logo inner

Staff Machine Learning Infrastructure Engineer

Dyno TherapeuticsWatertown | Massachusetts, United StatesOnsite

The Role


Staff ML Infrastructure Engineer. We’re looking for a relentless systematizing infra expert who thrives at the intersection of machine learning and cloud-native engineering. This role is for someone eager to build the foundation underlying Dyno’s ML capabilities and help accelerate the discovery of next-generation gene therapies.Job Type: Full TimeLocation: Watertown, MA or NYC

How You Will Contribute


As Staff ML Infrastructure Engineer, you will be responsible for designing, optimizing, and scaling the infrastructure that powers Dyno’s ML-driven capsid design platform. Your work will ensure our models train faster, deploy more efficiently, and operate reliably at scale. This role is core to our platform’s success - enabling seamless iteration across ML research and engineering, and accelerating our mission to transform genetic medicine.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: 

  • Own and optimize ML compute infrastructure: manage dynamic allocation, track usage and costs, and forecast future needs.
  • Partner with other engineers to evolve our ML tooling and development environment, improving reproducibility, efficiency, and developer velocity.
  • Deploy ML models into production environments and improve inference performance.
  • Manage vendor relationships (e.g., Google Cloud, Weights & Biases), including technical oversight and future-looking decision making.
  • Work with urgency and adaptability, balancing innovation with execution.
  • Collaborate cross-functionally, leveraging Dyno’s high-trust, high-impact culture to drive results.

Basic qualifications


  • BS with 4 years+ of relevant industry experience.
  • Experience with cloud-native infrastructure (GCP or AWS), particularly for ML workflows.
  • Python fluency for scripting, automation, and infrastructure tooling.
  • Experience working in and managing containerized environments (Docker, Kubernetes).
  • Hands-on experience supporting large-scale ML training and experimentation.
  • Ability to own vendor relationships from a technical perspective.
  • Alignment with Dyno’s core values - We seek individuals who step up when things get tough, recalibrate when priorities shift, and thrive in a high-expectation environment.
  • A proactive, problem-solving mindset.

Preferred qualifications


  • Experience with deep learning frameworks (e.g., PyTorch, TensorFlow) in production.
  • Experience managing compute budgets and forecasting needs.
  • Prior involvement in cloud infrastructure transitions or system migrations.

The Company


At Dyno Therapeutics, we are a high-energy, high-impact team on a mission to build high-performance genetic technologies that transform patient lives. Our team unites world-class molecular biologists, protein engineers, software developers, data scientists, and machine learning experts—all working together at the intersection of AI and genetic medicine.Our culture is defined by three core values that guide everything we do:

  • One Mission: Everything we do is for the mission. We are a cohesive and motivated team, thinking ahead and supporting one another to overcome challenges.
  • Proactive Responsibility: We take action, inject energy into our work, and hold ourselves accountable for delivering results.
  • Reaching for Excellence: We constantly strive for excellence, fueled by curiosity, adaptability, and the courage to speak hard truths in pursuit of success.

These values are more than words—they drive our actions and decisions. Our greatest strength isn’t technology—it’s our work ethic. More than just technologists, we’re a team of relentlessly resourceful problem-solvers: with an unshakable drive we generate breakthroughs at the intersection of AI and genetic medicine.

🚀 What You’ll Give:


  • Bring an unstoppable work ethic, stepping up when things get tough and adapting as priorities shift.
  • Embrace challenges as opportunities, finding solutions where none exist and driving innovation forward.
  • Operate with urgency, responsibility, and resilience, because this mission demands the best from us.

🎯 What You’ll Get:


  • Competitive compensation & equity—your contributions drive results, and we pay accordingly.
  • Mission-aligned, high-trust environment—we succeed together, supporting each other through challenges.
  • A career-defining experience—work at the forefront of AI-driven genetic medicine, tackling problems that reshape healthcare.

If you’re ready to push boundaries, build the future, and thrive in a fast-moving, high-impact environment—we’d love to hear from you.

Equal Employment Opportunity (EEO) Statement


We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.Fraud Alert: Please be aware of recruitment scams targeting job seekers. Dyno Therapeutics will never make an offer of employment without conducting a formal interview process, nor will we ask for personal information such as financial details over email. Official communication will only come from an @dynotx.com email address.

If you are contacted by someone claiming to represent Dyno Therapeutics from any other domain, please report it as spam and report the communication to us at jobs@dynotx.com.

Life at Dyno Therapeutics

Dyno Therapeutics is a Cambridge based, VC-backed biotech startup that uses next-gen DNA technologies and machine learning to engineer Adeno-associated Virus (AAV) capsids for effective delivery of gene therapies.
Thrive Here & What We Value- Pioneer in machine learning for blackbox protein design- Values diversity; non-discriminatory policies- NEVY Emerging Company of the Year (2021)- Endpoints 11 Company (2021)- Forbes' America’s Best Startups (2022, 2023)

Related Sub

This job belongs to these sub. Explore related roles here:
Machine learning jobs
Your tracker settings

We use cookies and similar methods to recognize visitors and remember their preferences. We also use them to measure ad campaign effectiveness, target ads and analyze site traffic. To learn more about these methods, including how to disable them, view our Cookie Policy or Privacy Policy.

By tapping `Accept`, you consent to the use of these methods by us and third parties. You can always change your tracker preferences by visiting our Cookie Policy.

logo innerThatStartupJob
Discover the best startup and their job positions, all in one place.
Copyright © 2025