Senior Machine Learning Engineer

Who you are

• 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
• 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
• 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 the job involves

• As 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
• 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
• 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

Benefits

• Health & dental insurance through BCBS
• Vision coverage Health Savings Account
• Life Insurance & Disability Coverage
• 401(k) plan
• Access to KGA Life Services, which includes counseling, financial & legal consultations, and referrals for a wide range of services
• 20 vacation days
• Unlimited sick days
• 40 hours of time off for volunteer work
• 12 paid holidays
• Parental leave
• New facility in Watertown, MA
• Free on-site lunch daily
• Commuter benefits
• Free on-site parking