Lead Platform Engineer - Cambridge, Ma

$200000 - $250000

Job Description A technology-driven organization in Cambridge, MA is hiring a Lead Platform Engineer to help build and scale the infrastructure powering next-generation AI and machine learning systems. This is a highly visible leadership opportunity for an experienced engineer who has successfully taken machine learning initiatives from research through production deployment at scale.

This role is ideal for someone who combines deep platform engineering expertise with hands-on MLOps experience. You will partner with data scientists, machine learning engineers, and infrastructure teams to develop robust systems for model training, deployment, monitoring, and lifecycle management. The successful candidate will play a key role in establishing best practices for production AI workloads while ensuring reliability, observability, and operational excellence. Required Skills & Experience

• 10+ years of experience in Software Engineering, Platform Engineering, DevOps, SRE, or related disciplines

• 2+ years of hands-on MLOps experience in production environments

• Experience training, deploying, and operating machine learning models at scale

• Strong understanding of ML lifecycle management from experimentation through production

• Experience building infrastructure for model training pipelines and model deployment workflows

• Expertise with cloud platforms, preferably AWS

• Experience implementing observability, monitoring, and alerting solutions for machine learning systems

• Strong background with Kubernetes and containerized applications

• Experience with CI/CD automation and infrastructure-as-code practices

• Proficiency with Python and modern software engineering best practices

• Strong communication and technical leadership skills

Desired Skills & Experience

• Experience supporting GenAI, LLM, or Agentic AI applications

• Familiarity with ML orchestration frameworks such as Kubeflow, MLflow, SageMaker, Airflow, or similar technologies

• Experience with distributed training environments and GPU infrastructure

• Background in platform architecture and technical leadership

• Experience designing secure and scalable cloud-native systems

• Exposure to data engineering and large-scale data platforms

What You Will Be Doing Daily Responsibilities

• Lead the design and development of scalable platform infrastructure supporting machine learning workloads

• Build and optimize model training pipelines and deployment frameworks

• Develop processes and tooling for reliable model delivery into production environments

• Create observability solutions to monitor model performance, drift, latency, availability, and operational health

• Partner with Data Science and Engineering teams to improve the efficiency of the ML development lifecycle

• Establish best practices for MLOps, automation, and platform reliability

• Drive improvements in cloud infrastructure, Kubernetes operations, and deployment automation

• Mentor engineers and provide technical leadership across platform initiatives

• Troubleshoot complex production issues involving AI and ML services

• Ensure high availability, scalability, and security of model-serving environments

The Offer

• Base Salary: Up to $250,000

• Location: Cambridge, MA

• Full-Time Opportunity

• Leadership-Level Position

• Competitive Bonus Potential

You will receive the following benefits

• Medical Insurance

• Dental Benefits

• Vision Benefits

• Paid Time Off (PTO)

• 401(k)

Applicants must be currently authorized to work in the US on a full-time basis now and in the future.

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.