Description

You will lead the design and implementation of machine learning solutions.

This role is hybrid.

Responsibilities

• Design and implement ML models including regression, classification, clustering, time-series forecasting, and boosting algorithms.
• Develop and integrate Generative AI solutions using LLMs and foundation models, applying prompt engineering, LoRA, and PEFT.
• Build and optimize neural networks (CNNs, RNNs, LSTMs) for diverse data and use cases.
• Manage the end-to-end ML lifecycle, including model serialization, API deployment with FastAPI, and serverless infrastructure.
• Champion Databricks adoption for AutoML, pipeline automation, and scalable development.

Required Skills

• 5+ years of professional experience in ML engineering.
• Expert proficiency in Python.
• Experience deploying solutions using Docker and Kubernetes.
• Hands-on experience with cloud platforms, specifically AWS and Azure.
• Proficiency with deep learning frameworks, including PyTorch and CNNs.
• Strong capability in data processing and analysis using pandas, NumPy, and scikit-learn.
• Experience developing interfaces using Streamlit and front-end technologies (HTML, CSS, JavaScript).
• Familiarity with Git for version control.

Key Skills

Education

Any Gradute