MLops Engineer (Remote)

Motion Recruitment; Massachusetts; Remote; USD 180,000 - 250,000; Full time

Benefits offered by this job

100% employer-paid benefits

Unlimited PTO

401K

Remote work

Life Insurance

Continuous improvement culture

Job summary

TetraScience is seeking a Lead Software Platform Engineer to own and scale AI and data infrastructure for production-grade AI/ML workflows used by scientists at top pharmaceutical companies.

You will serve as the design authority for AI platforms, model serving, LLMs, agents, observability, security, and evaluation frameworks, defining the future direction of AI infra in regulated settings.

Qualifications

• 10+ years in software and infrastructure engineering for distributed cloud-native systems.
• Technical leader or architect responsible for design, scalability, performance and cost optimization.
• Experience designing security into multi-tenant platforms handling sensitive data (PII/PHI) and LLM risks.

Responsibilities

• Design and scale AI/ML platform architecture for production use.
• Build model-serving and agent infrastructure across teams.
• Develop evaluation, observability, and governance capabilities for AI platforms.
• Partner with Applied AI, Data Engineering, Security, and Platform teams.
• Provide technical leadership, architecture reviews, and mentorship.

Skills

Distributed systems

Technical leadership

Security for multi-tenant

AWS

CI/CD

Observability

Mentoring

REST/OpenAPI

LLM infrastructure

Python

TypeScript

Model serving

Tools

Databricks MLflow

Docker

AWS CDK

CloudFormation

OpenAPI

REST

Kubernetes

Job description

Join TetraScience, the Scientific Data and AI Cloud company, as a Lead Software Platform Engineer working at the intersection of distributed systems and MLOps. In this role, you will own and scale AI and data infrastructure that supports production-grade AI/ML workflows for scientists at some of the world's largest pharmaceutical companies.
This is a highly impactful opportunity for an engineer who has built AI/ML infrastructure as a multi-tenant product rather than internal tooling. You will serve as the technical design authority for AI platforms, model serving, LLMs, agents, observability, security, and evaluation frameworks while helping define the future direction of AI infrastructure in a regulated environment.

Required Skills & Experience

• 10+ years of professional experience in software engineering and infrastructure engineering designing, building, and scaling distributed cloud-native systems
• Demonstrated experience as a technical leader or architect responsible for system design, scalability, performance, and cost optimization
• Experience designing security into multi-tenant platforms, including handling sensitive data such as PII and PHI and mitigating LLM-specific risks
• Extensive experience building and maintaining AI/ML infrastructure in production as a multi-tenant product with external users
• Deep hands-on experience deploying and operating LLM-based systems including RAG architectures, retrieval and embedding design, prompt versioning, model versioning, and tool/function calling
• Expert-level coding skills in TypeScript and Python for backend services and APIs
• Production experience with model registry and serving platforms, ideally Databricks MLflow
• Experience building AI evaluation frameworks, regression gates, and drift or quality monitoring capabilities
• Experience designing scalable, secure, versioned APIs using REST and OpenAPI specifications
• Strong AWS and containerization experience, including Docker
• Experience with CloudFormation or AWS CDK and contributing to deployment automation and CI/CD processes
• Experience defining observability practices including monitoring, alerting, logging, distributed tracing, and SLI/SLO/SLA models
• Ability to influence technical direction, communicate with customers and cross-functional teams, and mentor engineers

Desired Skills & Experience

• Familiarity with emerging LLM frameworks for advanced prompt orchestration and programmatic LLM pipelines
• Experience running agentic or multi-step orchestration in production
• Experience with MCP as an integration surface for tooling and non-human identities
• Understanding of LLM cost monitoring, latency optimization, and usage analytics in production environments
• Experience with multimodal model inputs including image and instrument data
• Experience with fine-tuning, distillation, quantization, batching, KV-cache strategies, or other model optimization techniques
• Experience delivering AI/ML systems in regulated environments including GxP, 21 CFR Part 11, or SOC 2 environments
• Background in scientific, life sciences, or laboratory data domains

What You Will Be Doing

Tech Breakdown

• AI/ML Platform Architecture
• [Confirm: percentage] LLMs, Agents, and RAG Systems
• [Confirm: percentage] AWS Infrastructure & Cloud Services
• [Confirm: percentage] Model Lifecycle Management & MLflow
• [Confirm: percentage] Security, Observability, and Compliance

Daily Responsibilities

• Designing and scaling AI/ML platform architecture
• Building model-serving and agent infrastructure
• Developing evaluation, observability, and governance capabilities
• Partnering with Applied AI, Data Engineering, Security, and Platform teams
• Technical leadership, architecture reviews, and mentoring

The Offer

• 100% employer-paid benefits for all eligible employees and immediate family members
• Unlimited paid time off (PTO)
• 401K
• Flexible working arrangements - Remote work
• Company paid Life Insurance, LTD/STD
• A culture of continuous improvement where you can grow your career and get coaching