[Hiring] Senior Machine Learning Engineer @Dyania Health

Role Description

We are seeking Senior Machine Learning / Software engineers who are passionate about their craft to help us in that mission. As a senior ML engineer at Dyania, you'll design, build, and deploy scalable ML-driven systems that power biomedical information processing. In this role, you will operate at the intersection of machine learning research and production-grade software engineering, owning the full lifecycle of ML-powered microservices — from model development and evaluation to deployment, monitoring, and continuous improvement.

You will play a key technical leadership role, mentor junior engineers, and collaborate closely with product, UX, and clinical teams to translate real-world healthcare challenges into robust, scalable solutions.

• Design, implement, and deploy ML-powered software components within a microservice architecture.
• Lead development and productionization of NLP and transformer-based models for biomedical information processing.
• Own the full ML lifecycle: data preparation, model training, evaluation, optimization, deployment, and inference at scale.
• Architect scalable and maintainable ML infrastructure and services.
• Collaborate cross-functionally with product, UX, and clinical stakeholders to understand requirements and rapidly prototype new capabilities.
• Analyze model and system performance; communicate findings and trade-offs clearly to technical and non-technical stakeholders.
• Ensure reliability, scalability, and security of ML services in production environments.
• Mentor junior engineers and contribute to raising the technical bar across the team.
• Contribute to architectural discussions and strategic technical decisions.
• Champion engineering best practices including testing, CI/CD, version control, and documentation.

Qualifications

• 5+ years of industry experience in machine learning-focused software engineering (excluding internships and academic projects).
• Bachelor’s or graduate degree in Computer Science, Mathematics, Electrical Engineering, or a related technical field.
• Strong hands-on experience training, testing, deploying, and serving ML models in production environments.
• Experience with transformer architectures and NLP applications.
• Experience with multi-GPU and multi-node distributed training and inference.
• Proficiency in Python.
• Proficiency in Java (and/or Kotlin/Scala) or C++.
• Experience designing and implementing microservices.
• Professional experience with Git and collaborative development workflows.
• Experience with relational databases and/or NoSQL systems (e.g., knowledge graphs).
• Strong communication skills and ability to explain technical concepts clearly.

Preferred Qualifications

• Experience working with AWS or similar cloud platforms.
• Experience working in agile development environments and familiarity with Jira.
• Experience building ML systems in healthcare or other regulated environments.
• Experience with monitoring, observability, and performance optimization in production ML systems.

What Success Looks Like

• You deliver production-ready ML systems that are scalable, reliable, and maintainable.
• You proactively identify technical risks and propose thoughtful solutions.
• You translate ambiguous biomedical problems into structured ML approaches.
• You elevate the engineering team through mentorship and thoughtful technical leadership.
• You effectively communicate insights and trade-offs to diverse stakeholders.

Team Culture

• We try every day to maintain empathy for patients and our teammates.
• We value small egos, self-awareness, and humility in our teammates.
• We appreciate flexible and adaptive attitudes towards solving problems, as strategic priorities may shift.
• We love diversity of thought, perspective, working style, skill set, knowledge, and interests amongst our team.
• We value open dialogue and brainstorming across multidisciplinary teams.

Benefits

• Competitive Salary
• Health Care Plan (Medical, Dental & Vision)
• Retirement Plan (401k, IRA)
• Generous Paid Time Off (Vacation, Sick & Public Holidays)
• Family Leave (Maternity, Paternity)
• Training & Professional Development Support
• Remote work