Description

You will design, develop, and deploy scalable ML models across regression, forecasting, and deep learning architectures.

Responsibilities

• Lead LLM integration and fine-tuning using LoRA and PEFT, optimizing for performance and cost.
• Build and automate MLOps pipelines in Databricks using Docker, FastAPI, and serverless solutions.
• Develop user-facing AI tools and ensure seamless system integration.
• Maintain data quality, infrastructure reliability, and platform scalability.
• Mentor junior engineers and collaborate cross-functionally to drive AI adoption.

Required Skills

• 8+ years experience in AI/ML engineering and software development.
• Advanced Python expertise, including pandas, polars, NumPy, scikit-learn, and PyTorch.
• Hands-on experience with Generative AI, prompt engineering, and LLM fine-tuning.
• Experience evaluating model performance, latency, and scalability.
• Hands-on experience with AWS or Azure cloud platforms.
• Strong understanding of Git, Docker, CI/CD, and modern development workflows.
• Expertise in data cleaning, feature engineering, and visualization (e.g., Seaborn).
• Deep knowledge of Databricks, including AutoML and model lifecycle automation.
• Experience building APIs using FastAPI and deploying scalable AI solutions.

Key Skills

Education

Not specified