Technical Lead, ML Platform & Ops (Hybrid)

United States Digital Space LLC; Boston (MA); Hybrid; USD 150,000 - 215,000; Full time

Job summary

the company is seeking a Senior ML Platform Technical Lead to own the strategy, roadmap, and execution for a core component of our ML platform in Boston. This hybrid IC/leadership role blends hands-on engineering with people leadership.

You will mentor a small team of engineers, drive end-to-end delivery, and ensure reliability, scalability, and performance while collaborating with Data Science, AI, Product, and Engineering to translate ambiguous requirements into robust platform solutions.

Qualifications

• Bachelor's degree in CS, software engineering, or related field.
• 7+ years of software engineering experience with ML infrastructure and cloud-based systems.
• Proven track record delivering complex systems end-to-end and leading engineers.
• Strong experience with AWS and distributed systems.

Responsibilities

• Own the technical vision, roadmap, and delivery for a core ML platform component.
• Lead a small team of engineers and set direction.
• Drive end-to-end delivery including planning and reliability.
• Mentor engineers and coach for growth.
• Design and evolve scalable ML infra and CI/CD.
• Partner with Data Science, AI, Product, and Engineering to translate requirements.
• Establish best practices for architecture, observability, and operations.
• Contribute to hiring and team-building.

Skills

Leadership / team management

Hands-on engineering

Communication

Education

Bachelor’s Degree in Computer Science, Software Engineering, or related field

Tools

Python

Java

AWS

APIs

Job description

the company is seeking a Senior ML Platform Technical Lead to own the strategy, roadmap, and execution for a core component of our ML platform in Boston. This hybrid IC/leadership role blends hands-on engineering with people leadership.

You will mentor a small team of engineers, drive end-to-end delivery, and ensure reliability, scalability, and performance while collaborating with Data Science, AI, Product, and Engineering to translate ambiguous requirements into robust platform solutions.