The RoleSr. Machine Learning Engineer. A research-minded machine learning engineer who thrives at the intersection of cutting-edge AI, scientific research, and rigorous engineering. This role is for someone excited to build and scale the models, infrastructure, and AI tools that accelerate Dyno's work at the frontier of AI-driven genetic medicine.
Job Type: Full Time
Location: Watertown, MA; Remote
How You Will ContributeAs a Sr. Machine Learning Engineer, you will build and scale the ML infrastructure, tools, and workflows that power Dyno's research efforts. You will partner closely with AI scientists, protein engineers, and fellow ML engineers to turn novel research into robust, reusable systems-improving model training and inference, optimizing performance, and advancing agentic AI workflows that accelerate scientific discovery.
Responsibilities:
- Build modular, generalizable, and portable ML training systems that support the ongoing development of protein design models.
- Improve the scalability, reliability, and performance of ML training and inference infrastructure to enable rapid research experimentation.
- Optimize model performance using tools such as GPU profiling, custom kernels, and modern accelerated computing frameworks.
- Develop and standardize agentic AI workflows that increase research velocity while maintaining appropriate safety and reliability.
- Partner closely with AI scientists, protein engineers, and other ML engineers to translate research prototypes into robust, reusable tools and systems.
- Contribute across the ML engineering stack, from modeling and GPU-level optimization to distributed training and multi-node orchestration.
- Stay current on emerging ML engineering and agentic AI tools and help the team evaluate and adopt approaches that advance Dyno's research.
- Support the delivery and communication of Dyno's work, both internally and externally.
- 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- 5+ years professional experience building software for machine learning
- Strong software engineering fundamentals (OO design, testing, version control, dependency management, API design)
- Experience containerizing code for remote environments including hands-on experience with Docker and Kubernetes.
- Experience with large-scale distributed training or inference with Ray or a similar framework
- Familiarity with ML performance engineering (identifying bottlenecks, analyzing resource usage, profiling, writing custom kernels)
- Experience designing and owning technically complex systems through requirements-setting, implementation, rollout and maintenance
- Ability to contribute to technical direction through design reviews, cross-team planning, documentation, etc.
- 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 - you don't just identify challenges; you find solutions.
Preferred qualifications- Professional or academic experience in ML research / scientific computing
- Experience building internal platforms and/or developer tools
- Familiarity with common MLOps tools and practices (model monitoring, model versioning, CI/CD, model registries)
- Experience with GPU programming (CUDA, Triton, etc).
- Highly proficient in agentic and usage of modern AI tools for software development
- Exposure to biology, bioinformatics, structural biology, or protein modeling
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.
At Dyno, we believe in transparent and equitable compensation practices.
Base Salary Range: $178,662.29 - $213,680.10/yearThis reflects the typical offer range for this role, based on experience, role scope, and internal equity. Final compensation decisions are made using a consistent leveling framework and consider the candidate's experience, interview performance, and expected impact.
This role is eligible for:
- Annual performance-based bonus
- Stock options
- Comprehensive medical, dental, and vision coverage
- 401(k) plan
- Flexible paid time off and holidays
- Perks including on-campus gym membership, onsite lunch, commuter support, and company provided laptop
Our compensation ranges are reviewed annually to ensure alignment with market trends and internal equity.
