Senior Principal Machine Learning Engineer
Skills
Computer ScienceAmazon Web ServicesApache SparkChanging EnvironmentsCommandData WarehousingEasily Adaptable
What the job involves
The main requirements, responsibilities and hiring steps.
Requirements
- Bachelor's or Master's degree in Computer Science Engineering or related technical field or equivalent practical experience
- 12+ years of software or data engineering experience with significant time at Principal level or above
- Expert knowledge of distributed data processing with Spark and stream and batch pipeline design
- Strong ML engineering skills including feature engineering model training evaluation deployment and production monitoring
- Hands-on experience with GenAI and LLM workflows including RAG fine-tuning prompt engineering and responsible AI practices
- Cloud-native platform experience across AWS GCP Azure and managed data and ML services
- Proficiency in Python and SQL with comfort in Go Java or equivalent
- Proven ability to lead complex cross-functional technical initiatives from ambiguity to production
- Excellent written and verbal communication skills with senior technical and non-technical stakeholders
Nice to have
- Strategic thinking
- Systems thinking
- Technical depth
- Cross-functional influence
- Data-driven
- Ownership
- Clear communication
- Mentorship
- Adaptability
Day to day
- Lead the technical direction for company-wide Data and AI/ML solutions with autonomy and pragmatic judgment.
- Design and unblock scalable ML platform architecture while moving fluidly between hands-on execution and high-level strategy.
- Partner with engineering, product, clinical, data, and business stakeholders to turn ambiguous problems into production-ready technical solutions.
- Mentor senior engineers, influence cross-functional teams, and strengthen the broader engineering organization through design review and technical coaching.