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Maymobility
Tech Lead, Performance Evaluation
datafull-timeRemote, USA
SALARY
Not listed
WORK TYPE
remote
JOB TYPE
full-time
INDUSTRY
ai
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About the role
Responsibilities
- Evaluate simulation test results to drive release & safety decisions.
- Work independently with cross functional teams to develop software and system requirements.
- Lead team code quality activities including design and code reviews.
- Communicate complex analytical findings and model performance metrics to both technical and non-technical stakeholders through clear visualizations and presentations.
- Provide technical guidance to team members.
Skills
Success in this role typically requires the following competencies:
- Expertise in analyzing high-dimensional simulation data.
- Experience building ML prediction models.
- Detail-oriented with a focus on validation, testing, and error detection.
- Awareness of the latest advancements in the field, with the ability to translate innovative concepts into practical solutions for May.
- Excellent problem-solving skills with a meticulous approach to model architecture and optimization.
- Ability to provide individual and team mentorship, including technical leadership for complex projects.
Qualifications and Experience
Required
- B.S, M.S. or Ph.D. Degree in Engineering, Data Science, Computer Science, Math, or a related quantitative field.
- 10+ years of hands-on experience as a Data Scientist or ML Engineer with a strong focus on algorithmic design and deep learning.
- Strong proficiency in Python, SQL, and data analysis tools (e.g., Pandas, NumPy, Spark).
- Demonstrated expertise in databases for data extraction, transformation, and analysis.
- Proven experience building and managing large datasets and evaluations.
- Hands-on expertise in architecting and training complex predictive machine learning models.
- Prior experience in mentoring and supporting junior engineers.
Desirable
- Background in Autonomous vehicles, robotics, physics or related fields.
- Hands-on experience working with simulation data.
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