Top Machine Learning Engineer Jobs

Lead and manage an ML Models-as-a-Service team to define vision, build and deploy production ML models and APIs, establish MLOps and CI/CD pipelines, enforce governance and security, collaborate with stakeholders, and oversee project delivery and resource allocation across the model lifecycle.

Design and implement agentic AI integrations: build retrieval and ingestion pipelines, embeddings and vector-store indexing, develop APIs/microservices, optimize query routing and caching, implement auth/audit, and support prototypes, demos, and pilot deployments.

Design, develop, deploy, and maintain production ML models and MLOps pipelines. Build custom AI/ML algorithms, run experiments, evaluate and optimize model performance, and integrate models with cross-functional teams for mission-driven applications in a federal environment.

Design, develop, deploy, and maintain production ML models and pipelines. Build MLOps frameworks, run experiments, evaluate and fine-tune models, and integrate AI/ML solutions with cross-functional teams to deliver mission value for federal clients.

Build production systems that probe and modify LLM internals to improve reliability and enforce deterministic policy. Implement mechanistic-interpretability techniques (activation patching, control vectors), work with weights/activations, build evaluation and deployment loops, and design feature-level intervention systems for enterprise inference.

Design, build, and productionize personalized recommendation models and LLM-based experiences for Spotify's Home feed. Own model training, fine-tuning, evaluation, A/B testing, inference optimization, and ML platform/data pipeline improvements. Drive technical direction, mentor engineers, and collaborate with cross-functional partners to deliver scalable, cost-efficient personalization at global scale.

Build and scale backend services, platform infrastructure (serverless), and APIs powering financial workflows for clinical development. Integrate with LLM agents and AI workflows, implement frontend components as needed, resolve production incidents, contribute to architecture, and mentor teammates.

The Staff Engineer will design and manage ML infrastructure while mentoring teams, driving MLOps strategies, and ensuring compliance in healthcare data systems.

Join Sajix as a Machine Learning Engineer Trainee to assist in building and deploying ML models for healthcare solutions, collaborating with data scientists, and gaining hands-on experience.

As an AI Engineer at Extend, you'll build advanced document processing infrastructures and AI product features, impacting customer operations significantly.

Design, build, and operate scalable enterprise AI/ML systems including LLM infrastructure, RAG pipelines, and autonomous agent frameworks. Provide architecture and code-level leadership, establish ML engineering best practices, implement safety guardrails and traceability, develop evaluation frameworks, and standardize CI/CD and lifecycle processes while ensuring compliance with data governance and responsible AI standards.

Design and deploy machine learning systems for autonomous vehicles, collaborating with teams to improve model performance and safety using real-world data.

Lead and grow a team of 4-5 ML engineers to design, build, and operate enterprise-grade, distributed AI/ML systems (LLM serving, retrieval, agentic frameworks). Provide architectural direction, establish ML lifecycle CI/CD and evaluation frameworks, implement safety/traceability guardrails, and ensure responsible AI and data governance compliance.

Design and develop machine learning systems for construction robots, including scalable infrastructure, computer vision models, and data analysis for performance improvement.

The Machine Learning Engineer will develop editable visuals combining computer vision and machine learning, enabling chat-driven figure editing and leveraging biological understanding to produce accurate visuals.

Lead post-training for LLMs (CPT, SFT, RL) focusing on RL methods; design and curate training and reward data; run and debug distributed training on mid-to-large GPU clusters; build evaluation and verifier pipelines; partner with product and business teams to deliver targeted model improvements quickly.

Lead a small team to research, develop, train, optimize, and deploy computer vision and multimodal fusion AI/ML models for remote sensing (EO/SAR). Analyze large datasets, translate research into operational systems, present technical findings to customers, and produce supporting documentation and user guides.

The role involves developing AI/ML algorithms in various disciplines, analyzing datasets, and mentoring team members within a research environment.

We seek a Machine Learning Engineer to enhance our ML platform, focusing on modeling techniques, research workflows, and production infrastructure.

Design and develop machine learning infrastructure, enhancing core components for model training, monitoring, and serving. Collaborate with ML engineers on robust pipelines.

The role involves designing robot learning algorithms, leveraging data for generalizable behaviors, and collaborating on consumer robot development. Responsibilities include end-to-end task management from definition to deployment.

The Senior Machine Learning Engineer will develop core ML models, manage data pipelines, and collaborate with stakeholders to deliver scalable ML solutions.

Lead the development of AI systems for an automation platform, focusing on design, implementation, and evaluation of AI/ML projects in financial services.

Lead initiatives to enhance the ML platform, mentor junior engineers, build scalable ML models, and ensure code quality while driving innovation in a startup environment.

The Senior Machine Learning Engineer will lead the development of a GenAI platform, enhance AI infrastructure, mentor junior engineers, and drive project ownership in a startup environment.