Top Machine Learning Engineer Jobs

Join Spotify's Personalization team to enhance music recommendations using cutting-edge ML and AI technologies, collaborating across teams and prototyping new features.

The Data/ML Infrastructure Engineer builds and operates data infrastructures for processing drone and orbital sensing data, ensuring reliability, observability, and performance while collaborating with research and product teams.

Lead the development and deployment of machine learning systems for mineral refining operations, collaborating with chemistry and engineering teams to optimize performance and inform operational decisions.

The Senior Machine Learning Engineer will lead the perception stack, focusing on detection, tracking, classification, and sensor fusion for targeting systems, with responsibilities including model development and real-time optimization on embedded devices.

The role involves designing and deploying machine learning systems for content safety at Spotify, collaborating with various stakeholders, and providing technical leadership.

The Senior Machine Learning R&D Engineer will innovate in spatial computing, develop ML algorithms, process 3D data, and collaborate with teams to enhance Matterport's platform.

As a Software Engineer in ML Infrastructure, you will build automated resource provisioning, optimize workload scheduling, manage large-scale data processing, and enhance feature management for model development.

Design and develop data pipelines for autonomous driving systems, create storage for data metrics, build dashboards, and maintain data integrity, focusing on ML components.

Responsible for designing and developing scalable data pipelines, storage systems, and monitoring tools for ML data infrastructure, ensuring system integrity and performance evaluation.

The role involves building and optimizing ML infrastructure, focusing on automated resource provisioning, workload scheduling, data processing, and feature management to enhance the Nuro Driver development lifecycle.

As a Senior Machine Learning Engineer for the Localization team, you'll improve ML systems for pose estimation, integrate computer vision models, and maintain coding best practices. You'll also collaborate closely on model validation and contribute technically to team architecture.

The role entails optimizing model performance and developer experience through serverless inference platforms, distributed systems, and API development. Responsibilities include enhancing system robustness and scalability, partnering with product teams, and maintaining clean software and IaC.

Translate RL and inference research into production systems to improve latency, throughput, cost, and model quality. Design and implement inference engines and scheduling, build RL/post‑training pipelines, profile and optimize GPU/network/memory performance, run scale experiments, and drive production roadmap and benchmarks. Provide technical leadership and mentor others.

As an ML Eval Engineer, you'll build evaluation systems for model quality, develop metrics to identify failures, and collaborate with teams to improve models using real-world datasets.

Develop and maintain ML pipelines for entity classification; collaborate with data scientists; implement monitoring frameworks and improve data workflows.

Join Equilibrium Energy as a Staff/Sr Staff Software Engineer to enhance the Science Platform for ML model deployment, requiring strong Python and ML expertise.

The Senior Data Engineer defines technical approaches for client projects, evaluates modeling strategies, and conducts internal R&D in applied machine learning and analytics, with a strong emphasis on Python-based solutions and mentorship of junior engineers.

As a Senior ML Engineer for Payments, you will develop AI solutions for payment experiences, optimize transaction processing, and ensure system reliability while mentoring teammates and collaborating with cross-functional teams.

As a Senior Software Engineer at NVIDIA, you will design and implement inference software optimizations for AI applications using TensorRT, collaborating with deep learning experts to influence hardware and software design.

Design and develop scalable ML infrastructure to support training and inference, optimizing distributed systems, and maintaining operational excellence. Collaborate with various teams to enhance AI capabilities and ensure reliability and performance.

Develop algorithms and optimizations for NVIDIA's LPX inference and compiler stack focusing on performance, efficiency, and integration with hardware systems.

The role involves transforming research into products, building diverse datasets, accelerating ML workflows, and collaborating effectively across teams.

The role involves developing and deploying machine learning solutions, optimizing models, and collaborating with cross-functional teams. Responsibilities include cloud architecture, algorithm engineering, and infrastructure best practices.

The role focuses on leading AI/ML architecture and deployment for scalable solutions in cloud security, shaping technical strategies, and managing the lifecycle of AI models.

The role involves building data infrastructure for ML models, managing petabytes of camera data, and collaborating with cross-functional teams to enhance model quality.