{"id":160162,"url":"https://alion.io/job/sydiai-ai-genai-ml-engineer","title":"AI / GenAI / ML Engineer","company":{"id":60312,"name":"SYDIAI","domain":"sydiai.com","url":"https://alion.io/company/sydiai","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":null,"work_mode":"hybrid","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":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Anthropic","optional":false},{"name":"CI/CD","optional":false},{"name":"Docker","optional":false},{"name":"Embeddings","optional":false},{"name":"FastAPI","optional":false},{"name":"Fine-tuning","optional":false},{"name":"Function Calling","optional":false},{"name":"Git","optional":false},{"name":"Hallucination","optional":false},{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"LlamaIndex","optional":false},{"name":"LLM","optional":false},{"name":"LoRA","optional":false},{"name":"Machine Learning","optional":false},{"name":"Mistral","optional":false},{"name":"OpenAI","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"QLoRA","optional":false},{"name":"RAG","optional":false},{"name":"Reranking","optional":false},{"name":"Azure","optional":true},{"name":"Computer Vision","optional":true},{"name":"Databricks","optional":true},{"name":"FAISS","optional":true},{"name":"Gemini","optional":true},{"name":"Hugging Face","optional":true},{"name":"Kubernetes","optional":true},{"name":"Llama","optional":true},{"name":"LLM Guardrails","optional":true},{"name":"LLMOps","optional":true},{"name":"Milvus","optional":true},{"name":"MLFlow","optional":true},{"name":"Model Context Protocol","optional":true},{"name":"Multimodal AI","optional":true},{"name":"PEFT","optional":true},{"name":"Pinecone","optional":true},{"name":"PyTorch","optional":true},{"name":"Weaviate","optional":true}],"status":"live","first_seen_at":"2026-08-29T04:31:22Z","employer_posted_date":null,"last_verified_at":"2026-08-29T04:31:22Z","board_verified":false,"closed_at":null,"days_open":53,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":53},"description":"We are looking for an AI / GenAI / ML Engineer to design and build production-grade AI solutions using Generative AI, LLMs, Machine Learning, RAG, and AI Agents. The ideal candidate should combine strong software engineering skills with practical experience in developing, evaluating, deploying, and scaling AI applications.\nResponsibilities:\nDesign and develop production-ready GenAI and ML applications.\nBuild LLM-powered applications using models from providers such as OpenAI, Anthropic, Google, Meta, Mistral, or open-source models.\nDevelop RAG pipelines including document ingestion, chunking, embeddings, retrieval, reranking,\nand response generation.\nBuild intelligent AI agents and agentic workflows using frameworks such as LangChain, LangGraph, or equivalent technologies.\nDevelop prompt engineering, structured generation, tool calling, and function-calling solutions.\nEvaluate LLM/AI systems for accuracy, relevance, hallucination, latency, cost, and safety.\nImplement model fine-tuning techniques such as LoRA / QLoRA where appropriate.\nIntegrate AI models with enterprise APIs, databases, search systems, and business applications.\nDevelop scalable AI services and APIs using Python and FastAPI or equivalent frameworks.\nWork with Data Scientists and Data Engineers to integrate ML models and enterprise data.\nDeploy and operate AI solutions using cloud and container technologies.\nImplement observability, evaluation, monitoring, security, and responsible AI practices.\nRequirements:\nStrong Python and software engineering fundamentals.\nHands-on experience with LLMs and Generative AI.\nPractical knowledge of RAG, embeddings, vector databases, prompt engineering, and LLM evaluation.\nExperience with LangChain, LangGraph, LlamaIndex, or equivalent frameworks.\nUnderstanding of machine learning and deep learning fundamentals.\nExperience building APIs and integrating AI models into applications.\nKnowledge of Git, Docker, CI/CD, and cloud deployment.\nStrong understanding of AI application architecture and production engineering.\nStrong engineering fundamentals, hands-on AI implementation experience, experimentation mindset, and the ability to take an AI idea from prototype to production scale.\nGood to Have:\nExperience with AI Agents, multi-agent systems, tool calling, MCP, or agent orchestration.\nExperience with OpenAI / Azure OpenAI, Anthropic, Gemini, Llama, Mistral or similar models.\nExperience with LoRA, QLoRA, Hugging Face, and PyTorch.\nKnowledge of vector databases such as Pinecone, FAISS, Weaviate, or Milvus.\nExperience with MLflow, Azure ML, Databricks, and Kubernetes.\nExperience with LLMOps, model evaluation, guardrails, observability, and AI security.\nKnowledge of multimodal AI, speech AI, or computer vision is an 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shot","p_open":0.4,"p_active":0.418,"p_room":0.35,"age_days":52,"expected_fill_days":23,"reasons":["seen:52","win:tail"],"computed_at":"2026-10-20T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/sydiai-ai-genai-ml-engineer","json_url":"https://alion.io/job/sydiai-ai-genai-ml-engineer.json","meta":{"generated_at":"2026-10-21T05:39:42Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per 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