about 2 months ago
Base Salary
$200k - $250k/yr
Responsibilities
- Own the deployment of ML models and engineering surrogates to customer production environments.
- Communicate results and trade-offs to senior stakeholders and influence product direction.
- Lead scoping and architecture design for data/ML systems, defining success metrics and delivery plans.
- Build robust and scalable ML systems, training and inference pipelines, and APIs.
- Mentor and develop engineers and data scientists, providing technical direction.
- Travel to customer sites for collaboration and solution building.
Requirements
- At least 3 years of industry experience in a commercial, non-research environment.
- Proficiency in Python, PyTorch, Pandas, fastAPI, Scipy, and Kubeflow.
- Experience in deploying ML systems end-to-end and at scale.
- Ability to manipulate 3D point-cloud and mesh data for geometry-aware modeling.
- Strong problem-solving skills and ability to lead technical initiatives.
- US citizenship required due to the nature of aerospace and defense work.
Benefits
- Equity options to share in the company's success.
- 5% contribution to 401(k) for long-term security.
- Free team lunch once a week to foster connection.
- Private health insurance for comprehensive coverage.
- Enhanced parental leave with 3 months full pay for paternity and 6 months for maternity.
- 20 days of annual leave plus public holidays.
- Dedicated support for personal development and learning.
- Subsidized Gympass/Wellhub for physical and mental wellbeing.
- Flexible Spending Account (FSA) for eligible healthcare expenses.