Top Machine Learning Engineer Jobs

Architect and productionize ML and GenAI solutions on the Databricks platform, advise customers on end-to-end ML pipelines, optimize training and inference, apply MLOps best practices, collaborate with product and engineering, and mentor peers while supporting technical pre/post-sales activities and customer adoption.

As a Machine Learning Engineer, you will address AI and robotics challenges, focusing on areas like computer vision, sensor fusion, and predictive modeling.

Lead the design and development of advanced recommendation systems and machine learning pipelines, optimizing performance for millions of users.

Lead the design and implementation of advanced machine learning models to solve complex problems, working closely with teams to enhance services through AI/ML solutions.

As a Staff Machine Learning Engineer, you'll build production-scale ML models for personalization and risk management, mentor junior scientists, and collaborate with cross-functional teams to drive impactful product features.

Design and build core backend services for a cloud-agnostic ML compute platform. Integrate with GPU hardware and orchestration, improve performance, scalability, reliability, and drive large cross-team initiatives to support ML training and deployment.

As a Senior Staff Data Scientist/Machine Learning Engineer, you will develop machine learning models to enhance Autodesk's eCommerce platforms, drive data-informed decisions, and mentor junior team members.

Lead the design, development, and implementation of machine learning models to solve complex problems, collaborating with cross-functional teams to enhance services and deploy solutions in production environments.

Lead the design and delivery of large-scale machine learning systems, mentoring engineers while driving technical strategy and collaboration across teams in AEC solutions.

Design, build, and deploy production-grade AI systems for supply chain applications. Prototype and productionize LLM and Foundation Model solutions, integrate AI with enterprise systems (ERP, cloud, Kubernetes/Terraform), lead technical decisions, mentor teams, and ensure responsible, safe AI deployment and operations.

As a Principal Machine Learning Engineer, you will develop distributed inference infrastructure, integrate with vLLM, and optimize inference workloads, mentoring fellow engineers along the way.

The Principal Machine Learning Engineer will develop optimization algorithms, enhance LLM deployments, and collaborate with research teams on model performance and compression.

Work on Wayfinding projects using LLMs and agentic workflows, collaborate with engineering/product/research teams, receive mentorship, and gain hands-on experience with model evaluation, prompt engineering, and shipping code in a real engineering environment.

Lead design and implementation of production GenAI/ML services and agentic systems for post-trade workflows. Build RAG/vector retrieval, integrate ML components, enforce governance/auditability, establish evaluation and monitoring, optimize performance/cost, and mentor engineering teams while collaborating with product and operations.

Develop and deploy LLM-powered systems for document processing, RAG pipelines, vector search, and production ML infrastructure. Own end-to-end model lifecycle, production integration, monitoring, and cross-functional collaboration to automate permitting workflows.

Lead design, training, and deployment of custom ML models for radar and EO/IR perception: segmentation, detection, and tracking. Build multi-stage pipelines, fuse sensor data (Radar, EO/IR, AIS, cartography), optimize models for CPU/ARM64 edge deployment, integrate outputs into tracking/SLAM, and contribute to ML-Ops for large-scale training and continuous evaluation.

As a Machine Learning Engineer at Shipwell, you'll build and scale AI-powered logistics solutions, maintaining data pipelines and ML infrastructure across the organization.

Join a team focusing on end-to-end ML Ops for the insurance sector. Develop and deploy ML solutions, build infrastructure, and solve business challenges using advanced technologies.

The Forward Deployed ML Engineer will integrate AI/ML models into clinical software, assist in model fine-tuning, and engage with clients to ensure success in healthcare deployments.

The role involves building AI technologies for customer service, developing ML systems, and collaborating with cross-functional teams to enhance user experiences.

The Senior Machine Learning Engineer will implement and enhance ML solutions, working closely with various business departments to deliver scalable applications and improve MLOps practices.

Design, develop, and deploy AI-driven solutions, optimize algorithms, and collaborate with teams and customers to implement scalable AI models and functionalities.

The Staff Machine Learning Engineer will design ML systems, mentor engineers, work on AI product development, and improve legal data processing.

The Staff Machine Learning Engineer will develop advanced Document AI models, solve complex modeling challenges, lead LLM fine-tuning, and provide leadership in a collaborative environment.

The Software Engineer, II will optimize ML models on GPU platforms, contribute to resource management, and collaborate with feature teams for vehicle integration.