I.T. & Communications · Permanent
MLops Engineer (Remote)
Motion Recruitment · Georgia, United States
- Location: Georgia, United States
- Employment: Permanent
Job description
Overview
In this Lead Software Platform Engineer role, you own and scale AI/ML infrastructure as a production-grade, multi-tenant platform for scientists at top pharmaceutical customers. You will serve as the technical design authority for AI platforms, model serving, LLMs, and observability within a regulated environment. You'll shape the future direction of AI infrastructure while collaborating with cross-functional teams. This position offers high-impact work at the intersection of distributed systems and MLOps, tackling scale, security, and governance across enterprise workloads.
Compensation / Benefits
• 100% employer-paid benefits for all eligible employees and immediate family members
• Unlimited PTO
• 401K
• Remote work
• Company paid Life Insurance, LTD/STD
• Culture of continuous improvement
Responsibilities
• Design and scale AI/ML platform architecture
• Build model-serving and agent infrastructure
• Develop evaluation, observability, and governance capabilities
• Partner with Applied AI, Data Engineering, Security, and Platform teams
• Provide technical leadership, conduct architecture reviews, and mentor engineers
Key requirements
• 10+ years in software and infrastructure engineering designing, building, and scaling distributed cloud-native systems
• Technical leader or architect experience with system design, scalability, performance, and cost optimization
• Security-by-design for multi-tenant platforms handling sensitive data (PII/PHI) and LLM risks
• Production experience building AI/ML infrastructure as a multi-tenant product with external users
• Hands-on deployment/operation of LLM-based systems (RAG, embeddings, prompt/versioning)
• Expert TypeScript and Python coding for backend services/APIs
• Experience with model registry/serving platforms, preferably Databricks MLflow
• Experience with AI evaluation frameworks, drift/quality monitoring
• REST/OpenAPI API design, scalable/versioned APIs
• Strong AWS and containerization (Docker); CloudFormation or AWS CDK; CI/CD familiarity
• Observability practices (monitoring, logging, tracing, SLI/SLO/SLA) and collaboration with cross-functional teams
• Ability to influence technical direction, communicate with customers, and mentor engineers
• Cross-functional collaboration
• Mentoring and leadership
• Strong communication with customers and teams
• TypeScript
• Python
• Databricks MLflow
In this Lead Software Platform Engineer role, you own and scale AI/ML infrastructure as a production-grade, multi-tenant platform for scientists at top pharmaceutical customers. You will serve as the technical design authority for AI platforms, model serving, LLMs, and observability within a regulated environment. You'll shape the future direction of AI infrastructure while collaborating with cross-functional teams. This position offers high-impact work at the intersection of distributed systems and MLOps, tackling scale, security, and governance across enterprise workloads.
Compensation / Benefits
• 100% employer-paid benefits for all eligible employees and immediate family members
• Unlimited PTO
• 401K
• Remote work
• Company paid Life Insurance, LTD/STD
• Culture of continuous improvement
Responsibilities
• Design and scale AI/ML platform architecture
• Build model-serving and agent infrastructure
• Develop evaluation, observability, and governance capabilities
• Partner with Applied AI, Data Engineering, Security, and Platform teams
• Provide technical leadership, conduct architecture reviews, and mentor engineers
Key requirements
• 10+ years in software and infrastructure engineering designing, building, and scaling distributed cloud-native systems
• Technical leader or architect experience with system design, scalability, performance, and cost optimization
• Security-by-design for multi-tenant platforms handling sensitive data (PII/PHI) and LLM risks
• Production experience building AI/ML infrastructure as a multi-tenant product with external users
• Hands-on deployment/operation of LLM-based systems (RAG, embeddings, prompt/versioning)
• Expert TypeScript and Python coding for backend services/APIs
• Experience with model registry/serving platforms, preferably Databricks MLflow
• Experience with AI evaluation frameworks, drift/quality monitoring
• REST/OpenAPI API design, scalable/versioned APIs
• Strong AWS and containerization (Docker); CloudFormation or AWS CDK; CI/CD familiarity
• Observability practices (monitoring, logging, tracing, SLI/SLO/SLA) and collaboration with cross-functional teams
• Ability to influence technical direction, communicate with customers, and mentor engineers
• Cross-functional collaboration
• Mentoring and leadership
• Strong communication with customers and teams
• TypeScript
• Python
• Databricks MLflow