Lead MLOps Engineer (Remote in MA)

Motion Recruitment; Cambridge (MA); À distance; USD 180 000 - 230 000; Plein temps

Avantages offerts par ce poste

Medical Insurance

Dental Benefits

Vision Benefits

Unlimited PTO

Résumé du poste

Motion Recruitment is seeking a Lead MLOps Engineer / Software Platform Engineer to design and scale cloud-native AI infrastructure for production AI workloads. The role requires guiding architecture decisions for large-scale platforms and mentoring multiple engineering teams.

Remote opportunity for Massachusetts-residing professionals, with emphasis on secure, multi-tenant environments and observability. Strong leadership and hands-on deployment of LLM-based systems are essential.

Qualifications

• 10+ years of professional software and infrastructure engineering experience.
• Proven expertise designing and scaling cloud-native distributed systems in production.
• Strong background leading technical architecture decisions for large-scale platforms.
• Experience building and operating AI/ML infrastructure as a customer-facing product.
• Hands-on experience deploying and supporting LLM-based applications in production.
• Deep knowledge of Retrieval-Augmented Generation (RAG), prompts, embeddings, and model lifecycle management.

Responsabilités

• Lead the design and evolution of the organization’s AI and machine learning platform.
• Define architecture standards for model serving, agent execution, and scalable AI workloads.
• Manage model lifecycle processes including deployment, versioning, promotion, rollback, and governance.
• Build infrastructure supporting both real-time and batch AI processing.
• Design secure, multi-tenant AI environments with strong data isolation controls.
• Develop evaluation frameworks, testing pipelines, and release gates for AI systems.
• Establish observability, monitoring, and operational excellence standards.
• Drive platform reliability, scalability, and cost-efficiency initiatives.
• Partner with engineering, security, and data teams to deliver enterprise-grade AI solutions.
• Lead design reviews and provide technical mentorship to engineering teams.
• Evaluate emerging AI technologies and make strategic build-versus-buy recommendations.
• Contribute to infrastructure automation, CI/CD improvements, and deployment practices.

Connaissances

Cloud-native architectures

MLOps leadership

Python

TypeScript

LLM deployment

AWS

Docker

CDK

OpenAPI

RAG / prompts

Multi-tenant security

Observability

Outils

Docker tooling

CloudFormation

CDK

OpenAPI

Description du poste

Job DescriptionA rapidly growing AI and data platform organization is seeking a Lead MLOps Engineer / Software Platform Engineer to help build and scale the infrastructure powering next‑generation machine learning and generative AI applications. This fully remote opportunity is open to professionals residing in Massachusetts who want to play a key role in designing cloud-native AI systems used in highly regulated environments.

In this position, you will lead the architecture, deployment, and operational strategy for production‑grade AI services, machine learning platforms, and large language model (LLM) solutions. You will work closely with AI engineers, data teams, and platform engineers to create scalable, secure, and resilient infrastructure that supports both customer-facing and internal AI workloads.

This role is ideal for someone who has successfully built and operated AI/ML platforms serving external users, understands the challenges of distributed systems at scale, and enjoys driving technical direction across engineering organizations.

Required Skills & Experience

• 10+ years of professional software engineering and infrastructure engineering experience
• Proven expertise designing and scaling cloud-native distributed systems in production environments
• Strong background leading technical architecture decisions for large‑scale platforms
• Extensive experience building and operating AI/ML infrastructure as a customer‑facing product
• Hands‑on experience deploying and supporting LLM‑based applications in production
• Deep knowledge of Retrieval‑Augmented Generation (RAG), prompts, embeddings, and model lifecycle management
• Advanced programming skills in Python and TypeScript
• Experience with model deployment, versioning, and model‑serving platforms
• Strong understanding of API architecture, REST services, and OpenAPI specifications
• AWS expertise and experience working with containerized environments such as Docker
• Experience with Infrastructure as Code tools, including CloudFormation or CDK
• Knowledge of observability, monitoring, alerting, tracing, and SLI/SLO/SLA practices
• Experience implementing security controls for multi‑tenant environments, including PII and PHI protection
• Ability to mentor engineers and influence architecture across multiple teams

Desired Skills & Experience

• Familiarity with modern LLM orchestration frameworks
• Experience supporting agent‑based AI systems in production
• Knowledge of model serving optimization, inference tuning, and cost management
• Experience with multimodal AI solutions involving image or scientific datasets
• Background in model optimization techniques such as quantization or distillation
• Experience working in regulated industries with compliance requirements
• Exposure to life sciences, healthcare, laboratory systems, or scientific data platforms
• Understanding of AI governance, evaluation frameworks, and quality monitoring

Daily Responsibilities

• Lead the design and evolution of the organization’s AI and machine learning platform
• Define architecture standards for model serving, agent execution, and scalable AI workloads
• Manage model lifecycle processes including deployment, versioning, promotion, rollback, and governance
• Build infrastructure supporting both real‑time and batch AI processing
• Design secure, multi‑tenant AI environments with strong data isolation controls
• Develop evaluation frameworks, testing pipelines, and release gates for AI systems
• Establish observability, monitoring, and operational excellence standards
• Drive platform reliability, scalability, and cost‑efficiency initiatives
• Partner with engineering, security, and data teams to deliver enterprise‑grade AI solutions
• Lead design reviews and provide technical mentorship to engineering teams
• Evaluate emerging AI technologies and make strategic build‑versus‑buy recommendations
• Contribute to infrastructure automation, CI/CD improvements, and deployment practices

The Offer

• Competitive base salary plus potential bonus eligibility
• Fully remote opportunity for candidates located in Massachusetts
• Opportunity to influence the architecture of a high‑impact AI platform
• Leadership role with significant technical ownership and decision‑making authority

You will receive the following benefits

• Medical Insurance
• Dental Benefits
• Vision Benefits
• Unlimited Paid Time Off (PTO)
• 401(k)
• Life Insurance
• Long‑Term Disability Coverage
• Short‑Term Disability Coverage

Applicants must be currently authorized to work in the US on a full‑time basis now and in the future. Sponsorship is not available for this position.