$200000 – $250000
Job Description
A 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 environments
Experience 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.
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