Top Hybrid Machine Learning Engineer Jobs

Design, develop, and deploy end-to-end data science pipelines and predictive models. Collaborate with product, engineering, and business teams to run experiments, implement MLops best practices (CI/CD, versioning, monitoring), and deliver scalable solutions (including LLM/RAG workflows) that improve restaurant operations and business outcomes.

Develop, implement, and validate production-level control and learning algorithms (MPC, RL, IL) for real-world embodied robotic systems. Design experiments to improve robustness and adaptability, integrate AI control stacks with perception and systems engineering, and use simulation and digital twins to accelerate deployment.

Join Capsule as an AI Engineer to develop ML models for video editing. Responsibilities include researching ML techniques, collaborating on feature development, and optimizing model performance.

Lead machine learning initiatives, oversee product development, improve execution pace, enhance team reliability, and foster team growth at Hightouch.

Build and deploy production LLM/ML pipelines for patent workflows: retrieval, multi-step prompt pipelines, evals frameworks, fine-tuning, agentic workflows, monitoring, and cloud deployment. Collaborate with attorneys and cross-functional teams to convert domain expertise into robust, scalable inference and data solutions.

As a Software Engineer (AI), you will design and implement AI systems, manage backend services, and collaborate closely with teams. You need extensive experience with LLMs and backend technologies.

Design and oversee the development of robust data platforms for training and evaluating ML models, focusing on autonomous driving. Collaborate with multiple teams and optimize data processing pipelines.

Lead AI feature design and delivery, build large-scale ML systems, mentor engineers, and define best practices across the engineering organization.

Design, implement, and maintain Python microservices for a real-time voice pipeline (capture, streaming transcription, LLM orchestration, TTS). Integrate providers and transports (WebRTC, SIP, phone), deliver ultra-low latency (<500ms), instrument tracing/metrics (OpenTelemetry), ensure production hardening and HIPAA-compliant security, and collaborate with ML, product, and client SDK teams.

Lead the Identity squad to design, implement, and scale identity resolution (clustering/entity resolution) pipelines and algorithms at US scale. Own architecture, cost/performance optimization across Dagster, Spark, and Iceberg, build observability and evaluation frameworks, extend identity into audience construction, and lead cross-functional roadmap and mentoring for the squad.