Junior Machine Learning Developer

What You’ll Do

- Build and tune supervised and unsupervised models using Python, scikit-learn, TensorFlow, or PyTorch.  

- Collect, label, augment, and version datasets with MLflow and DVC.  

- Write modular, testable code; document experiments in Jupyter notebooks.  

- Debug numerical issues, handle data drift, and raise model accuracy through hyperparameter optimization.  

- Package models as RESTful APIs with FastAPI, Docker, and Kubernetes.  

- Benchmark runtime and memory footprints, proposing GPU or CPU optimizations.  

- Collaborate with product, DevOps, and analytics teams to align ML outputs with business KPIs.  

- Keep abreast of research papers; translate findings into production POCs.  

- Participate in code reviews, pair programming, and weekly learning sessions.  

What You Bring

- Bachelor’s degree in Computer Science, Data Science, or related STEM field.  

- 0-2 years of hands-on experience building machine learning projects in academic or industry settings.  

- Proficiency in Python 3.x and core libraries (NumPy, pandas, matplotlib).  

- Working knowledge of scikit-learn plus either TensorFlow or PyTorch.  

- Familiarity with Git, Unix command line, and CI/CD workflows.  

- Solid grasp of statistics, linear algebra, and probability.  

- Ability to communicate complex ideas to technical and non-technical partners.  

- Growth mindset, autonomy, and relentless curiosity.  

- Eligibility to work in the United States.