{"id":3530788,"url":"https://alion.io/job/quantiphi-senior-machine-learning-engineer-7","title":"Senior Machine Learning Engineer","company":{"id":6155,"name":"Quantiphi","domain":"quantiphi.com","url":"https://alion.io/company/quantiphi","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"services","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"B","score":72,"open_postings":65,"ghost_share":0.462,"stale_share":0,"repost_share":0.015,"time_to_fill_p50_days":34,"computed_at":"2026-10-31T05:58:55Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India","Thiruvananthapuram, India","Mumbai, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":23000,"max_usd":47000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":41},"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Amazon CloudWatch","optional":false},{"name":"Amazon S3","optional":false},{"name":"Amazon SageMaker","optional":false},{"name":"API Gateway","optional":false},{"name":"AWS","optional":false},{"name":"AWS Bedrock","optional":false},{"name":"AWS Bedrock AgentCore","optional":false},{"name":"AWS Lambda","optional":false},{"name":"CI/CD","optional":false},{"name":"Claude","optional":false},{"name":"CrewAI","optional":false},{"name":"Embeddings","optional":false},{"name":"FastAPI","optional":false},{"name":"Git","optional":false},{"name":"IAM","optional":false},{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"LlamaIndex","optional":false},{"name":"LLM","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"Machine Learning","optional":false},{"name":"NumPy","optional":false},{"name":"OpenSearch","optional":false},{"name":"Pandas","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Rest API","optional":false},{"name":"Agile","optional":true},{"name":"Amazon Redshift","optional":true},{"name":"Anthropic","optional":true},{"name":"AWS Glue","optional":true},{"name":"Docker","optional":true},{"name":"DynamoDB","optional":true},{"name":"Gemini","optional":true},{"name":"Kubernetes","optional":true},{"name":"NLP","optional":true},{"name":"OCR","optional":true},{"name":"OpenAI","optional":true},{"name":"SQL","optional":true}],"status":"live","first_seen_at":"2026-10-30T15:58:15Z","employer_posted_date":"2026-10-30","last_verified_at":"2026-10-31T09:47:40Z","board_verified":true,"closed_at":null,"days_open":1,"trust":{"level":"ok","repost_count":0,"flags":["company_stale"],"days_open":1},"description":"While technology is the heart of our business, a global and diverse culture is the heart of our success. We love our people and we take pride in catering them to a culture built on transparency, diversity, integrity, learning and growth.\nIf working in an environment that encourages you to innovate and excel, not just in professional but personal life, interests you- you would enjoy your career with Quantiphi!\nJOB ROLE - Senior Machine Learning Engineer (4-7 yrs)\nAs a Senior Machine Learning Engineer at Quantiphi, you will be responsible for designing and developing advanced machine learning models and algorithms to solve complex business problems. You will work on optimizing and deploying these models on AWS infrastructure, ensuring scalability and reliability.\nMust have skills:\nExperience with LangChain, LangGraph, LlamaIndex, CrewAI, or similar Agentic AI frameworks.\n\nPython: Good exposure to Python (Pandas, NumPy, FastAPI, advanced Python concepts).\n\nAWS Bedrock: Hands-on experience with AWS Bedrock and foundation models such as Claude Haiku and Claude Sonnet.\n\nLLM & GenAI: Hands-on experience in developing RAG pipelines, Prompt Engineering, and LLM-based GenAI applications.\n\nML Pipeline Architecture: Experience with Titan Embeddings, Amazon OpenSearch Vector Search, and vector-based retrieval.\n\nAgentic AI: Hands-on experience with Agentic AI frameworks and AWS Bedrock AgentCore for developing AI agents and workflow orchestration.\n\nAI Agents & Knowledge Base: Experience developing AI agents for customer query automation and Knowledge Base (KB) solutions.\n\nExperience with document parsing, chunking, vectorizing and re-ranking strategies.\n\nGuardrails & Security: Experience configuring AWS Bedrock Guardrails and implementing authentication and authorization for secure AI applications.\n\nAWS Services: Hands-on experience with API Gateway, Lambda, S3, IAM, CloudWatch, ECR, and SageMaker.\n\nSoftware Engineering: Experience with Git, REST APIs, and CI/CD pipelines.\n\nRelevant AWS certifications (e.g., AWS Certified AI Practitioner, AWS Certified Machine Learning Engineer - 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