Lead MLOps Engineer (Remote EST)

Kelly Services

Cambridge (MA)

Remote

USD 200,000 - 250,000

Full time

14 days+

Get a reply from this employer

Your resume and cover letter, tailored to exactly what they’re hiring for.

Get past ATS filters

Benefits offered by this job

Medical Insurance
Dental Benefits
Vision Benefits
Unlimited PTO
401(k)
Life Insurance
Short-Term Disability
Long-Term Disability

Job summary

Motion Recruitment Partners is seeking a senior Lead MLOps Engineer to join a remote-first team operating in the Eastern Time Zone. You will architect and run scalable ML platforms that move models from development to production, balancing reliability, security, and governance across AI services.

You will own deployment frameworks, observability, and cost management while mentoring engineers and shaping engineering standards. This role is fully remote for ETZ-aligned candidates.

Qualifications

  • 10+ years of experience in software engineering, infrastructure engineering, or platform development.
  • Proven experience leading MLOps initiatives in enterprise production environments.
  • Strong background designing highly scalable distributed applications and services.
  • Expertise deploying, managing, and optimizing machine learning models in production.
  • Experience supporting Generative AI and Large Language Model (LLM) applications.
  • Deep understanding of CI/CD pipelines for AI and machine learning workloads.
  • Hands-on experience with model registries, versioning strategies, and deployment automation.
  • Advanced proficiency developing production software with Python and TypeScript.
  • Strong experience designing and consuming RESTful APIs.
  • Expertise building solutions within AWS cloud environments.
  • Experience working with Docker and container orchestration technologies.
  • Knowledge of Infrastructure as Code methodologies including AWS CDK and CloudFormation.
  • Experience implementing monitoring, logging, alerting, and reliability practices.
  • Understanding of security best practices for cloud-native and multi-tenant platforms.
  • Ability to lead technical discussions, mentor engineers, and drive engineering standards.

Responsibilities

  • Own the operational strategy for machine learning infrastructure and deployment platforms.
  • Build frameworks that accelerate the delivery of AI solutions from experimentation to production.
  • Create repeatable deployment processes that improve reliability and reduce operational risk.
  • Develop platform capabilities that support model serving, monitoring, and governance.
  • Implement automation that simplifies infrastructure provisioning and software releases.
  • Establish observability practices across AI services, APIs, and backend systems.
  • Partner with machine learning engineers to improve model performance and operational readiness.
  • Drive platform scalability initiatives that support growing customer demand.
  • Define best practices for security, resiliency, and cost management.
  • Troubleshoot complex production issues and lead technical resolution efforts.
  • Collaborate with cross-functional teams on architecture, planning, and platform strategy.
  • Mentor engineering teams on MLOps methodologies and modern cloud engineering practices.

Skills

ML Ops Leadership
Distributed Systems
AI CI/CD
Python
TypeScript
AWS Cloud
Docker
Kubernetes
REST APIs
Model Registry
Security Best Practices

Tools

AWS CDK
CloudFormation

Job description

$200000 - $250000

Job DescriptionA remote-first technology company transforming how organizations operationalize artificial intelligence is seeking a Lead MLOps Engineer to join its growing engineering team. Candidates must be based within the Eastern Time Zone to support collaboration across product, engineering, and leadership stakeholders.

This is a senior-level opportunity for an engineer who has built and operated machine learning platforms that support real-world production workloads. Rather than focusing solely on model development, this role centers on creating the infrastructure, deployment frameworks, governance standards, and operational processes that allow AI systems to run reliably at scale.

You will be responsible for bridging the gap between software engineering and machine learning by creating the systems that enable models, AI services, and intelligent applications to move efficiently from development to production. Success in this role requires deep cloud expertise, platform engineering experience, and a passion for building highly available systems that support business-critical AI initiatives.

Required Skills & Experience
  • 10+ years of experience in software engineering, infrastructure engineering, or platform development
  • Proven experience leading MLOps initiatives in enterprise production environments
  • Strong background designing highly scalable distributed applications and services
  • Expertise deploying, managing, and optimizing machine learning models in production
  • Experience supporting Generative AI and Large Language Model (LLM) applications
  • Deep understanding of CI/CD pipelines for AI and machine learning workloads
  • Hands-on experience with model registries, versioning strategies, and deployment automation
  • Advanced proficiency developing production software with Python and TypeScript
  • Strong experience designing and consuming RESTful APIs
  • Expertise building solutions within AWS cloud environments
  • Experience working with Docker and container orchestration technologies
  • Knowledge of Infrastructure as Code methodologies including AWS CDK and CloudFormation
  • Experience implementing monitoring, logging, alerting, and reliability practices
  • Understanding of security best practices for cloud-native and multi-tenant platforms
  • Ability to lead technical discussions, mentor engineers, and drive engineering standards
Desired Skills & Experience
  • Experience supporting Retrieval-Augmented Generation (RAG) implementations
  • Knowledge of vector databases, embeddings, and semantic search architectures
  • Familiarity with AI agent frameworks and model orchestration technologies
  • Experience creating automated model evaluation and validation pipelines
  • Understanding of scalable GPU infrastructure and inference optimization
  • Exposure to scientific computing, healthcare, life sciences, or regulated industries
  • Experience implementing AI governance, auditing, and compliance controls
  • Familiarity with performance tuning techniques for model serving environmentsExperience improving development workflows through automation and platform tooling
What You Will Be Doing Daily Responsibilities
  • Own the operational strategy for machine learning infrastructure and deployment platforms
  • Build frameworks that accelerate the delivery of AI solutions from experimentation to production
  • Create repeatable deployment processes that improve reliability and reduce operational risk
  • Develop platform capabilities that support model serving, monitoring, and governance
  • Implement automation that simplifies infrastructure provisioning and software releases
  • Establish observability practices across AI services, APIs, and backend systems
  • Partner with machine learning engineers to improve model performance and operational readiness
  • Drive platform scalability initiatives that support growing customer demand
  • Define best practices for security, resiliency, and cost management
  • Troubleshoot complex production issues and lead technical resolution efforts
  • Collaborate with cross-functional teams on architecture, planning, and platform strategy
  • Mentor engineering teams on MLOps methodologies and modern cloud engineering practices
The Offer
  • Competitive compensation package
  • Fully remote position for candidates located in the Eastern Time Zone
  • Opportunity to lead critical machine learning infrastructure initiatives
  • Exposure to large-scale AI and cloud engineering challenges
  • High degree of ownership, autonomy, and technical influence
  • Collaborative environment focused on innovation and engineering excellence
You will receive the following benefits
  • Medical Insurance
  • Dental Benefits
  • Vision Benefits
  • Unlimited Paid Time Off (PTO)
  • 401(k)
  • Life Insurance
  • Short-Term Disability Coverage
  • Long-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.

Motion Recruitment Partners (MRP) is an Equal Opportunity Employer. All applicants must be currently authorized to work on a full-time basis in the country for which they are applying, and no sponsorship is currently available. Employment is subject to the successful completion of a pre-employment screening. Accommodation will be provided in all parts of the hiring process as required under MRP’s Employment Accommodation policy. Applicants need to make their needs known in advance.

Get your free, confidential resume review.

or drag and drop your file here.

Similar jobs

Similar jobs worth comparing

Lead MLOps Engineer (Remote EST)
Lead MLOps Engineer (Remote EST)

Motion Recruitment • Massachusetts

Remote
USD 180,000 - 240,000
Medical Insurance
Dental Benefits
Vision Benefits
+5
Lead MLOps Engineer (Remote EST)
Lead MLOps Engineer (Remote EST)

Motion Recruitment • Cambridge (MA)

Remote
USD 180,000 - 240,000
Medical Insurance
Dental Benefits
Vision Benefits
+5
Lead MLOps Engineer (Remote in MA)
Lead MLOps Engineer (Remote in MA)

Kelly Services • Cambridge (MA)

Remote
USD 200,000 - 250,000
Medical Insurance
Dental Benefits
Vision Benefits
+5
Staff MLOps Engineer (Remote in RI)
Staff MLOps Engineer (Remote in RI)

Motion Recruitment • Providence (RI)

Remote
USD 150,000 - 210,000
Medical Insurance
Dental Benefits
Vision Benefits
+5
MLops Engineer (Remote)
MLops Engineer (Remote)

Kelly Services • Boston (MA)

Remote
USD 276,000 - 372,000
Remote work
401K
Paid PTO
+1
IT Analyst V
IT Analyst V

Experis Technology Group • United States

Remote
USD 120,000 - 160,000
Remote work
Senior MLOps Engineer
Senior MLOps Engineer

Judge Group, Inc. • Phoenix (AZ)

On-site
USD 90,000 - 96,000
Medical insurance
Dental insurance
Vision insurance
MLOps Senior Engineer - Remote
MLOps Senior Engineer - Remote

Kforce Inc • Atlanta (GA)

Remote
USD 130,000 - 180,000
Medical insurance
Dental insurance
Vision insurance
+5
MLOPS Engineer- Remote
MLOPS Engineer- Remote

Innova Solutions • United States

Remote
USD 120,000 - 180,000
Senior ML OPs Engineer
Senior ML OPs Engineer

Glocomms • California

Hybrid
USD 198,000 - 230,000
Meal stipends for remote work days
Generous paid time off
Comprehensive health coverage
+1