Top Machine Learning Engineer Jobs

Develop and deploy deep learning models for medical imaging: prototype and production work, design and run experiments, document results, collaborate on data labeling, and optimize models for inference and deployment.

Develop and productionize deep learning models for computer vision and NLP on medical imaging products. Design and run experiments, document results, collaborate on data labeling, write deployment/docker code, optimize inference speed, and conduct DL methodology research.

Lead design, training, and deployment of large-scale ML models (LLMs, diffusion, GNNs). Own end-to-end training pipelines, distributed training, evaluation, and inference architecture. Collaborate with data and infra teams, drive reproducible model development, and provide technical leadership and mentorship from research through production.

As an AI/ML Engineer, you'll design, build, and ship large scale NLP and LLM systems for classification, ranking, and content generation while collaborating with cross-functional teams.

As a Machine Learning Engineer/Scientist, you will develop ML systems for cryopreservation research, manage data pipelines, and deploy models for scientific insight.

Design and build AI assistants for interactive 3D workflows: build NLP pipelines, integrate cloud and client LLMs, design knowledge graphs, fine-tune foundation models, prototype AI features, and improve personalization and system performance.

The Staff ML Engineer will define and build ML capabilities, focusing on production systems, strategy, and infrastructure in a cybersecurity context.

The Lead AI/ML Engineer evaluates emerging technologies, leads teams in adopting solutions, and provides technical leadership while mentoring junior specialists.

The Machine Learning Engineer will build a robot-learning stack, design training infrastructure, deploy ML policies, and collaborate with engineers in heavy manufacturing.

As a Machine Learning Engineer, you will design, build, and maintain ML systems, fine-tune LLMs, and translate ML research into scalable solutions.

As a Staff Machine Learning Engineer, you will design, build, and deploy ML systems, optimize performance, and collaborate with teams to integrate AI solutions.

Lead and architect scalable agentic AI runtime services integrating LLM-based reasoning. Manage and mentor a distributed team, drive technical roadmap, deploy models in microservice environments, and collaborate cross-functionally to deliver production conversational AI solutions.

The Machine Learning Engineer will train, fine-tune, and deploy ML models for parsing unstructured data, and build data pipelines for product integration.

The Staff AI/ML Engineer will develop and prototype AI/ML algorithms, analyze datasets, and mentor team members in an interdisciplinary environment.

The AI/ML Engineer designs and operates a production-grade orchestration platform, focusing on multi-agent workflows, LLM integration, and backend systems. Responsibilities include managing cloud-native infrastructure, ensuring system reliability and observability.

Design and deploy object detection and tracking modules; develop ML algorithms; guide team members; improve data governance and quality assessment.

Design and productionize ML models and infrastructure to assess autonomous vehicle behavior in simulation and field. Operate large-scale ML and data systems, build simulation workflows, combine human judgments with ML for training and evaluation, and collaborate across teams to deploy state-of-the-art models and improve model quality.

Designs, trains, evaluates, deploys, and monitors scalable AI/ML models and data pipelines to meet federal customer requirements. Leads model architecture, testing, integration, and iterative improvement while ensuring data and model quality and presenting results to stakeholders.

Design and prototype state-of-the-art visual encoders and multimodal representations; train billion-scale models on GPU clusters; build visual reasoning and retrieval tools; collaborate on text-to-image and VLM projects; mentor junior researchers; publish research and ship models to production.

Lead and architect the technical strategy and roadmap for Content Quality at Pinterest, focusing on building signals for content quality and collaboration with ML engineers on deployment.

As a Senior Staff Machine Learning Engineer, you will drive AI product development, collaborate with cross-functional teams, and enhance ML models at scale.

Lead and drive strategy for generative AI projects, develop cutting-edge models, engineer data pipelines, and collaborate across teams to implement AI solutions.

Lead the Generative AI team at Xometry, setting vision and strategy, developing multimodal models, and collaborating with various stakeholders to deliver AI solutions.

Lead the Generative AI team by setting technical direction, developing large-scale models, and mentoring team members while collaborating across departments.

Lead the Generative AI team by setting technical direction, developing models, creating data pipelines, and driving AI strategy across Xometry's marketplace.