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Gurugram · On-site · 1-4 Yrs · Sep 28
1 to 50 Employees · New Delhi, India
1 open role0 posted in 7d1 in 30d
Hiring: Engineering
Job description
Overview
We are seeking an experienced GenAI / AI-ML Engineer to design, develop, and deploy scalable Generative AI and Machine Learning solutions.
Responsibilities
- GenAI & Agentic Systems: Develop LLM-powered applications utilizing prompt engineering, AI agents, and multi-agent workflows (LangChain, LangGraph).
- RAG Pipelines: Build, optimize, and evaluate Retrieval-Augmented Generation (RAG) pipelines using modern vector databases and frameworks like RAGAS.
- Backend Integration: Write robust Python code and build high-performance REST APIs using FastAPI to support AI models in production.
- ML/DL Engineering: Design end-to-end data preprocessing, feature engineering, fine-tuning, and model evaluation pipelines using Scikit-learn, PyTorch, TensorFlow, and Keras.
- Cloud & DevOps: Containerize applications using Docker and deploy scalable models on AWS (SageMaker, Bedrock, EC2, S3) with CI/CD integration.
- Collaboration: Partner with Data Engineering, DevOps, and Product teams to ensure reliability, security, and performance of production environments.
Qualifications
- Programming & Backend: Solid proficiency in Python, SQL, and framework expertise with FastAPI.
- GenAI Stack: Hands-on experience with OpenAI APIs, Hugging Face, LangChain, LangGraph, LangSmith, and vector databases (Pinecone, FAISS).
- Evaluation Metrics: Practical experience with evaluation frameworks (RAGAS, BLEU, ROUGE) and semantic search architectures.
- Cloud Infrastructure: Solid background with AWS services (EC2, S3, SageMaker, Bedrock), Docker, and Git.
- Availability: Immediate joiners or candidates currently serving their notice period based in Noida/NCR.
- Are you based in Noida/NCR and available as an immediate joiner (or currently serving your notice period)
- Do you have at least 1 year of hands-on experience building GenAI applications using LangChain, LangGraph, or multi-agent workflows
- Which vector databases and RAG evaluation tools have you used in production (e.g., Pinecone, FAISS, RAGAS)
- How many years of experience do you have building production REST APIs using FastAPI in Python
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Job application FAQ
Last updated 29 September 2026
- How do I apply for GenAI / AI-ML Engineer( Machine Learning / Deep Learning) (Gurugram) at Tasknera?
- Open this job on Feedback AI and sign up free (or sign in). You can apply from the job detail page; match scores and skill gaps appear when your profile is complete. Tasknera may attach structured assessments to interview rounds after you apply.
- Does Feedback AI show a match score for this GenAI / AI-ML Engineer( Machine Learning / Deep Learning) (Gurugram) role?
- Yes after you add a resume or skills. Match score ranks this role against your profile — skills met, gaps, level, and location — so you prioritise applications where fit is strongest.
- Is GenAI / AI-ML Engineer( Machine Learning / Deep Learning) (Gurugram) remote or on-site in Gurugram, Haryana?
- This listing is marked on_site with location Gurugram, Haryana. Confirm details on the job description before applying.
- What skills matter for this GenAI / AI-ML Engineer( Machine Learning / Deep Learning) (Gurugram) role at Tasknera?
- This is a mid-level GenAI / AI-ML Engineer( Machine Learning / Deep Learning) (Gurugram) role. Key skills include skills listed in the job description. Feedback AI highlights matched vs missing skills on your profile after signup.