Description

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

This role is hybrid.

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 with existing infrastructure.
• Maintain data quality, platform scalability, and infrastructure reliability.
• Mentor junior engineers and collaborate with cross-functional teams to drive AI adoption.

Required Skills

• 11+ years of experience in AI/ML engineering and software development.
• Advanced Python expertise, including 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.
• Deep knowledge of Databricks, including AutoML and model lifecycle automation.
• Strong understanding of Git, Docker, CI/CD, and modern development workflows.
• Expertise in data cleaning, feature engineering, and visualization (e.g., Seaborn).

Preferred Skills

• Experience building APIs using FastAPI and deploying scalable AI solutions.
• Bachelor's degree in a relevant technical field.
• 3+ years tenure in current or previous roles.

Key Skills

Education

Bachelor's degree