
Generative AI Engineer
3 weeks ago
Job Title : Generative AI / Machine Learning Engineer
Location : Pune, India
Experience Required : 7+ years
Notice Period : Immediate / Serving Notice
About the Role :
Model Development & Deployment :
- Design, train, and deploy supervised and unsupervised ML models for large-scale
applications.
- Build and optimize Generative AI pipelines (LLMs, RAG architectures, AI Agents).
- Implement scalable data preprocessing, feature engineering, and inference AI Applications :
- Architect and implement RAG pipelines combining vector databases (e.g., Pinecone, Weaviate, FAISS) and LLMs for enterprise knowledge retrieval.
- Build and deploy AI Agents for automation, decision support, and conversational & Integration :
- Write clean, production-grade Python code following best practices.
- Integrate ML/GenAI solutions into existing enterprise systems, APIs, and applications.- Collaborate with data engineers, product managers, and DevOps teams to deliver scalable AI & Cloud :
- Use MLOps frameworks (MLflow, Kubeflow, Vertex AI, SageMaker, Azure ML) for experiment tracking, CI/CD, and deployment.
- Deploy models on cloud platforms (AWS/GCP/Azure) with containerized workflows (Docker, Kubernetes).- Optimize models for latency, scalability, and cost Skills & Qualifications Expertise :
- Strong proficiency in Python and ML libraries : TensorFlow, PyTorch, scikit-learn, Hugging Face Transformers.
- Deep understanding of ML algorithms (supervised, unsupervised, deep learning).
- Proven hands-on experience in Generative AI frameworks (LangChain, LlamaIndex, Haystack, RAG pipelines, AI Agent Knowledge :
- Experience with vector databases (Pinecone, FAISS, Weaviate, Milvus).
- Familiarity with LLM fine-tuning, embeddings, and prompt optimization.- Strong foundation in data preprocessing, feature engineering, and model Skills :
- MLOps exposure (CI/CD pipelines, model monitoring, drift detection).
- Cloud experience with AWS (SageMaker, Bedrock), GCP (Vertex AI), Azure ML.
- Familiarity with API design, microservices architecture, and distributed :
- Bachelors or Masters in Computer Science, Data Science, AI/ML, or related fields.
- Certifications in AI/ML, Cloud, or Generative AI (preferred but not mandatory). (ref:hirist.tech)-
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