AI Engineer

About us and the role

At DS Stream, we help global enterprises move beyond AI pilots and build AI at scale. We deliver enterprise-grade solutions across Data Engineering, AI Engineering, Data Science, Generative AI, Agentic AI and AI Platform Engineering.

We work with organizations across CPG, Retail, Manufacturing, Telecom, Financial Services and Healthcare, helping them build AI Factories, modern data platforms and production-ready AI solutions.

We are looking for experienced Backend/AI Engineers to join our growing Team in India.

Role Overview

As an AI Engineer at DS Stream, you will bridge the gap between traditional data science and modern AI applications. Leveraging your strong foundation in machine learning, statistics, and data engineering, you will design, train, and deploy ML models while integrating GenAI capabilities into existing data pipelines. You will be responsible for the full ML lifecycle - from experimentation and model development to production deployment and monitoring - ensuring our AI solutions are robust, scalable, and aligned with business objectives.

Key Responsibilities

• Design and operate AI-driven pipelines that automatically ingest, analyze, and classify operational incidents and tickets.
• Leverage LLMs with structured prompt logic and few-shot prompting (using historically similar tickets) to deliver consistent, scalable triage replacing manual classification and accelerating resolution.
• Collaborate closely with cross-functional teams and contribute to scaling AI capabilities across projects.
• Drive tasks independently with minimal supervision.

Required Skills

• 4+ years of hands-on experience in GenAI/Machine Learning/Data Science with strong background in Python.
• Proficiency in deep learning frameworks (PyTorch or Tensorflow preferred).
• Experience with SQL and relational/non-relational/vector databases
• Solid understanding of ML fundamentals (supervised/unsupervised learning, model evaluation, feature engineering).
• Practical experience with LLM orchestration frameworks (LangChain, LangGraph or LlamaIndex).
• Understanding of GenAI integration patterns and LLM APIs.
• Experience building and deploying ML models to production.
• Hands-on exposure to at least one cloud ML platform (AWS SageMaker, Azure ML, Google Vertex AI, Databricks).
• Familiarity with software engineering best practices (GitHub, CI/CD, testing, code review).
• Understanding of workflow orchestration (Airflow, Kubeflow).

Nice to Have

• Strong foundation in statistics and mathematics (linear algebra, probability, optimization).
• Experience with Spark (PySpark, Databricks).
• Open-source contributions to AI or data projects.
• Experience working in Agile/Scrum environments.