Tech Stack

Description

You will design, build, and deploy practical AI-powered solutions, applying modern ML and GenAI techniques in production systems. Working with cross-functional teams, you'll turn ambiguous problems into scalable, reliable capabilities while balancing technical rigor with real-world constraints.

Requirements

• Strong foundation in ML concepts (model selection, training, validation, evaluation)
• Experience building and deploying ML models in production
• Proficiency in Python and ML libraries (PyTorch, TensorFlow, scikit-learn)
• Experience with LLMs, embeddings, and prompt-driven systems
• Familiarity with data processing tools (Pandas, SQL, Spark) and software engineering best practices

Responsibilities

• Design, develop, and deploy ML/AI features into production systems
• Apply supervised, unsupervised, and deep learning techniques to structured and unstructured data
• Build and evaluate models for classification, ranking, prediction, NLP, or anomaly detection
• Develop and integrate GenAI solutions (e.g., LLM workflows, RAG, agents)
• Translate business needs into ML problem statements, metrics, and experiments