Senior AI/ML Engineer

Keka Technologies Private Limited; Hyderabad; On-site; INR 1,000,000 - 1,500,000; Full time

Benefits offered by this job

Mentorship from senior architects

Innovation-driven environment

Continuous learning opportunities

Job summary

Keka Technologies Private Limited is seeking a skilled Senior AI/ML Engineer located in Hyderabad, India. The ideal candidate will have hands-on experience in building and deploying AI/ML applications, particularly with LLM frameworks. You will design scalable AI solutions and collaborate with cross-functional teams to innovate in AI technologies.

This role requires proficiency in Python, knowledge of RAG systems, and experience with vector databases. We offer an opportunity to work on cutting-edge technologies, mentorship from senior architects, and a collaborative culture.

Qualifications

• 2–5 years of hands-on experience in AI/ML or LLM engineering.
• Previous project or product development experience in NLP/LLM highly preferred.

Responsibilities

• Design, develop, and deploy end-to-end LLM-based applications and automation workflows.
• Implement RAG systems using vector databases.
• Integrate ML/LLM workflows using microservices and APIs.

Skills

Python

LLMs (OpenAI, Llama, etc.)

LangChain, LlamaIndex, or Hugging Face

RAG pipelines

Vector databases (Pinecone, FAISS, etc.)

REST APIs

Git, Docker, CI/CD

Education

Bachelor’s or Master’s degree in Computer Science, AI/ML, Data Science, or related field

Tools

FastAPI

Flask

AWS

Azure

GCP

Job description

Employment Type: Full-Time

Experience Required: 2+–5 Years

About the Role

We are looking for a skilled Senior AI/ML Engineer with hands‑on experience in building, deploying, and optimizing AI/ML and LLM‑based applications. The ideal candidate should have strong Python expertise, experience with LLM frameworks, and the ability to design scalable AI solutions for enterprise use cases. You will collaborate with cross‑functional teams to build agentic AI workflows, RAG pipelines, vector search systems, and production‑grade AI applications.

Key Responsibilities

• Design, develop, and deploy end‑to‑end LLM‑based applications, conversational agents, and automation workflows.
• Build prompt engineering strategies, evaluation workflows, and structured prompting for enterprise use cases.
• Implement RAG (Retrieval Augmented Generation) systems using vector databases such as Pinecone, FAISS, or ChromaDB.
• Fine‑tune, evaluate, and optimize models (open‑source or API‑based LLMs).
• Build and deploy ML models for classification, NLP, prediction, and document processing.
• Work on data preprocessing, feature engineering, and model optimization.
• Integrate ML/LLM workflows using microservices, APIs, webhooks, and automation pipelines.

Architecture & Integrations

• Work with Python frameworks (FastAPI/Flask) to build scalable model‑serving endpoints.
• Integrate AI systems with enterprise platforms, databases, and internal applications.
• Contribute to architecture decisions for LLM apps, agentic systems, and AI microservices.
• Collaborate with data scientists, product owners, and solution architects to deliver AI‑powered features.
• Review code, mentor junior engineers, and set technical standards for AI development.
• Prepare documentation, reusable components, and best practices for AI implementation.

Required Skills

Core Skills

• Strong proficiency in Python (Pandas, NumPy, FastAPI/Flask, Async programming preferred).
• Hands‑on experience with LLMs (OpenAI, Llama, Mistral, Claude, Qwen, etc.).
• Experience with LangChain, LlamaIndex, or Hugging Face.
• Strong understanding of RAG pipelines, embeddings, and vector search.
• Practical experience with vector databases: Pinecone, FAISS, Weaviate, or ChromaDB.
• Knowledge of REST APIs, JSON integrations, token‑based authentication.
• Experience with Git, Docker, CI/CD workflows.

ML & Data Skills

• Experience with NLP, classical ML, text preprocessing, and supervised learning.
• Ability to evaluate model performance and optimize latency & accuracy.
• Understanding of data pipelines and ETL workflows.
• Experience with at least one cloud platform (AWS/Azure/GCP).
• Familiarity with Kubernetes, model deployment, or container orchestration (nice to have).

Nice‑to‑Have Skills

• Experience with agentic AI frameworks (AutoGen, CrewAI, LangGraph, Swarm, etc.).
• Exposure to MLOps tools (MLflow, Airflow, Weights & Biases).
• Knowledge of front‑end AI app integration (Streamlit, Gradio, or React).
• Understanding of AI security, governance, and responsible AI principles.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, AI/ML, Data Science, or related field.
• 2–5 years of hands‑on experience in AI/ML or LLM engineering.
• Previous project or product development experience in NLP/LLM highly preferred.

What We Offer

• Opportunity to work on cutting‑edge AI/LLM technologies.
• Exposure to enterprise‑grade AI architectures, RAG systems, and agentic workflows.
• Mentorship from senior architects and a collaborative engineering culture.
• Innovation‑driven environment with continuous learning opportunities.