AI/ML Engineer
- Smartavya Analytica
- 3 - 5 years
- Pune
- 29 days ago
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Job Description
Role Overview
Join our Pune AI Center of Excellence to drive software and product development in the AI space. As an AI/ML Engineer, youll build and ship core components of our AI productsowning end-to-end RAG pipelines, persona-driven fine-tuning, and scalable inference systems that power next-generation user experiences.
Key Responsibilities
- Model Fine-Tuning & Persona Design
- Adapt and fine-tune open-source large language models (LLMs) (e.g. CodeLlama, StarCoder) to specific product domains.
- Define and implement personas (tone, knowledge scope, guardrails) at inference time to align with product requirements.
- RAG Architecture & Vector Search
- Build retrieval-augmented generation systems: ingest documents, compute embeddings, and serve with FAISS, Pinecone, or ChromaDB.
- Design semantic chunking strategies and optimize context-window management for product scalability.
- Software Pipeline & Product Integration
- Develop production-grade Python data pipelines (ETL) for real-time vector indexing and updates.
- Containerize model services in Docker/Kubernetes and integrate into CI/CD workflows for rapid iteration.
- Inference Optimization & Monitoring
- Quantize and benchmark models for CPU/GPU efficiency; implement dynamic batching and caching to meet product SLAs.
- Instrument monitoring dashboards (Prometheus/Grafana) to track latency, throughput, error rates, and cost.
- Prompt Engineering & UX Evaluation
- Craft, test, and iterate prompts for chatbots, summarization, and content extraction within the product UI.
- Define and track evaluation metrics (ROUGE, BLEU, human feedback) to continuously improve the products AI outputs.
Must-Have Skills
- ML/AI Experience: 34 years in machine learning and generative AI, including 18 months on LLM-
based products.
- Programming & Frameworks: Python, PyTorch (or TensorFlow), Hugging Face Transformers.
- RAG & Embeddings: Hands-on with FAISS, Pinecone, or ChromaDB and semantic chunking.
- Fine-Tuning & Quantization: Experience with LoRA/QLoRA, 4-bit/8-bit quantization, and model context protocol (MCP).
- Prompt & Persona Engineering: Deep expertise in prompt-tuning and persona specification for product use cases.
- Deployment & Orchestration: Docker, Kubernetes fundamentals, CI/CD pipelines, and GPU setup.
Nice-to-Have
- Multi-modal AI combining text, images, or tabular data.
- Agentic AI systems with reasoning and planning loops.
- Knowledge-graph integration for enhanced retrieval.
- Cloud AI services (AWS SageMaker, GCP Vertex AI, or Azure Machine Learning)
Job Classification
Industry: IT Services & ConsultingFunctional Area / Department: Data Science & Analytics
Role Category: Data Science & Machine Learning
Role: Machine Learning Engineer
Employement Type: Full time
Contact Details:
Company: Smartavya AnalyticaLocation(s): Pune
Keyskills: AI/ML Engineering RAG Architecture AWS SageMaker GCP Vertex AI CI/CD Prometheus ChromaDB Azure Machine Learning ETL Grafana Python
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