Data Scientist, ML Evaluation and Autonomy

Shieldai in San Diego Metro Area

Introduction to Shield AI
Shield AI’s mission is to protect service members and civilians with intelligent systems. Shield AI is a fast growing, venture-backed defense-technology company built around a team of proven executives, distinguished warfighters, and world-class AI engineers. Since 2018, Shield AI’s products and people have supported operations around the world with the US Department of Defense and our allies.


At Shield you’ll be part of an elite team that uses machine learning to develop the best AI pilot. Help us build world-class infrastructure for autonomous behavior, scene understanding and embedded AI. We develop large pipelines for training, evaluating and productizing machine learning models. As a member of our machine learning team you will work with colleagues to evaluate and improve new models in the areas of reinforcement learning, attention mechanisms and object detection and tracking. You will evaluate workflows to evaluate models and to ensure that they operate at peak performance onboard the different autonomous platform.



Salary Range:  Base + Bonus + Benefits + Equity (if applicable)
Actual compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. Information on the benefits offered is here. All offers are contingent on a cleared background check.

Location guidelines-
Onsite = 5 days/week
Hybrid = Several days in the office
Remote = Remote but able to come to the office as requested for business needs

If you're interested in being part of our team, apply now!

Shield AI is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please let us know.
To conform to U.S. Government regulations, applicant must be a U.S. citizen, lawful permanent resident of the U.S., protected individual as defined by 8 U.S.C. 1324b(a)(3), or eligible to obtain the required authorizations from the U.S. Department of State.
    • 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
    • Rigorous evaluation of ML and RL models in simulated environments
    • Create efficient ways to represent and learn in multi-agent 3D environments
    • Maximize the efficiency of simulator-based training
    • Strive to improve end-to-end learning pipelines
    • Identify efficient approaches to transfer ML models to real-world platforms
    • Drive towards scale by leveraging low-fi/high-fi efficient training and other forms of agent pre-training
    • 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
    • Master's degree in data science, machine learning, mathematics, physics or computer science
      • #LI-KR1
Apply