Technical Lead, ML Operations

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

At the company, we're on a mission to unlock human performance and healthspan. the company empowers members to live longer and perform at higher levels through a deeper understanding of their bodies and daily lives.

We are seeking a senior engineer to operate as a Technical Lead on the the company MLOps team. This individual will own the strategy, roadmap, and execution for a critical component of our ML platform. This is a hybrid individual contributor and leadership role where you will set technical direction and lead a small team, while driving architectural decisions, and partnering closely with Data Science, AI, and Engineering teams to scale the company’s machine learning capabilities.

In this role, you will be responsible not only for building and optimizing ML infrastructure, but also for defining the long‑term vision of your domain, aligning stakeholders, and ensuring successful delivery through both hands‑on contributions and technical leadership.

RESPONSIBILITIES

• Own the technical vision, roadmap, and delivery for a core component of the company’s ML platform, aligning with product and business priorities.

• Lead and manage a small team of engineers by setting direction, prioritizing work, and ensuring high-quality execution against roadmap goals.

• Drive end-to-end delivery of the team, including planning, unblocking, and maintaining a high bar for reliability, scalability, and performance.

• Act as a player‑coach by contributing hands‑on to system design and critical components while mentoring engineers and supporting their growth through regular feedback and coaching.

• Design and evolve scalable ML infrastructure and CI/CD systems, enabling efficient model deployment, monitoring, and lifecycle management.

• Partner cross‑functionally with Data Science, AI, Product, and Engineering to translate ambiguous requirements into robust platform solutions.

• Establish and enforce best practices for architecture, observability, and operational excellence across ML systems.

• Contribute to hiring and team building, helping to scale a high‑performing ML platform team.

QUALIFICATIONS

• Bachelor’s Degree in Computer Science, Software Engineering, or a related field; or equivalent practical experience.

• 7+ years of software engineering experience, including deep experience in ML infrastructure and cloud‑based systems, and prior experience leading or managing engineers.

• Proven track record of owning and delivering complex systems end‑to‑end, including driving execution through a team.

• Experience managing or formally leading engineers, including mentoring, performance feedback, and supporting career development.

• Strong technical expertise in AWS and distributed systems, with experience building scalable, production‑grade ML platforms.

• Proficiency in programming (e.g., Python, Java) and experience building APIs, data pipelines, and real‑time inference systems.

• Demonstrated ability to balance hands‑on technical work with team leadership responsibilities.

• Strong communication and collaboration skills, with experience working across cross‑functional stakeholders.

This role is based in the the company office located in Boston, MA. The successful candidate must be prepared to relocate if necessary to work out of the Boston, MA office.

the company is an Equal Opportunity Employer and participates inE-verifyto determine employment eligibilityThe the company compensation philosophy is designed to attract, motivate, and retain exceptional talent by offering competitive base salaries, meaningful equity, and consistent pay practices that reflect our mission and core values.

At the company, we view total compensation as the combination of base salary, equity, and benefits, with equity serving as a key differentiator that aligns our employees with the long‑term success of the company and allows every member of our corporate team to own part of the company and share in the company’s long‑term growth and success.

The U.S. base salary range for this full‑time position is $150,000 - $215,000. Salary ranges are determined by role, level, and location. Within each range, individual pay is based on factors such as job‑related skills, experience, performance, and relevant education or training. In addition to the base salary, the successful candidate will also receive benefits and a generous equity package. These ranges may be modified in the future to reflect evolving market conditions and organizational needs. While most offers will typically fall toward the starting point of the range, total compensation will depend on the candidate’s specific qualifications, expertise, and alignment with the role’s requirements.