Top Machine Learning Engineer Jobs

The Machine Learning Engineer will design, build, and maintain scalable ML systems, optimize ML pipelines, implement MLOps, and collaborate with teams to deploy models into real-time products.

The Staff Machine Learning Engineer will design, train, and deploy NLP models, optimize processes, and mentor engineers. The role demands expertise in model training and productionization.

Design and implement LLM‑powered and agentic workflows for intelligence missions. Capture user workflows, integrate AI with APIs and enterprise data, ensure production reliability and security in classified environments, and collaborate with operators and mission leadership to deliver AI-enabled decision support.

Design, train, and deploy high-throughput ML/NLP models and pipelines at consumer scale. Build resilient production model services, migrate ML infrastructure to public cloud (GCP), process massive distributed datasets, integrate AI-driven workflows, and collaborate cross-functionally to embed personalization into Yahoo Mail while maintaining code quality and performance.

Design, build, and maintain scalable self-service data and ML platform tools and workflows. Mentor junior engineers, collaborate with cross-functional teams, implement monitoring/alerts, drive infrastructure improvements, integrate new technologies, and produce technical documentation to support reliable, scalable data products and pipelines.

Design, develop, and maintain core ML inference platform components including model deployment, optimization pipelines, and benchmarking/simulation workflows. Collaborate with systems and cloud engineers, and build APIs/tools to ensure scalable, reliable, and hardware-efficient inference solutions.

Develop and implement machine learning algorithms for defect detection in high-resolution images. Optimize real-time performance and evaluate model efficiency.

The Principal ML Engineer will design and scale ML infrastructure for scientific discovery, collaborating with AI scientists to enhance model training and deployment processes.

The role involves training and developing large-scale image and video models, optimizing data pipelines, and conducting experiments in a high-performance computing environment.

The ML Engineer will architect and build personalization and recommendation systems, design user preference algorithms, collaborate with teams, and improve systems from research to production.

The Junior-Midlevel Developer will build and enhance Dumroo.ai's AI-powered education platform, collaborating on software components, data pipelines, and machine learning features.

As a Senior Applied ML Engineer at Macroscope, you will design, build, and optimize ML/AI systems, leading the AI Code Review process and ensuring integration with backend systems.

The Senior Staff Machine Learning Engineer will lead the development of GEICO's AI-driven virtual agent platform, overseeing technical design, cross-functional collaboration, strategic planning, and mentoring within the team throughout project lifecycles.

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

The Machine Learning Engineer will apply data science and machine learning practices to solve problems, develop prototypes, and communicate insights to stakeholders in a dynamic environment.

As a Data Scientist/Machine Learning Engineer, you'll finetune models, improve data quality, add new signals, and push solutions to production.

Lead the development of device intelligence and fingerprinting systems by designing backend services, collaborating on integrations, and applying advanced machine learning algorithms to enhance security and combat fraud.

As Lead ML Engineer, you will architect and build a conversational AI interface, optimize models for deployment, and collaborate with a multidisciplinary team.

As an intern, you'll develop software and machine learning systems for robots, focusing on perception, intelligence, behavior, and real-time software integration.

The ML Engineer will develop and advance multimodal models for robot perception and behavior, integrating these systems into hardware while collaborating closely with robotics engineers.

Develop and deploy machine learning algorithms for planning in autonomous trucks, ensuring safety and real-time efficiency.

The role involves designing and scaling ML systems for prediction and recommendation, mentoring junior engineers, and leading projects.

Develop and implement automation for ML/LLM integrations and data pipelines to support incident response and automated malware analysis. Build ingestion, transformation, monitoring, API integrations, and scale automation from pilot to production while ensuring data quality and documenting solutions.

Design, build, and operate production ML systems and LLM-based agents for fraud and risk detection at a global crypto exchange. Responsibilities span feature engineering, model training and serving, monitoring, explainability, integration with operations, and building safe, auditable LLM agents for investigation and automation.

Lead the development of machine learning algorithms focusing on perception for autonomous driving, collaborating across teams and mentoring ML developers.