Junior AI Engineer

A fast-growing U.S. technology group creates data-driven solutions for Fortune 500 clients and high-growth startups alike. Our engineers collaborate across time zones, share knowledge openly, and ship production-ready code every sprint—no bureaucracy, just results.

What You’ll Do  

- Craft clean Python code that translates research ideas into deployable AI services.  

- Train, validate, and benchmark deep-learning models in TensorFlow or PyTorch.  

- Debug performance bottlenecks—profiling memory, latency, and accuracy metrics.  

- Optimize pipelines through feature engineering, hyper-parameter tuning, and vectorized computation.  

- Document experiments, model decisions, and reproducibility steps in clear technical language.  

- Pair with senior data scientists during code reviews and architecture discussions.  

- Collaborate with DevOps to containerize models for scalable cloud deployment.  

- Monitor live systems, analyze anomalies, and propose iterative improvements.  

Must-Have Skills  

- Solid grasp of Python syntax, data structures, and virtual environments.  

- Coursework or projects in machine learning, statistics, or linear algebra.  

- Familiarity with TensorFlow or PyTorch APIs for model definition and training loops.  

- Ability to read academic papers and implement algorithms from scratch.  

- Confident with Git workflows and unit testing.  

- Strong analytical thinking, written communication, and curiosity.  

Nice-to-Have Extras  

- Experience with AWS SageMaker, GCP Vertex AI, or Azure ML.  

- Exposure to RESTful API design, FastAPI, or Flask.  

- Knowledge of MLOps concepts such as CI/CD, model registry, and feature stores.  

- Participation in Kaggle competitions or open-source contributions.