Description
You will build, train, and deploy machine learning models for AI applications.
Responsibilities
- Develop, train, and fine-tune machine learning models for AI/ML applications.
- Design and implement data pipelines for processing, model training, and inference.
- Deploy models using MLOps and integrate them with cloud infrastructure.
- Research and implement ML and AI techniques to improve model performance.
- Collaborate with product managers and designers to conceptualize AI-driven features.
Required Skills
- 12+ years of experience in machine learning or related fields.
- Proficiency in Python and ML frameworks including Scikit-learn, XGBoost, TensorFlow, and PyTorch.
- Experience with SQL and ETL data pipelines, data processing, and feature engineering.
- Hands-on experience with Docker and container-based deployments.
- Strong understanding of Supervised Learning, Unsupervised Learning, Deep Learning, and Reinforcement Learning.
- Knowledge of at least one cloud platform (AWS, Azure, or GCP), with a preference for Azure.
- Understanding of various statistical models.
- Bachelor's degree.
Preferred Skills
- Exposure to LLMs and foundation models such as OpenAI, Hugging Face, or Mistral.