Top Machine Learning Engineer Jobs

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.

Responsible for supporting AI/ML initiatives through CI/CD pipeline design, infrastructure management, and collaboration with engineers and data scientists, ensuring optimized and secure deployments.

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.

The Senior Machine Learning Engineer will build and operate ML systems end-to-end, focusing on production-grade ML platforms, feature pipelines, and MLOps practices while collaborating with cross-functional teams.

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.

The Senior AI Engineer will develop AI solutions for incident management, collaborate cross-functionally, and enhance observability tools through iteration and ownership.

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.

Develop machine learning models for brain-computer interfaces, focusing on decoding neural data and signal processing for improved user interaction.

The Senior Databricks AI/ML Engineer will design and deploy AI/ML solutions in the insurance sector, focusing on Databricks architecture, data pipelines, and MLOps workflows, while collaborating with various teams to operationalize models and optimize processes.

The AI/ML Engineer will design and implement AI/ML models to enhance analytics for government decision-making, ensuring accuracy, security, and alignment with objectives while mentoring staff.

Develop systems and APIs for LLM inference and fine-tuning. Design production systems, collaborate with teams, and improve system efficiency.

As a Machine Learning Engineer, you will fine-tune transformer models, deploy machine learning solutions, and work with cross-functional teams on innovative projects.

The Applied Machine Learning Engineer will build end-to-end ML pipelines, extract insights from data, and optimize systems, primarily using Python and SQL.

Design, deploy, and maintain production-grade agentic and ML systems. Build evaluation, monitoring, and experimentation tooling; automate ML lifecycle and retraining; QA agent behaviors; collaborate cross-functionally and communicate findings to stakeholders.

Design and develop data solutions, optimize ETL/ELT pipelines, integrate ML models, collaborate with engineers, and operationalize analytics for semiconductor R&D and operations.

Citizen Health seeks AI/Machine Learning Engineers to develop AI solutions for healthcare using advanced ML techniques, focusing on rare diseases and patient care. Responsibilities include designing ML models, optimizing LLMs, and ensuring compliance.

As a Machine Learning Engineer at Doppel, you will design, train, and deploy ML models for detecting malicious content, ensuring scalability and real-time performance while collaborating with teams and stakeholders.

The Machine Learning Engineer will develop AI capabilities, improve data processing methods, and focus on machine learning algorithms for data analysis and target detection.