Machine Learning/Applied AI Engineer, QuantSpark

• SC Eligibility Required
• You have 2–5 years of experience in ML Engineering, Data Science, or Applied AI
• Experience building and training models using scikit‑learn or similar ML frameworks
• Understanding of model evaluation metrics and validation best practices
• Hands-on experience developing on CPU/GPU environments (local or cloud)

Desirable

• Reporting to: Engineering Manager
• Develop and Train ML Models: Design lightweight but production-minded machine learning pipelines for classification, regression, or prediction use cases
• Operationalize Models: Package and deploy models as REST APIs or microservices (FastAPI, Flask, or equivalent)
• Leverage Applied AI & Foundation Models: Integrate and fine-tune pretrained models (e.g., from Hugging Face or similar libraries) for text, tabular, or simple image tasks
• Ensure Reproducibility & Quality: Track experiments, manage artifacts (models, metrics, parameters), and use ML best practices for versioning and reproducible results
• Collaborate Across Disciplines: Work closely with data engineers and software developers to build scalable, maintainable end‑to‑end ML applications
• Monitor and Improve Deployed Models: Collect performance metrics, identify drift, and support model lifecycle operations in partnership with the MLOps team

• 1. 30 mins intro call with talent team
• 2. short take home test
• 3. 75 mins in-person Tech interview
• 4. 1 hour culture interview - virtual