Top Machine Learning Engineer Jobs

Responsible for the full lifecycle of AI/machine learning on resource-constrained hardware, including data ingestion, model development, and deployment on embedded devices, while working closely with cross-functional teams.

Lead the technical architecture for Spotify's Agent Engine, integrating AI systems and improving agent-based experiences while guiding platform consolidation efforts.

The Machine Learning Engineer will develop software solutions, optimize data pipelines, and deploy machine learning models using cloud platforms and best practices.

The Machine Learning Engineer will develop and optimize models, manage datasets, enhance training pipelines, and collaborate across teams to innovate in autonomous vehicle technology.

You will build and own end-to-end ML systems, focusing on training, evaluation, deployment, and integration with applications, while ensuring quality and efficiency.

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.

Lead the advancement of embedding-based retrieval systems, focusing on multimodal models, model performance, and extensibility for various use cases.

Design and improve end-to-end ML/AI pipelines, process datasets, and contribute production code for high-quality solutions in machine learning projects.

Seeking an AI/ML Engineer to build, train, and evaluate advanced language models, collaborating on technical solutions for government contracts.

The Senior Data Scientist will support U.S. government contracts by developing machine learning algorithms, conducting advanced data analysis, and leading a team of data scientists. Strong collaboration with software engineers and subject matter experts is essential to develop production analytics for mission-critical applications.

The AI/Machine Learning Engineer will develop systems for automating health benefits decisions, integrating large language models with rule-driven patterns, and ensuring compliance with regulations.

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.

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.

Design, develop, and deploy scalable ML software systems for healthcare. Collaborate with teams to improve products and ensure performance and reliability.

The ML Engineer will develop and enhance machine learning models for credit decisioning, drive technical innovation, and collaborate across teams to deliver impactful solutions for small businesses.

As a Staff Machine Learning Engineer, you will develop models and agents for AI integration into products, focusing on performance monitoring and issue resolution.

Develop deep learned models and collaborate on generating driving plans for autonomous vehicles, employing imitation and reinforcement learning techniques.

Lead collaboration to improve ML workloads on cloud and self-driving cars, optimize models, and mentor junior engineers.

The Machine Learning Engineer will develop and maintain ML deployment pipelines, operationalize AI models, and ensure system reliability and scalability.

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.

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.

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

Manage and optimize computational infrastructure for training ML models, ensuring scalability for large datasets and performance optimization.

You will build a search and assistant product, improve personalization, train models, and write robust code while mentoring junior engineers.

The role involves solving customer problems by building ML solutions, engaging with various stakeholders, and taking ownership of the outcome through deployment.