{"id":2494781,"url":"https://alion.io/job/gradera-ml-engineer","title":"ML Engineer","company":{"id":4377760,"name":"Gradera","domain":"gradera.ai","url":"https://alion.io/company/gradera","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"middle","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Hyderabad, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":19500,"max_usd":46000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":25},"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Apache Kafka","optional":false},{"name":"AutoGen","optional":false},{"name":"AWS","optional":false},{"name":"AWS Bedrock","optional":false},{"name":"Azure","optional":false},{"name":"Chroma","optional":false},{"name":"CI/CD","optional":false},{"name":"Claude","optional":false},{"name":"CrewAI","optional":false},{"name":"Docker","optional":false},{"name":"DSPy","optional":false},{"name":"Embeddings","optional":false},{"name":"FastAPI","optional":false},{"name":"GCP","optional":false},{"name":"Git","optional":false},{"name":"GitHub","optional":false},{"name":"GitHub Actions","optional":false},{"name":"GraphRAG","optional":false},{"name":"Hallucination","optional":false},{"name":"Hugging Face","optional":false},{"name":"Jira","optional":false},{"name":"Knowledge Graph","optional":false},{"name":"Kubernetes","optional":false},{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"Llama","optional":false},{"name":"LlamaIndex","optional":false},{"name":"LoRA","optional":false},{"name":"Machine Learning","optional":false},{"name":"Milvus","optional":false},{"name":"MLFlow","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"Multi-Agent Systems","optional":false},{"name":"Neo4j","optional":false},{"name":"OpenAI","optional":false},{"name":"OpenTelemetry","optional":false},{"name":"pgvector","optional":false},{"name":"Pinecone","optional":false},{"name":"PostgreSQL","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"QLoRA","optional":false},{"name":"Qwen","optional":false},{"name":"RAG","optional":false},{"name":"Redis","optional":false},{"name":"Rest API","optional":false},{"name":"Semantic Kernel","optional":false},{"name":"ServiceNow","optional":false},{"name":"Vertex AI","optional":false},{"name":"PEFT","optional":true}],"status":"live","first_seen_at":"2026-07-16T13:07:12Z","employer_posted_date":"2026-07-16","last_verified_at":"2026-10-14T20:08:24Z","board_verified":true,"closed_at":null,"days_open":90,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":90},"description":"About Gradera\nGradera 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.\nOverview\nAs 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.\nOur Core AI Stack\nPython, FastAPI\nGPT, Claude, Gemini, Llama, Qwen, Mistral\nLangGraph, AutoGen, CrewAI, Semantic Kernel\nLangChain, LlamaIndex, DSPy\nMCP (Model Context Protocol)\nVector Databases: pgvector, Pinecone, Milvus, Chroma\nNeo4j Knowledge Graphs & GraphRAG\nMLflow, Hugging Face, LoRA/QLoRA\nAzure AI Foundry, Azure OpenAI, AWS Bedrock, Vertex AI\nDocker, Kubernetes, GitHub Actions, OpenTelemetry\nRedis, Kafka, PostgreSQL\nKey Responsibilities\nDesign and develop enterprise-grade GenAI applications.\nBuild autonomous AI agents and multi-agent workflows.\nDevelop RAG pipelines using vector databases and knowledge graphs.\nIntegrate AI agents with enterprise applications such as GitHub, Jira, ServiceNow, databases, and REST APIs.\nEngineer prompts, memory, tools, and reasoning workflows for high-quality outcomes.\nEvaluate and optimize AI systems for latency, cost, accuracy, and hallucination reduction.\nDeploy scalable AI services using cloud-native technologies.\nBuild observability, tracing, and monitoring for AI applications.\nCollaborate with product, platform, and engineering teams to deliver production-ready solutions.\nStay current with the rapidly evolving AI ecosystem and contribute best practices.\nCore Qualifications\nBachelor's or Master's degree in Computer Science, AI, Machine Learning, or a related field.\n3+ years of software engineering experience with Python.\nHands-on experience with Large Language Models and Generative AI.\nStrong understanding of RAG, embeddings, vector search, and prompt engineering.\nExperience building APIs using FastAPI or similar frameworks.\nFamiliarity with cloud platforms such as Azure, AWS, or GCP.\nStrong software engineering fundamentals, testing, CI/CD, and Git.\nPreferred Qualifications\nExperience with Agentic AI and multi-agent architectures.\nExperience with LangGraph, AutoGen, CrewAI, or Semantic Kernel.\nExperience with Neo4j, GraphRAG, and knowledge graphs.\nExperience with MLflow and Hugging Face.\nFamiliarity with Kubernetes, Docker, Redis, Kafka, and cloud-native deployments.\nExperience with AI evaluation frameworks and observability.\nHighly Desirable\nExperience building enterprise AI copilots.\nExperience with coding agents or software engineering automation.\nOpen-source contributions in AI/ML.\nStrong communication and architectural design skills.\nPassion for experimenting with emerging AI 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