ML Engineer
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Before you apply
LocationHyderabad, India Office
Work modeon-site
Typefull-time
SeniorityMid
Experience3+ yrs
DepartmentAI Native - Delivery
Company size7+ people
First seenJul 5, 2026 · 4mo ago
Verified live1d ago
At a glanceSummarised by Seekless from the posting.
Bachelor's or Master's degree in Computer Science, AI, Machine Learning, or a related field
3+ years of software engineering experience with Python
Hands-on experience with Large Language Models and Generative AI
Strong understanding of RAG, embeddings, vector search, and prompt engineering
Experience building APIs using FastAPI or similar frameworks
Familiarity with cloud platforms such as Azure, AWS, or GCP
Strong software engineering fundamentals, testing, CI/CD, and Git
Experience with Agentic AI and multi-agent architectures
Experience with LangGraph, AutoGen, CrewAI, or Semantic Kernel
Experience with Neo4j, GraphRAG, and knowledge graphs
Experience with MLflow and Hugging Face
Familiarity with Kubernetes, Docker, Redis, Kafka, and cloud-native deployments
Experience with AI evaluation frameworks and observability
Experience building enterprise AI copilots
Experience with coding agents or software engineering automation
Open-source contributions in AI/ML
Strong communication and architectural design skills
Passion for experimenting with emerging AI technologies
Skills
Python
FastAPI
GPT
Claude
Gemini
Llama
Qwen
Mistral
LangGraph
AutoGen
CrewAI
Semantic Kernel
LangChain
LlamaIndex
DSPy
MCP
pgvector
Pinecone
Milvus
Chroma
Neo4j
GraphRAG
MLflow
Hugging Face
LoRA
QLoRA
Azure AI Foundry
Azure OpenAI
AWS Bedrock
Vertex AI
Docker
Kubernetes
GitHub Actions
OpenTelemetry
Redis
Kafka
PostgreSQL
Git
CI/CD
Jira
ServiceNow
REST APIs
About Gradera
Gradera defines a new category of enterprise transformation called Software-Orchestrated Services™ - where software orchestrates human expertise, digital workers, and enterprise systems to deliver governed outcomes at scale. As an AI Native Services firm, we help enterprises redesign how work gets done across operations, product, engineering, customer experience, data, and enterprise workflows to move beyond fragmented AI pilots and disconnected automation toward measurable business outcomes.
Overview
As an AI/ML Engineer specializing in Generative AI and Agentic AI, you will design, develop, and deploy intelligent AI applications powered by Large Language Models (LLMs). You will build autonomous agents, multi-agent systems, Retrieval-Augmented Generation (RAG) pipelines, evaluation frameworks, and production-ready AI services for enterprise customers.
Our Core AI Stack
• Python, FastAPI
• GPT, Claude, Gemini, Llama, Qwen, Mistral
• LangGraph, AutoGen, CrewAI, Semantic Kernel
• LangChain, LlamaIndex, DSPy
• MCP (Model Context Protocol)
• Vector Databases: pgvector, Pinecone, Milvus, Chroma
• Neo4j Knowledge Graphs & GraphRAG
• MLflow, Hugging Face, LoRA/QLoRA
• Azure AI Foundry, Azure OpenAI, AWS Bedrock, Vertex AI
• Docker, Kubernetes, GitHub Actions, OpenTelemetry
• Redis, Kafka, PostgreSQL
Key Responsibilities
• Design and develop enterprise-grade GenAI applications.
• Build autonomous AI agents and multi-agent workflows.
• Develop RAG pipelines using vector databases and knowledge graphs.
• Integrate AI agents with enterprise applications such as GitHub, Jira, ServiceNow, databases, and REST APIs.
• Engineer prompts, memory, tools, and reasoning workflows for high-quality outcomes.
• Evaluate and optimize AI systems for latency, cost, accuracy, and hallucination reduction.
• Deploy scalable AI services using cloud-native technologies.
• Build observability, tracing, and monitoring for AI applications.
• Collaborate with product, platform, and engineering teams to deliver production-ready solutions.
• Stay current with the rapidly evolving AI ecosystem and contribute best practices.
Core Qualifications
• Bachelor’s or Master’s degree in Computer Science, AI, Machine Learning, or a related field.
• 3+ years of software engineering experience with Python.
• Hands-on experience with Large Language Models and Generative AI.
• Strong understanding of RAG, embeddings, vector search, and prompt engineering.
• Experience building APIs using FastAPI or similar frameworks.
• Familiarity with cloud platforms such as Azure, AWS, or GCP.
• Strong software engineering fundamentals, testing, CI/CD, and Git.
Preferred Qualifications
• Experience with Agentic AI and multi-agent architectures.
• Experience with LangGraph, AutoGen, CrewAI, or Semantic Kernel.
• Experience with Neo4j, GraphRAG, and knowledge graphs.
• Experience with MLflow and Hugging Face.
• Familiarity with Kubernetes, Docker, Redis, Kafka, and cloud-native deployments.
• Experience with AI evaluation frameworks and observability.
Highly Desirable
• Experience building enterprise AI copilots.
• Experience with coding agents or software engineering automation.
• Open-source contributions in AI/ML.
• Strong communication and architectural design skills.
• Passion for experimenting with emerging AI technologies.