Remote Gpu Engineer Jobs in Missouri (NOW HIRING)

• Own and evolve research infrastructure end-to-end, including experiment orchestration, distributed training, model tracking, evaluation workflows, and automated deployment systems.
• Build and scale distributed computing solutions for machine learning workloads, including multi-node GPU environments, data pipelines, and cost-efficient infrastructure management across cloud platforms.
• Improve research and development velocity through performance engineering, including optimizing simulators, training pipelines, profiling bottlenecks, and implementing scalable solutions.
• Act as a bridge between research and production engineering teams, helping transform AI breakthroughs into reliable production-ready systems.
• Develop a deep understanding of internal platforms, tools, and technical capabilities to support effective customer-facing solutions.
• Maintain clear documentation of research projects, engineering decisions, products, and operational processes.
• Contribute to medium- and long-term technical decisions that shape research infrastructure and engineering strategy.
• Lead projects from concept to delivery, taking ownership of execution, prioritization, and successful outcomes.
• Mentor team members, share technical knowledge, and support collaborative problem-solving across engineering teams.
• Continuously improve development practices, tooling, and infrastructure to accelerate AI research and deployment.

• 4+ years of relevant professional experience in software engineering, machine learning engineering, MLOps, or related technical fields.
• Proven experience leading technical projects and owning delivery from initial concept through implementation.
• Previous experience working in machine learning research and development environments, ideally connecting research initiatives with production systems.
• Strong understanding of machine learning and MLOps concepts, including experiment tracking, model lifecycle management, deployment processes, and systems involving non-deterministic components.
• Strong programming skills in Python and familiarity with lower-level programming languages such as C++ or Rust.
• Solid engineering foundation combined with scientific understanding in areas such as machine learning, optimization, control systems, or physical sciences.
• Experience designing scalable infrastructure for AI workloads, distributed computing, or cloud-based environments.
• Strong problem-solving abilities, curiosity, and willingness to explore unfamiliar technical domains.
• Excellent organizational, communication, and collaboration skills in a remote and international environment.
• Alignment with values centered around transparency, collaboration, ownership, operational excellence, and empathy.

Preferred Skills & Experience:

• Experience with machine learning research, AI systems, or MLOps-focused engineering.
• Familiarity with reinforcement learning, simulation environments, or control systems.
• Experience using distributed computing frameworks such as Ray and managing GPU workloads across multiple nodes.
• Knowledge of platforms and tools such as PyTorch, SciPy, scikit-learn, NumPy, pandas, MLflow, Docker, Kubernetes, and cloud infrastructure.
• Understanding of industrial systems, including heating, cooling, manufacturing, or data center environments.
• Scientific or technical background that enables effective collaboration with research-focused teams.

• Competitive base salary ranging from 92,065 to 173,648, depending on location tier, experience, qualifications, and other relevant factors.
• Eligibility for meaningful equity participation.
• Fully remote work environment with flexibility across different locations and time zones.
• Medical, dental, and vision insurance, with benefits varying by region.
• Unlimited paid time off with a required minimum of 20 days per year.
• Paid parental leave, depending on regional policies.
• Flexible stipends supporting workspace setup, personal well-being, and continued professional development.
• Company-provided MacBook.
• Training programs covering technical development, customer immersion, and professional growth.
• Opportunity to work in a fast-paced, collaborative environment where your contributions directly influence technical direction.
• Strong remote culture based on documentation, asynchronous collaboration, regular communication, and virtual team-building activities.
• Significant ownership opportunities and the chance to contribute to impactful AI-driven solutions.