Top Remote Machine Learning Jobs in St. Louis, MO

The Lead Data Scientist will architect AI solutions for the energy sector, develop ML algorithms, and collaborate with leadership to shape product strategy.

Lead complex projects leveraging AI and machine learning to deliver innovative data-driven solutions, requiring extensive experience and technical expertise.

As a Research Intern, you will prototype and productionize research in AI and cryptographic schemes, collaborating with teams for real-world impact.

Lead efforts in applying reinforcement learning techniques to enhance model quality and controllability for creative applications. Mentor researchers and contribute to human-in-the-loop systems.

Lead the Mid-Market Sales team to connect technical organizations with AI and data science tools, driving adoption and growth through value-based selling and strong partnerships with engineering teams.

As a Product Manager for Risk, you'll design fraud prevention tools, manage cross-functional teams, and improve fraud detection methods.

As a Staff Software Engineer, you will lead engineering teams, collaborate cross-functionally, drive technical initiatives, and contribute to code while ensuring system resiliency.

The AI Engineer will design, implement, and prototype GenAI and ML solutions to enhance operational intelligence and efficiency in investment services.

The Senior Engineering Manager at Planet leads the engineering team, focusing on delivering products for Defense Intelligence. Responsibilities include mentoring engineers, refining processes, and collaborating across teams for effective deployment of technology.

The VP of Marketing will scale marketing functions, drive demand generation, build teams, establish marketing strategies, and coordinate with sales to enhance pipeline and revenue growth.

The VP of AI and Innovation will define and lead the AI strategy at BeOne Medicine, focusing on innovation, data management, and organizational enablement in healthcare. They will mentor teams and engage stakeholders to drive AI adoption and ensure alignment with business objectives.

Lead product development for credit card decisioning and customer journeys, translating credit policy and data into real-time actions. Partner with Engineering, Data, and Credit to operationalize underwriting and payment models, run experiments, use SQL for analytics, and craft roadmaps that balance business outcomes with customer well-being.

Lead the development of intelligent decision engines modeling customer intent in real-time using advanced data science techniques such as causal inference and machine learning. Collaborate with cross-functional teams to optimize systems for search, fulfillment, and customer experience.

Lead technical engagement across pre-sales, deployment, and post-sales for on-premises quantum systems. Drive customer success, inform product development, support sales with deep HPC/AI/optimization expertise, present at industry events, and translate customer needs into deployment strategies and R&D feedback.

The Global Process Owner for S&OP leads the design and continuous improvement of the S&OP process, ensures collaboration across functions, and drives digital transformation and automation within the organization.

As a ML Engineer focused on inference, you'll design and optimize deep learning models for real-time communication AI applications, collaborating with cross-functional teams and ensuring production readiness.

As a Research Intern, you will work on AI/ML projects, contributing to the development of the Nebula LLM and applying machine learning techniques to real-world problems.

Design and maintain scalable machine learning infrastructure, collaborating with data scientists, ensuring performance, security, and compliance of AI systems.

The ML Engineering Intern will contribute to the Nebula LLM development, tackle machine learning challenges, and gain hands-on experience in AI and language technology.

Senior ML research leader who translates state-of-the-art ML pipeline insights into product requirements, reference architectures, benchmarks, and platform roadmaps. Partners cross-functionally and with strategic customers and research institutions to set evaluation standards, reproducibility, and responsible ML practices while providing technical leadership and influencing product and executive audiences.

As an AI/ML Ops Engineer, you will architect and operate ML pipelines, automate CI/CD processes, and collaborate with cross-functional teams to enhance engineering productivity.

The role involves deploying, optimizing, and maintaining ML-driven motion planning and control algorithms for autonomous driving, collaborating across teams to ensure reliability under performance and safety constraints.

Serve as the presales technical expert for ML capabilities: lead discovery, architect ML solutions, run demos/workshops/proofs-of-concept, coordinate cross-functional teams, and inform product direction based on customer feedback.

Design, architect, and deploy generative AI/LLM solutions from prototype to production; work directly with clients to translate business needs into technical plans; write production-quality code integrating LLMs and ML models; collaborate with cloud, DevOps, and frontend teams; support proposals, sales, and evaluation/observability of models.

As a Product Lead, you will craft the vision and strategy for Payments Intelligence, prioritize projects, and manage a team to optimize products that maximize user revenue while minimizing costs.