Design, develop, and optimize machine learning pipelines using GCP services.
Build scalable data processing workflows for training and deploying ML models.
Develop reusable and efficient Python-based modules and components.
Implement data ingestion, transformation, and feature engineering pipelines.
Collaborate with data scientists and product teams to deploy ML models into production.
Work on NLP, OCR, and Generative AI use cases.
Optimize model performance, scalability, and reliability.
Integrate third-party APIs (OpenAI, Gemini, Anthropic) into ML workflows.
Ensure best practices in code quality, testing, and documentation.
Generative AI & Agentic Frameworks
Strong exposure to:
LangChain, LangGraph, LlamaIndex
Vector Databases: FAISS / Pinecone
LLM APIs: OpenAI, Anthropic, Google Gemini
Building AI agents using LangGraph
Cloud & Data Engineering
Hands-on experience with Google Cloud Platform (GCP) services
Experience in building data pipelines and ML pipelines
Understanding of distributed systems and scalable architecture
Preferred Skills:
Experience with CI/CD pipelines for ML workflows
Knowledge of Docker / Kubernetes
Familiarity with real-time data processing
Experience in production deployment of ML models
Soft Skills:
Robust problem-solving and analytical thinking
Good communication and collaboration skills
Ability to work in Agile environments
Nice to Have:
Experience in Agentic AI systems and LLM-based applications
📌 Data Engineer, Ahmedabad (Gurugram)
🏢 Altraize
📍 Gurugram
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