Top Machine Learning Engineer Jobs

Train, fine-tune, and deploy vision-language-action and robot manipulation models across the full pipeline. Handle data curation, pre-training and fine-tuning, sim-to-real distillation, debugging, evaluation, and iterative autonomous improvement on physical robots.

Design, build, and productionize ML models and infrastructure at scale. Collaborate with product and data science teams, develop and validate models, construct data pipelines, deploy and monitor models, apply CI/CD, and ensure Responsible/Explainable AI and high availability for ML systems.

Design, develop, and implement AI/ML models; analyze large datasets; integrate AI solutions into existing systems; apply MavLink for autonomous systems; collaborate across teams and improve ML development processes.

Design and implement agent harnesses and post-training pipelines, build evaluation benchmarks, develop RL environments and reward models, and debug/optimize multi-GPU training runs to improve LLM capabilities for agentic applications.

The Staff Machine Learning Engineer will enhance Quora's recommendation systems, lead machine learning projects, and own end-to-end ML processes.

The Principal Machine Learning Engineer will lead hands-on model development, oversee predictive modeling, and drive AI initiatives, ensuring models are effective and operationally sound.

The Machine Learning Engineer designs, builds, deploys, and maintains machine learning models, optimizing their performance for business value. Responsibilities include managing ML pipelines and collaborating with data teams to implement MLOps best practices.

The Senior Machine Learning Engineer will develop and optimize AI image generation models, monitor production issues, and collaborate on ML solutions for generative features.

As a founding Data Scientist/Machine Learning Engineer, you'll develop AI/ML models, enhance product capability, and drive impactful user outcomes while working closely with product teams.

The role involves designing and scaling ML infrastructure for LLMs, including building training pipelines and deploying models in cloud and on-prem environments. Collaboration with engineers and managing GPU/TPU workloads is key.

Design and implement ML solutions for optimizing GPU accelerated Apache Spark workloads. Collaborate on deployment and lead technical teams in ML.

The Machine Learning Engineer will apply machine learning techniques to enhance the performance of MIMO radios and wireless systems, collaborating with experts to develop solutions for challenging RF environments.

As a Founding Machine Learning Engineer at Trove, you will develop AI applications for financial firms, focusing on data retrieval and knowledge graphs. Your role involves designing algorithms and collaborating with elite AI labs to enhance human-level capabilities in GenAI.

The Machine Learning Engineer II will design, develop, and maintain machine learning models, lead ML initiatives, collaborate across teams, and mentor junior members while working on Insider Risk Management solutions.

As a Machine Learning Engineer, you'll design and deploy large-scale models for advertising and commerce systems, optimizing for performance and relevance while maintaining ML pipelines.

The Machine Learning Engineer will develop and deploy AI systems for robotics, focusing on advanced manipulation techniques and control algorithms, collaborating across teams.

The Staff ML Engineer will lead architecture decisions for ML infrastructure, operate real-time computer vision systems, and mentor engineers, ensuring high-quality ML deployment and operational excellence at SimpliSafe.

Design and optimize GenAI solutions, collaborate with teams, enhance system performance, present technical findings, and stay updated on GenAI advancements.

Develop, train, and deploy AI surrogate models to enhance engineering simulations for aerospace applications while collaborating with engineers to tackle complex challenges.

Develop ultra-realistic simulations for autonomous vehicles using machine learning, focusing on realism and integration into production systems.

The AI/ML Engineer develops AI features for Cengage's educational products, focusing on enhancing student engagement and learning outcomes through shipping production AI capabilities.

The Machine Learning Engineer will collaborate on AI projects, develop algorithms, optimize solutions, and maintain coding standards within Kitware, contributing to various machine learning tasks.

Collaborate on machine learning projects, perform prototyping, validate algorithms, and troubleshoot code for robustness in AI and computer vision.

Design and deploy next-generation recommendation and ranking models using LLMs, RLHF, and preference learning. Build user-understanding systems, apply RL and optimization to bidding and ad delivery, run causal A/B experiments, and collaborate with engineering to productionize research across the ML pipeline.

Design and evaluate next-generation recommendation and ranking models using LLMs, RLHF, and preference learning. Build user understanding systems for conversion and value estimation at scale. Apply RL and optimization to bidding and real-time delivery. Run causal inference, A/B tests, and offline evaluations. Collaborate with engineering to productionize research and communicate results to technical and non-technical stakeholders.