AI/ML Engineer
1 week ago
We are seeking a highly skilled and self-driven Machine Learning Engineer with 3–4
years of hands-on experience in Generative AI, LLM-based systems, prompt
engineering, vector databases, and agentic AI automation. The ideal candidate will
have a strong background in Python, knowledge retrieval systems, and deploying AI-
powered automation for tasks involving documents, communication, and workflows.
You will work at the forefront of AI-driven automation, helping us build intelligent
systems that interact with unstructured data, automate decision-making, and deliver
real-time insights using cutting-edge Gen AI tools and frameworks.
Key Responsibilities:
- Design, build, and deploy AI agents and agentic workflows for document
understanding, communication automation, and knowledge retrieval.
- Develop, fine-tune, and optimize LLM prompts, RAG pipelines, and memory-
based systems for contextual AI.
- Integrate and manage vector databases (e.g., Pinecone, Weaviate, FAISS) for
scalable semantic search and retrieval.
- Develop and maintain Python-based pipelines, APIs, and microservices for AI
automation tasks.
- Work with structured and unstructured data, including PDFs, emails, and text
data, to generate actionable insights using Gen AI.
- Collaborate with product, data, and engineering teams to design scalable AI
solutions.
- Evaluate and integrate external LLM APIs (e.g., OpenAI, Anthropic, Mistral, etc.)
and open-source LLMs (e.g., Llama, Mistral, etc.).
- Monitor and optimize AI model performance, latency, and cost. Stay updated on advancements in agentic AI, LLM frameworks, vector
search, and Gen AI tools; recommend adoption where appropriate.
Required Skills & Qualifications:
- 3–4 years of experience in Machine Learning / AI engineering, with a focus on
Gen AI and LLMs.
- Proficiency in Python, including frameworks like LangChain, LlamaIndex,
FastAPI, Pydantic, etc.
- Strong experience in prompt engineering and LLM integration (e.g., OpenAI,
Claude, Mistral).
- Hands-on experience with vector databases (e.g., Pinecone, Weaviate, FAISS,
Chroma).
- Experience building retrieval-augmented generation (RAG) systems.
- Familiarity with agentic AI frameworks (e.g., LangGraph, AutoGen, CrewAI,
AutogenStudio).
- Strong understanding of document processing, including OCR, PDF parsing,
text embeddings, and summarization.
- Comfortable working with APIs, webhooks, and automation of communication
workflows (e.g., email, chat, scheduling).
- Solid understanding of data structures, algorithms, and performance
optimization.
- Excellent problem-solving skills, ownership mindset, and ability to work in a fast-
paced environment.
Nice to Have:
- Experience with LLM fine-tuning or model distillation.
- Knowledge of Docker, Kubernetes, and cloud services (e.g., AWS, GCP, Azure).
- Familiarity with open-source LLMs (e.g., Llama, Mistral, Zephyr) and
deployment using vLLM, Ollama, or Modal.
- Exposure to PostgreSQL, Redis, and task queues like Celery or RQ.
- Experience with AI observability tools (e.g., LangSmith, Helicone, Phoenix) is a
plus.Soft Skills:
- Strong written and verbal communication skills.
- Ability to manage ambiguity and drive projects independently.
- Passion for staying updated with AI research and applying it to real-world use
cases.
Job Type: Full-time
Pay: Up to ₹1,900,000.00 per month
Benefits:
- Health insurance
Work Location: In person
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