Data Scientist
ML Evaluation and Autonomy, R1946
Posted on 2/11/2023
INACTIVE
Develops autonomous AI pilots for military aircrafts
Company Overview
Shield AI, a leader in AI for aviation, has a proven track record of technical innovation, with its Hivemind autonomy stack being the world's first autonomous AI Pilot deployed in combat since 2018. The company's culture is rooted in its mission to protect service members and civilians, and it has been recognized by Forbes, CB Insights, and Fast Company for its industry leadership. With a competitive edge backed by top-tier Silicon Valley VC funds, Shield AI offers a unique opportunity to work on cutting-edge AI technology in aviation.
AI & Machine Learning
Aerospace
B2B
Company Stage
Series F
Total Funding
$940.7M
Founded
2015
Headquarters
San Diego, California
Growth & Insights
Headcount
6 month growth
↑ 10%1 year growth
↑ 23%2 year growth
↑ 104%Locations
San Diego Metropolitan Area, CA, USA
Experience Level
Entry
Junior
Mid
Senior
Expert
Desired Skills
Bash
Python
Jupyter
Data Science
NumPy
C/C++
Linux/Unix
CategoriesNew
AI & Machine Learning
Data & Analytics
Requirements
- Bachelors in physics, engineering, mathematics, etc
- You have a demonstrated record of working hard, being a trustworthy teammate, holding yourself and others to high standards, and being kind to others
- Good written and verbal communication skills
- Ability to drive projects in complex and changing situations
- Deep expertise in data science tools including Python scripting, Jupyter Notebooks, Bash scripting, Linux environment, NumPy, SciPy, Matplotlib, Scikit-learn
- Experience with C++
- Familiarity with deep learning fundamentals
- Experience analyzing and training neural networks
Responsibilities
- Work closely with Subject Matter Experts and key stakeholders to define success, develop metrics and processes, and evaluate agent and team performance in a variety of scenarios
- Identify metrics to quantify agent performance in multi-agent adversarial scenarios of incomplete or imperfect information
- Own metrics reporting and distribution, in person and through automated reporting tools
- Test ML/RL model for regressive behavior
- Use rigorous statistical methods to generate synthetic simulated datasets for training the ML/RL models
- Contribute to the development of stable and unified evaluation code and pipelines that interact with existing company reporting tools
Desired Qualifications
- Master's degree in data science, machine learning, mathematics, physics or computer science
- #LI-KR1