Top Hybrid Machine Learning Engineer Jobs

Lead and run robotics data programs: translate ML priorities into collection/annotation/validation plans, own roadmaps and delivery, improve processes, and build tools to ensure high-quality datasets for model training and evaluation.

Lead the recommendations product across candidate generation, ranking, and presentation for Scribd. Define multi-year strategy and metrics, translate retrieval and ranking research into production, run experiments to improve engagement and conversion, partner with ML, engineering, design, and analytics, and communicate roadmap and impact to stakeholders.

Lead PayJoy’s ML platform organization and manage Staff and Senior ML and software engineers. Define the long-term roadmap for ML infrastructure, feature stores, model serving, ETL, internal APIs, deployment, monitoring, and MLOps. Partner with Risk, Fraud, Engineering, Product, and Data Science stakeholders to translate business goals into scalable technical solutions. Mentor engineering leaders, ensure production reliability and compliance, identify operational bottlenecks, and guide adoption of technologies such as LLMs and graph databases.

Develop autonomy software for mining vehicles, including perception, SLAM, motion planning, control, sensor fusion, localization, and mapping. Integrate LiDAR, cameras, radar, IMU, and GNSS while building embedded real-time systems. Create simulation, logging, and data pipelines, and validate autonomy software through bench, rig, and field testing. Collaborate with hardware, controls, and systems engineers to deliver safe, reliable vehicle autonomy.

The Senior Staff Engineer will lead ML initiatives, architect ML systems, build models, integrate AI solutions, and mentor data scientists.

As a Machine Learning Engineer at Doppel, you will design, train, and deploy ML models for detecting malicious content, ensuring scalability and real-time performance while collaborating with teams and stakeholders.

Lead design and delivery of production-ready AI systems within the ION Factory OS, ship AI-driven and core product features, architect scalable cloud-native systems and ML pipelines, implement RAG and MCP integrations, collaborate with product and data teams, ensure reliability and scalability, and mentor junior engineers.

As a Principal AI Engineer, you'll design scalable AI systems, mentor teams, develop large-scale LLMs, and optimize AI-driven cybersecurity solutions.

As an ML Research Engineer, you'll design experiments, implement model architectures, and engineer scalable libraries to advance molecular simulations to support drug discovery.

Implement and productionize ML research into performant C++ and Python systems, build ML infrastructure and training pipelines, design LLM/agent applications, and deploy AI workloads across edge, near-edge, and cloud environments while collaborating with data science and engineering teams.