Description

You will build and deploy scalable machine learning systems, lead LLM integration, and own the MLOps pipeline.

This role is on-site.

Responsibilities

• Design, develop, and deploy scalable ML models including regression, forecasting, and deep learning architectures.
• Lead LLM integration and fine-tuning using LoRA and PEFT to optimize performance and cost.
• Build and automate MLOps pipelines in Databricks using Docker, FastAPI, and serverless solutions.
• Develop user-facing AI tools, ensure seamless system integration, and maintain data quality.
• Mentor junior engineers and collaborate with cross-functional teams to drive AI adoption.

Required Skills

• 8+ years of experience in AI/ML engineering and software development.
• Advanced Python expertise with pandas, polars, NumPy, scikit-learn, and PyTorch.
• Strong 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.

Key Skills

Education

Bachelor's degree