Senior Machine Learning (ML) Engineer

Dyania Health is a venture-backed company focused on transforming the way machines understand and process medical information. They are seeking a Senior Machine Learning Engineer to design, build, and deploy scalable ML-driven systems that enhance biomedical information processing.

Responsibilities:

• 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

Requirements:

• 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
• 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