Senior Platform/MLOps Engineer

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Senior Platform/MLOps Engineer in United States.

This role sits at the intersection of advanced AI infrastructure and next-generation manufacturing, where software, robotics, and machine learning converge to redefine how modern factories operate. You will help build and scale the core platform that powers AI-driven inspection, computer vision, and deep learning systems used in real-world industrial environments. The work involves designing highly reliable MLOps pipelines that support training, deployment, and inference at scale, including GPU-based workloads running in Kubernetes. This is a high-impact engineering position where your contributions directly influence production systems used by leading global manufacturers. You will collaborate closely with robotics, platform, and AI teams in a deeply technical, fast-paced environment. The role is ideal for engineers who enjoy solving complex distributed systems challenges while working on cutting-edge AI applications. It combines strong software engineering rigor with real-world physical deployment impact.

Accountabilities:

• Design, build, and maintain scalable, secure, and highly reliable infrastructure supporting AI/ML pipelines, including training, deployment, and inference workflows.
• Develop and optimize MLOps systems for computer vision and deep learning models used in industrial inspection and automation use cases.
• Deploy and manage GPU-intensive workloads on Kubernetes, ensuring performance, scalability, and cost efficiency.
• Build and maintain CI/CD pipelines, GitOps workflows, and infrastructure-as-code solutions to support continuous delivery.
• Write clean, maintainable code and participate in peer code reviews to ensure engineering quality and consistency.
• Collaborate with cross-functional teams to prototype new technologies and evaluate technical feasibility of emerging solutions.
• Improve platform usability and developer velocity through continuous iteration based on real-world usage and feedback.

Requirements:

• 5+ years of experience in Platform Engineering, DevOps, Site Reliability Engineering, or similar infrastructure-focused roles.
• Strong proficiency in at least one modern programming language such as Python, Go, JavaScript, or C#.
• Hands-on experience building and operating MLOps systems in production environments.
• Deep knowledge of Kubernetes, including GPU workload orchestration and modern CNCF ecosystem tools.
• Experience with CI/CD pipelines, GitOps practices, and Infrastructure as Code tools such as Terraform or Ansible.
• Familiarity with observability tooling such as Prometheus, Grafana, and OpenTelemetry.
• Strong understanding of software engineering best practices across the full development lifecycle.
• Excellent collaboration and communication skills with the ability to work across engineering teams.
• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field, or equivalent experience.
• Willingness to travel up to 25%.

Benefits:

• Opportunity to work on cutting-edge AI and robotics systems powering next-generation manufacturing.
• High-impact role contributing directly to real-world industrial and AI infrastructure deployments.
• Collaborative engineering culture focused on innovation, quality, and continuous improvement.
• Exposure to large-scale Kubernetes, GPU computing, and advanced MLOps architectures.
• Career growth opportunities in a rapidly evolving AI and industrial automation environment.
• Work alongside highly skilled engineers across platform, robotics, and AI disciplines.
• Competitive compensation and comprehensive benefits (exact package not specified in the source).

How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether? Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time. #LI-CL1