictation; our vision includes developing native actions—a sophisticated framework that comprehends user intent and operates dependably.Our team comprises AI researchers, designers, growth specialists, and engineers who are fundamentally reimagining human-computer interaction. We seek high-agency individuals who value transparent communication, prioritize user experience, and are detail-oriented. We thrive on constructive discussions, a commitment to truth, and making a tangible impact in the real world.With a remarkable growth rate of over 150% in quarterly revenue for the past year and having secured $81 million from top-tier venture capitalists and renowned angel investors, Wispr Flow is poised for significant advancement.

Company Overview:At Specter, we are pioneering a software-defined control plane for the physical realm, beginning with safeguarding American enterprises through comprehensive monitoring of their physical assets.Our innovative approach leverages a connected hardware-software ecosystem built on advanced multi-modal wireless mesh sensing technology. This breakthrough enables us to reduce the deployment costs and time for sensors by a factor of 10. Our ultimate goal is to establish a perception engine that provides real-time visibility of a company’s physical environment and facilitates autonomous operations management.Co-founders Xerxes and Philip are dedicated to empowering our partners in the rapidly evolving landscape of physical AI and robotics. Join our dynamic and rapidly expanding team comprised of talents from Anduril, Tesla, Uber, and the U.S. Special Forces.Position Overview:We are seeking a Perception AI Engineer who will be instrumental in transforming sensor data pipelines into actionable insights for our clients.Key Responsibilities:Implement and deploy a range of deep-learning models, including vision, vision-language, and large language models, within our sophisticated distributed perception system.Design and scale a production-ready data collection, labeling, and model retraining platform.Lead the design of a multimodal software user interface.

At Philo, we are a dedicated team of technology and product enthusiasts committed to reshaping the television landscape. We blend cutting-edge technology with the captivating medium of television to create the ultimate viewing experience. Our mission is to enhance streaming capabilities through innovative cloud delivery and sophisticated machine learning algorithms that personalize content discovery. As a Senior Machine Learning Engineer specializing in Recommendation Systems, you will be at the forefront of our content personalization initiatives, significantly enhancing user engagement and satisfaction. Your expertise will help ensure that every time users open the Philo app, they find something they want to watch. In this pivotal role, you will spearhead the development of advanced algorithms and large-scale systems that drive Philo's recommendation engine. Collaborating closely with data science, product, infrastructure, and backend engineering teams, you will tackle complex machine learning challenges and develop innovative, data-driven solutions that enhance content discovery and foster user retention.

Role overview Quizlet is looking for a Machine Learning Engineer to join the Monetization and Decision Systems team. The focus is on building models that help drive user engagement and support revenue growth using data-driven approaches. What you will do Design and implement machine learning models that contribute to monetization strategies and decision-making systems. Collaborate with engineering, product, and design teams to deliver solutions that scale. Apply machine learning skills to develop products used by millions of learners. Locations Denver, CO New York, NY San Francisco, CA Seattle, WA

Join Our Team at Humble RoboticsAt Humble Robotics, we are at the forefront of revolutionizing ground transportation. Our mission is to create an autonomous, zero-emissions hauler that significantly reduces freight costs through innovative vision-based AI, tailored for today's dynamic global logistics network.As part of a fast-paced, collaborative team comprised of industry veterans and creative minds, you will experience a culture that thrives on innovation and teamwork. We believe that while culture cannot be engineered, when it aligns, it creates an extraordinary journey.Be part of the progress!