Top Machine Learning Engineer Jobs

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

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.

The Machine Learning Engineer will develop ML infrastructure, optimize models for anomaly detection, and manage technical projects to enhance space cybersecurity.

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

As an Applied Machine Learning Engineer, develop, deploy, and optimize machine learning models while collaborating with cross-functional teams to enhance customer solutions.

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

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

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

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.

Design, build, and deploy production-grade AI/ML systems (including LLMs and agents) for Defense and Intelligence. Implement MLOps, cloud-based solutions (AWS/Azure), containerized deployments (Docker/Kubernetes), integrate agents with APIs/databases, evaluate LLM performance and observability, and design scalable service-based architectures.

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

The AI/ML Engineer develops algorithms for healthcare applications, collaborates on data handling, and ensures regulatory compliance in AI/ML implementations.

Design, implement, and deploy LLM-powered autonomous agent systems. Build prompt engineering frameworks, safety/oversight mechanisms, testing frameworks, and services using models like GPT-4 and Claude. Collaborate on agent reasoning, planning, and execution across cloud infrastructure.

Develop and optimize ML pipelines and Language Models, implement agentic AI systems, deploy ML components on GCP, and improve models based on feedback.

The position involves building AI systems using language models, managing ML pipelines, and requiring expertise in MLOps and cloud services.

Design, build, and deploy production-grade AI/ML models, agentic workflows, and data pipelines using Python, Databricks, LangChain/LangGraph, and Azure. Collaborate with cross-functional teams to translate requirements into scalable LLM applications, implement feature engineering and validation frameworks, and embed responsible AI practices including fairness, security, and monitoring.

Design, build, and productionize large-scale foundation models and ML systems (transformer architectures, self-supervised learning). Architect and implement training, data pipelines, deployment, monitoring, and CI/CD. Collaborate with cross-functional teams, ensure model governance, reliability, and performance, and apply ML engineering best practices at scale.

The Machine Learning Engineer will design, deploy, and operate ML systems on AWS while ensuring reliability, cost-effectiveness, and compliance for the gaming industry.

As a Senior ML Engineer at Torc, you will develop and maintain ML frameworks, enabling advanced solutions for autonomous vehicles and improving ML platforms.

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

The AI Machine Learning Engineer will design, develop, and deploy AI/ML solutions, ensuring compliance with federal standards and improving operational efficiency.

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

The role involves leading technical directions for recommendation systems and AI initiatives, driving adoption of AI technologies, and mentoring others in system-level thinking.

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