Top Remote Machine Learning Jobs in St. Louis, MO

The Product Operations Associate will support the development of AI-driven products by ensuring accuracy, documentation, and effective workflows, while collaborating with various teams.

Lead the development of AI-powered tools and products, manage product roadmaps, collaborate cross-functionally, and drive innovation in media and advertising.

The Technical Product Manager will define roadmaps for an AI Platform, manage ML systems, partner with engineers, and improve healthcare outcomes.

The role involves designing and supporting GPU/Kubernetes clusters for AI/ML workloads, developing automation tools, and troubleshooting infrastructure issues.

As an AI/Machine Learning Intern, you will contribute to software applications and AI projects, working with data engineers and researchers to implement innovative solutions.

The intern will work on AI projects, gaining hands-on experience in software development, algorithm evaluation, and collaboration with engineers to enhance AI capabilities.

As a Machine Learning Engineer, you will design and build AI capabilities, develop scalable ML infrastructure, and collaborate on production systems in the real estate domain.

As a Senior Technical Recruiter for AI/ML, you'll manage full-cycle recruiting for senior AI roles, build talent pipelines, and partner with leadership to close top talent effectively.

As a Machine Learning Engineer, you will own the full lifecycle of ML from model development to production deployment, collaborating with teams to drive ML processes.

The role involves developing scalable ML solutions, leading cross-functional discussions, analyzing knowledge data, and producing technical documentation to improve search relevance using AI and machine learning technologies.

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 Senior Machine Learning Engineer will design and implement detection systems to improve email security, lead project execution, and mentor junior engineers.

As a Staff Machine Learning Engineer - AI Tech Lead, you will lead the design of AI systems for security operations, focusing on scalable architectures, AI safety, and mentoring. Responsibilities include overseeing technical evaluations, production workflows, LLM fine-tuning, and collaboration with teams to enhance AI capabilities.

The Lead Machine Learning Scientist designs and develops ML solutions, leads project teams, mentors members, and collaborates with clients to solve complex problems.

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.

This role involves defining and managing the AI platform's roadmap, collaborating with cross-functional teams to integrate AI capabilities, and ensuring product quality and reliability metrics.

The Senior AI/ML Engineer will design, build, and deploy Generative AI and ML platforms, ensuring compliance and high performance. Responsibilities include developing foundational services, overseeing model training infrastructure, and mentoring junior engineers.

Design and deliver scalable AI solutions powered by Large Language Models. Collaborate with teams to create cloud-native architectures, enable knowledge discovery, and mentor engineers in AI initiatives.

Lead the architecture, development, and management of machine learning systems for personalized decision-making, ensuring reliability and explainability in real-time contexts.

As a Sr. AI/ML Engineer III, you will design and implement reinforcement learning algorithms, integrate them into simulation environments, and evaluate their performance. Collaborating with engineering teams, you will ensure the maintainability and transparency of AI components while communicating results and recommendations clearly.

Lead technical direction and execution of Lime's CX automation platform, building scalable backend services, decision engines, and human-in-the-loop workflows to automate rider issue resolution while enforcing fraud and trust guardrails and improving operational metrics.

Design, build, and maintain scalable AI/ML architectures; collaborate with data scientists, engineers, product, and compliance to integrate models; evaluate tools and processes; monitor performance and ensure industry-standard compliance and ethical practices.

Design, build, and operate production-grade ML systems for personalization, search, and recommendations. Own end-to-end pipelines from data ingestion and modeling to deployment, monitoring, and iteration, ensuring scalable, reliable, and observable services.

Build and own ML platform infrastructure and tooling to enable model development, deployment, monitoring, and iteration. Lead realtime model monitoring, experiment tracking, reproducibility, and operational reliability to scale fraud-prevention ML systems in production.

Lead architectural design of AI/ML solutions, mentor staff, and ensure data governance compliance in high-scale enterprise environments.