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Machine Learning Engineering Lead

Dyno Therapeutics

United States

Remote

USD 120,000 - 160,000

Full time

Today
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Job summary

A leading biotech company in the United States is seeking an experienced Engineering Lead in Machine Learning to drive technical decisions and mentor junior engineers. This role involves scaling infrastructure, improving ML systems, and fostering partnerships with cloud providers, contributing to advancements in genetic technologies. Ideal candidates should have strong leadership skills and a background in machine learning and infrastructure.

Qualifications

  • Proven experience in a leadership role within machine learning and infrastructure.
  • Strong ability to mentor junior engineers and guide teams.
  • Experience in making high-level technical decisions aligned with company strategy.

Responsibilities

  • Deliver measurable improvements in ML/infra efficiency and reliability.
  • Establish mentorship opportunities for junior engineers.
  • Take ownership of technical decision-making.
  • Build partnerships with cloud providers.
  • Collaborate across R&D efforts.

Skills

Mentorship
Machine Learning
Infrastructure Scaling
Cross-functional Collaboration
Job description

This exciting opportunity is for a seasoned technical leader who thrives at the intersection of machine learning and infrastructure. This role is for someone eager to mentor engineers, scale Dyno’s ML systems, and represent us in strategic technical partnerships, all while helping shape the future of AI-driven genetic technologies.

How You Will Contribute

As an Engineering Lead in Machine Learning you will lead technical decision-making, mentor, and scale infrastructure within Dyno’s ML team. You’ll drive efficiency and reliability in ML/infra interfaces, guide junior engineers in their growth, and represent Dyno externally with strategic partners. Your work will ensure our ML systems can scale with the company’s scientific ambitions, directly enabling breakthroughs in genetic technologies.

At Dyno, every role is mission-driven. Whether in science, engineering, operations, or business, each AAViator contributes to solving some of the most complex challenges in genetic medicine.

Responsibilities
  • Deliver measurable improvements in the efficiency and reliability of ML/infra interfaces.
  • Establish structured mentorship opportunities for junior MLEs, accelerating skill development and team maturity.
  • Take ownership of high-level technical decision-making to ensure alignment with company strategy and scientific priorities.
  • Build and maintain strong partnerships with cloud providers, securing resources and capabilities that directly support Dyno’s ML needs.
  • Collaborate cross-functionally, ensuring ML capabilities are effectively integrated across R&D efforts.
  • Work with urgency and adaptability, balancing innovation with execution.
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