Junior AI Engineer - ML, RL & MLOps to Deploy

Nou Systems Inc; Lexington (MA); On-site; USD 70,000 - 125,000; Full time

Benefits offered by this job

Competitive Wages*

Medical, Rx, Dental & Vision Insurance

401(k) Retirement Plan

Employee Stock Ownership Plan (ESOP)

Tuition Reimbursement

Personal Time Off, Vacation, and Paid 

Lunch-n-Learns

Job summary

Noun Systems Inc’s Technical Solutions division is seeking a Junior AI Engineer to advance ML work from lab to real-world deployments, focusing on supervised learning, RL, and the MLOps foundations needed to operationalize them in Lexington, MA.

You will develop, train, and evaluate models, build training data pipelines, and collaborate with data scientists and other teams while communicating results through written and oral presentations.

Qualifications

• Bachelor’s degree in STEM field required.
• 1-3 years of hands-on deep learning with supervised/unsupervised/RL.
• Experience with PyTorch, TensorFlow or Jax.

Responsibilities

• Identify and design training datasets for model development.
• Implement and customize ML models based on open literature.
• Develop and maintain MLOps pipelines for training and deployment workflows.
• Develop, train, and analyze models for supervised and reinforcement learning.
• Visualize results and communicate findings in writing and verbally.
• Support multiple teams and collaborate across projects.
• Educate non-data-science teams on ML value and limitations.

Skills

Bachelor’s degree in STEM field

AI development experience (RL, XAI, Ls

1-3 years hands-on DL with PyTorch, TF

Strong written and verbal skills

Team player and self-directed

Statistical rigor

Experience with time series data, SL,

OpenAI Gymnasium & Ray RLlib

Education

Bachelor’s degree in STEM field

Tools

Python

PyTorch

TensorFlow

Jax

OpenAI Gymnasium

Ray RLlib

PyTorch Lightning

Optuna

MLflow

Git

Gitlab

CI/CD

Docker

Job description

Noun Systems Inc’s Technical Solutions division is seeking a Junior AI Engineer to advance ML work from lab to real-world deployments, focusing on supervised learning, RL, and the MLOps foundations needed to operationalize them in Lexington, MA.

You will develop, train, and evaluate models, build training data pipelines, and collaborate with data scientists and other teams while communicating results through written and oral presentations.