Junior AI Engineer

Nou Systems Inc•Huntsville, AL

9h•$70,000 - $125,000

About The Position

nou Systems, Inc. (nSI) is seeking an AI Engineer to join their Technical Solutions division. This role is part of a rapidly growing technology company operating in the defense, cybersecurity, test range modernization, biotechnology, and space control markets. The AI Engineer will be part of a team designing machine learning solutions from the lab to the field. This is a junior-level position focused on developing, training, and analyzing machine learning models for supervised and reinforcement learning. The role involves working on a mix of projects, collaborating with other data scientists, and educating non-data-science teams on machine learning. The position requires supporting multiple teams and effective teamwork.

Requirements

Bachelor’s degree in a STEM field.
Academic, internship, or professional experience with AI development (RL, XAI, LLM)
1-3 years of hands-on experience with deep learning models (supervised, unsupervised, and reinforcement learning) using PyTorch, Tensorflow, or Jax.
Must possess or can obtain an active Secret clearance.
Software development fundamentals in Python.
Great written and verbal communication skills.
Team player and glad to work on a variety of machine learning projects as opportunity presents.

Nice To Haves

Ability to write clean deep learning code in Python.
Ability and mindset to approach problems with statistical rigor.
Strong intellectual curiosity.
Comfort with self-direction.
Experience with time series data, satellite imagery, and graph neural networks.
Experience with RL development using OpenAI Gymnasium and Ray RLlib.
Experience with RL algorithms, including Q-Learning and Actor-Critic methods.
Experience with MLOps tools (PyTorch Lightning, Optuna, MLflow, etc.).
Experience with DevOps tools (Git, Gitlab, CI/CD, Remote Computing, Docker).

Responsibilities

Develop, train, and analyze machine learning models for supervised learning and reinforcement learning.
Work on a mix of projects, some of which will include other data scientists, others of which will require you to help educate non-data-science teams on the value and limitations of machine learning solutions.
Help identify and design training data sets.
Implement and customize ML models from open literature.
Develop MLOps pipelines.
Visualize and communicate your results in written documents and oral presentations.
Support multiple teams and must be able to work effectively with other teammates.