Enabling Robots To Build So That Humans Can Create.
Senior Machine Learning Engineer - Reinforcement Learning
Location
United States
Posted
4 days ago
Salary
0
Seniority
Senior
No structured requirement data.
Job Description
Senior Machine Learning Engineer - Reinforcement Learning
Path Robotics
Role Description As a Sr. ML Engineer focused on Reinforcement Learning, you will design, implement, and optimize RL algorithms that enable intelligent agents to operate in dynamic, unstructured environments. This role involves working closely with cross-functional teams to design, test, and deploy innovative solutions that improve the performance and capabilities of our robotic systems. This role can be located in our Columbus, Ohio Headquarters or Remote. - Design, implement, and evaluate RL algorithms for robotic control, motion planning, and adaptive behaviors in dynamic, unstructured environments. - Develop and integrate RL policies with robot control systems, ensuring compatibility with hardware constraints and real-time requirements. - Collaborate with perception teams to fuse RL with vision, depth, and sensor data for robust decision-making. - Build and maintain sim-to-real pipelines, including domain randomization and transfer learning techniques. - Conduct experiments on physical robots, including designing safety protocols and monitoring for unexpected behaviors. - Leverage simulation environments (Isaac Gym, Gazebo, MuJoCo, PyBullet) for large-scale training before real-world validation. - Continuously improve model efficiency to operate within compute and latency constraints on embedded robotic systems. Qualifications - Master’s or PhD in Computer Science, Robotics, Machine Learning, or related field, or equivalent practical experience. - Experience developing and deploying reinforcement learning algorithms on real-world systems. - Proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow. - Experience with simulation environments (e.g., MuJoCo, Isaac Gym). - Solid understanding of probability, statistics, and optimization. - Experience with training and deploying ML models in production systems. Benefits - Daily free lunch to keep you fueled and connected with the team. - Flexible PTO so you can take the time you need, when you need it. - Comprehensive medical, dental, and vision coverage. - 6 weeks fully paid parental leave, plus an additional 6–8 weeks for birthing parents (12–14 weeks total). - 401(k) retirement plan through Empower. - Generous employee referral bonuses—help us grow our team! Company Description At Path Robotics we love coming to work to solve interesting and tough challenges but also because our ideas are welcomed and valued. We encourage unique thinking and are dedicated to creating a diverse and inclusive environment. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. If you require a reasonable accommodation to participate in the application process or any part of the hiring process, please contact HR@path-robotics.com. We are committed to providing equal access and will work with qualified individuals to ensure a fair and accessible hiring experience. We will respond to your request within 48 hours.
Related Guides
Related Job Pages
More Machine Learning Engineer Jobs
Role Description Own recommendation, search, ranking, retrieval, and discovery for Sekai’s content ecosystem. What you will own: - Build recommendation and search across feed, discovery, search, and content continuation. - Own retrieval/ranking: candidate generation, embeddings, two-tower models, features, and serving quality. - Design, launch, and analyze recommendation/search experiments. Qualifications - 5+ years industry experience building production ML systems with senior ownership. - Hands-on recommendation, search, ranking, ads ranking, feed ranking, or content discovery systems. - Experience with consumer apps, entertainment, social, gaming, creator, or engagement-driven products. - Knowledge of two-tower models, embedding retrieval, candidate generation, ranking, and online/offline evaluation. Requirements - 5+ years industry experience building production ML systems with senior ownership. - Hands-on recommendation, search, ranking, ads ranking, feed ranking, or content discovery systems. - Experience with consumer apps, entertainment, social, gaming, creator, or engagement-driven products. - Knowledge of two-tower models, embedding retrieval, candidate generation, ranking, and online/offline evaluation. Benefits - Bonus signal: 5+ years production ML - Bonus signal: recommendation systems - Bonus signal: search ranking - Bonus signal: embedding retrieval Anti-signals - Cannot show core Senior Machine Learning Engineer, Recommendation experience. - Not comfortable with the listed work mode. - Low ownership, coordination-only, or no shipped examples. This is a remote position.
Senior Machine Learning Engineer
Encora DigitalEncora, a leader in digital engineering, drives innovation by crafting cutting-edge, cloud-first, data-first, and AI-first solutions that redefine industries. S
Role Description We at Coforge are hiring a Senior Machine Learning Engineer (#22151) with the following skill set. - Deploy, productionize, and optimize machine learning models, collaborating with Data Scientists to build scalable batch and real-time inference solutions. - Design and develop secure, scalable REST APIs and AI-driven data services that expose machine learning models and curated datasets for low-latency consumption. - Build and optimize high-performance inference services, improving model response times, throughput, caching strategies, and resource utilization. - Develop and maintain reliable data pipelines within Azure and Databricks, ensuring scalable, production-ready data and AI workflows. Qualifications - 5+ years of experience in Machine Learning Engineering, MLOps, or AI Platform Engineering. - Strong experience deploying machine learning models into production environments. - Hands-on experience with Azure services and Databricks for building scalable data and AI solutions. - Strong Python programming skills for machine learning and data engineering. - Experience designing and developing REST APIs and microservices for AI applications. - Experience building batch and real-time inference pipelines. - Knowledge of scalable model serving, performance optimization, and low-latency architectures. - Experience developing and maintaining production data pipelines and workflow orchestration. - Familiarity with MLOps best practices, version control, monitoring, and CI/CD pipelines. - Bachelor's degree in Computer Science, Engineering, Data Science, or a related field (or equivalent professional experience). Requirements - Experience with Azure Machine Learning, MLflow, or similar model lifecycle management tools. - Familiarity with dbt, Spark, and distributed data processing. - Experience with containerization technologies such as Docker and Kubernetes. - Knowledge of API security, authentication, and cloud-native architectures. - Experience working in Agile environments with cross-functional Data Science and Engineering teams. Company Description At Coforge, we hire professionals based solely on their skills and qualifications and do not discriminate based on age, disability, religion, gender, sexual orientation, socioeconomic status, or nationality.
Role Description Own recommendation, search, ranking, retrieval, and discovery for a consumer content ecosystem. - Build recommendation and search across feed, discovery, search, and content continuation. - Own retrieval and ranking systems, including candidate generation, embeddings, two-tower models, feature engineering, and serving quality. - Design, launch, and analyze recommendation and search experiments. Qualifications - 5+ years of industry experience building production ML systems with senior-level ownership. - Hands-on experience with recommendation, search, ranking, ads ranking, feed ranking, or content discovery systems. - Experience working on consumer applications, entertainment, social media, gaming, creator platforms, or other engagement-driven products. - Strong knowledge of two-tower models, embedding retrieval, candidate generation, ranking systems, and online/offline evaluation. - Fluency in Chinese (Mandarin) is required. Requirements - 5+ years of industry experience building production ML systems with senior-level ownership. - Hands-on experience with recommendation, search, ranking, ads ranking, feed ranking, or content discovery systems. - Experience with consumer applications, entertainment, social, gaming, creator, or engagement-driven products. - Expertise in two-tower models, embedding retrieval, candidate generation, ranking, and online/offline evaluation. Bonus Signals - 5+ years of production ML experience. - Strong background in recommendation systems. - Experience with search ranking. - Experience with embedding retrieval. Anti-Signals - Cannot demonstrate core Senior Machine Learning Engineer experience focused on recommendation systems. - Not comfortable with the specified remote work arrangement. - Primarily coordination-focused with limited technical ownership or no shipped production examples. Interview Process - Initial recruiter screen. - Senior Machine Learning Engineer (Recommendation) technical/product deep dive. - Team/founder conversation. Culture - AI-native, fast-paced startup environment with strong ownership expectations. - Focus on building consumer AI products at the intersection of AI, social, mobile, and interactive entertainment. - Looking for engineers who ship quickly, learn from users, and take end-to-end ownership.
Role Description Design, develop, and train advanced machine learning models, including: - Deep neural networks - Transformer-based architectures - Reinforcement learning systems To power large-scale online advertising ranking and optimization platforms. Responsibilities include: - Lead the development and optimization of complex feature representations, including: - High-dimensional embeddings - Contextual and temporal signals - Cross-session user behavior modeling - Drive end-to-end model lifecycle execution, including: - System architecture design - Large-scale experimentation - Model deployment - Performance monitoring - Iterative infrastructure improvements in production environments - Collaborate closely with product, data, and infrastructure engineering teams to: - Translate business objectives into scalable, statistically rigorous modeling solutions - Conduct advanced experiment design and causal analysis to: - Evaluate model impact - Inform strategic decisions - Provide technical leadership and mentorship to machine learning engineers - Contribute to organization-wide modeling standards, best practices, and long-term technical strategy - Shape the long-term modeling vision across multiple advertising domains, including: - Conversion optimization - Application advertising - Shopping - Brand advertising Full-time telecommuting is an option. Qualifications - Master’s degree in Computer Science, Engineering (any field) or related quantitative discipline - 3 years of experience in the job offered or related occupation Requirements - Python, Java, and Scala - C++, Go, or Rust - Major machine learning frameworks and libraries - Applied statistics, hypothesis testing, and experiment design for online machine learning systems - Large-scale data processing and analytics frameworks - Deployment and operation of production systems in containerized and distributed environments - Designing and training advanced models, including deep neural networks, transformer-based architectures, and reinforcement learning models - Marketplace dynamics, such as real-time bidding (RTB) or pacing control systems - Developing and optimizing online advertising systems, including ad ranking, targeting, and marketplace - Providing technical leadership, mentorship, or guidance to other machine learning engineers - Any suitable combination of education, training, and/or experience is acceptable Benefits - Comprehensive Healthcare Benefits and Income Replacement Programs - 401k with Employer Match - Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support - Family Planning Support - Gender-Affirming Care - Mental Health & Coaching Benefits - Flexible Vacation & Paid Volunteer Time Off - Generous Paid Parental Leave
