{"id":1900176,"url":"https://alion.io/job/infosys-aiml-engineer-snowflake-cloud","title":"AI/ML Engineer - Snowflake Cloud","company":{"id":223,"name":"Infosys","domain":"infosys.com","url":"https://alion.io/company/infosys","size_band":"5000+","is_staffing_agency":false,"employer_type":"services","is_intermediary":false,"listed_via":null,"ats_vendor":"Career site","truth_index":{"grade":"A","score":95,"open_postings":272,"ghost_share":0,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":93,"computed_at":"2026-10-06T05:45:30Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"junior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Indore, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":12500,"max_usd":31000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":11},"experience_years_min":2,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"Cortex","optional":false},{"name":"Docker","optional":false},{"name":"ETL/ELT","optional":false},{"name":"GCP","optional":false},{"name":"LangChain","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"NLP","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Semantic Search","optional":false},{"name":"Semantic Search","optional":false},{"name":"Snowflake","optional":false},{"name":"SQL","optional":false},{"name":"Prometheus","optional":true}],"status":"live","first_seen_at":"2026-10-01T07:47:01Z","employer_posted_date":"2026-10-05","last_verified_at":"2026-10-07T00:31:48Z","board_verified":true,"closed_at":null,"days_open":5,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":5},"description":"Develop, train, evaluate, and deploy Machine Learning models for business use cases.\nBuild predictive analytics, classification, regression, recommendation, and NLP solutions.\nWork with structured and unstructured datasets for model development and optimization.\nPerform feature engineering, model tuning, and performance optimization.\nDevelop data pipelines and ETL/ELT workflows using Snowflake.\nBuild AI/ML solutions leveraging Snowpark and Snowflake's data platform capabilities.\nDesign and implement scalable data models and data warehousing solutions in Snowflake.\nDevelop applications using LLMs and Generative AI technologies.\nBuild Retrieval-Augmented Generation (RAG) pipelines integrating enterprise data sources.\nImplement prompt engineering and LLM evaluation techniques.\nCollaborate with Data Engineers, Data Scientists, and business stakeholders to deliver AI-driven solutions.\nResponsibilities\nDevelop, train, evaluate, and deploy Machine Learning models for business use cases.\nBuild predictive analytics, classification, regression, recommendation, and NLP solutions.\nWork with structured and unstructured datasets for model development and optimization.\nPerform feature engineering, model tuning, and performance optimization.\nDevelop data pipelines and ETL/ELT workflows using Snowflake.\nBuild AI/ML solutions leveraging Snowpark and Snowflake's data platform capabilities.\nDesign and implement scalable data models and data warehousing solutions in Snowflake.\nDevelop applications using LLMs and Generative AI technologies.\nBuild Retrieval-Augmented Generation (RAG) pipelines integrating enterprise data sources.\nImplement prompt engineering and LLM evaluation techniques.\nCollaborate with Data Engineers, Data Scientists, and business stakeholders to deliver AI-driven solutions.\nTechnical requirements\n2-3 years of hands-on AI/ML development experience\nStrong Python and SQL programming skills\nExperience developing and deploying ML models using Snowflake and cloud platforms\nHands-on experience with Snowflake Data Cloud, Snowpark, and data warehousing concepts\nUnderstanding of the ML lifecycle from data preparation to model deployment and monitoring\nExperience building and maintaining ETL/ELT pipelines and data transformation workflows\nAdditional responsibilities\nExperience with Snowpark for Python and Snowflake-native development.\nExposure to Generative AI, LLMs, Prompt Engineering, and RAG architectures.\nKnowledge of LangChain, Vector Databases, and Semantic Search.\nExperience with MLOps practices, model monitoring, and CI/CD pipelines.\nFamiliarity with Docker and containerized deployments.\nExposure to Snowflake Cortex AI capabilities.\nExperience with AWS, Azure, or GCP cloud environments is a plus.\nSnowPro Certification or relevant Snowflake certifications are preferred.\nPreferred skills\nTechnology->AI-Generative AI->Artificial Intelligence - 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