Design and implement AI-powered systems using a mix of classical ML techniques and modern LLM-based approaches, frequently leveraging managed Azure AI/ML services as building blocks.
Apply a range of techniques—from classical ML to LLM-based approaches (RAG, prompt engineering, fine-tuning, semantic search)—with a strong focus on reliability, performance, and maintainability
Collaborate closely with product managers and designers to deliver high-quality, customer-focused features.
Write clean, testable, well-documented code and contribute to shared engineering standards.
Author clear design docs that explain system behavior, tradeoffs, and long-term implications.
Debug and resolve production issues across application code, data, and ML components.
Evaluate ML systems using metrics and real-world signals, and iteratively improve them.
Participate fully in an Agile development lifecycle, contributing to planning, reviews, and retrospectives.
Stay current on ML and software engineering best practices, adopting new tools thoughtfully and pragmatically.

Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related field—or equivalent practical experience.
4+ years of professional software engineering experience, with meaningful exposure to machine learning in production systems.
Strong ability to design and build scalable, production-quality software.
Excellent programming skills in Python
Hands-on experience applying machine learning models in real systems, including model integration, inference, and evaluation.
Familiarity with ML frameworks such as PyTorch, TensorFlow, Hugging Face, or scikit-learn.
Experience or interest in search, information retrieval, ranking, or recommendation systems.
Product mindset: you care about user impact, not just technical elegance.
Strong communication skills and comfort working cross-functionally.
Preferred: Experience with Node.JS and TypeScript
Preferred: Experience working on SaaS web applications
Preferred: Basic understanding of distributed systems
Preferred: Bonus: Docker, Kubernetes experience, AWS/Azure cloud infrastructure

Senior Software Engineer II – Machine Learning

Key skills