Principal Machine Learning Engineer

About Kintsugi

Kintsugi is on a mission to scale access to mental healthcare for all. We are developing novel voice biomarker software to detect signs of depression and anxiety from short clips of free form speech. Awarded multiple distinctions for AI technology and recently named one of Forbes’ Top 50 AI companies to watch in 2022 and Fierce 15 in 2023, Kintsugi helps to close mental health care gaps across risk-bearing health systems, ultimately saving time and lives.

At Kintsugi, we believe that mental health is just as important as physical health. We exist to ensure that everyone who needs mental healthcare has access to the right care at the right time.

About the Team

We're a female-founded organization, united and driven by our shared passion to revolutionize access to mental healthcare. Our mission is ambitious, and each member of our team wears multiple hats and plays a pivotal role. As an early-stage, Series A startup, we offer exciting growth opportunities and the chance to make a real impact. Join us to embark on a rewarding journey, learning and growing alongside our dedicated team of trailblazers. 

The Role

As our Machine Learning Tech Lead, you will play a pivotal role in leading a group of talented researchers and engineers in the development of cutting-edge voice analysis models. As our ML expert, you will communicate directly with company leadership on recent findings, strategy, and operational requirements for the success of the ML team. You'll work closely with the software engineering and product teams to ensure the seamless integration of our ML models into production. In addition, you'll collaborate with our clinical team to design data collection strategies and expand our clinically validated datasets. 

Kintsugi offers a holistic total rewards package designed to support our employees in all aspects of their life inside and outside of work. The expected base salary for this position will range from $175,000 - $225,000 + Equity. Actual compensation may vary from posted base salary depending on your confirmed job-related skills and experience.

Responsibilities

• Lead ML team in the technical aspects of core-product development including investigating, planning, executing, evaluating, and reporting on the entire MLOps pipeline from problem definition, data requirements, experimentation, productization, reporting, and monitoring
• Be self-directed to work independently in a multidisciplinary team environment
• Roll up your sleeves and work alongside team members on portions of projects to ensure the completion of high-priority tasks and critical non-project work
• Advise, direct, coach, inspire and review the work of early-career team members on complex projects
• Manage the workload, inter-team communication, conflict resolution, and career development of the ML staff
• Lead the planning, execution, and retros for the ML team sprints
• Build, maintain, and report on the technical roadmap and quarterly OKRs for ML workstreams, milestones, and deliverables in collaboration with the product and software engineering teams.
• Create and manage ML project plans, identifying critical paths and resource requirements, including budget allocation
• Conduct ongoing research on emerging voice analysis technologies and make recommendations on their applicability within our organization
• Stay current with industry advancements by attending seminars, reviewing technical literature, and establishing thought leadership in voice biomarkers

Qualifications

• M.S./Ph.D. in Computer Science or a related field with 5+ years of experience building production-grade machine learning models in industry settings
• 3+ years of experience leading R&D or ML projects
• Strong programming skills in Python with extensive experience with the scientific and deep-learning stack (numpy, pandas, numba, torch, tensorflow, jupyter)
• A proven track record of building end-to-end deep-learning models
• Experience with ML model efficiency optimization for production deployment
• Ambitious team player with strong communication skills (oral and written)
• Experience implementing and experimenting with cutting-edge ML techniques from the latest literature
• Experience with cloud services (GCP, AWS, Azure) for training, data processing and/or model deployment
• Possess excellent interpersonal skills, with the ability to communicate effectively, provide guidance, negotiate, and influence others as needed, while also building strong, productive working relationships in a variety of settings.

Bonus Qualifications