{"id":120653,"url":"https://alion.io/job/mthree-data-scientist","title":"Data Scientist","company":{"id":46778,"name":"MThree","domain":"mthree.ai","url":"https://alion.io/company/mthree","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"middle","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Delhi, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":15000,"max_usd":36000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":16},"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Docker","optional":false},{"name":"FAISS","optional":false},{"name":"GCP","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"NLP","optional":false},{"name":"Pinecone","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"RAG","optional":false},{"name":"Scikit-learn","optional":false},{"name":"Structured Outputs","optional":false},{"name":"TensorFlow","optional":false},{"name":"Weaviate","optional":false}],"status":"live","first_seen_at":"2026-08-25T04:39:10Z","employer_posted_date":null,"last_verified_at":"2026-08-25T04:39:10Z","board_verified":false,"closed_at":null,"days_open":55,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":55},"description":"Responsibilities:\nDesign scalable, reliable AI systems with a focus on production readiness, maintainability, and performance.\nPerform root cause analysis and debugging of AI pipelines to improve accuracy, consistency, and reliability.\nDevelop automated evaluation, validation, and testing strategies for AI applications.\nDesign reliable LLM workflows using structured outputs, validation, retrieval, and business rules.\nCreate and maintain RAG pipelines and AI agent frameworks.\nPerform data analysis, model evaluation, and performance optimisation.\nDevelop APIs and integrate AI solutions into existing products and platforms.\nCollaborate with cross-functional teams, including engineering and business stakeholders, to define AI use cases and deliver solutions.\nMonitor, troubleshoot, and continuously improve deployed AI systems.\nRequirements:\n3-4 years of experience building AI/ML applications with strong Python and software engineering skills.\nStrong proficiency in Python.\nHands-on experience with: Understanding of AI system design, evaluation, monitoring, and performance optimisation.\nExperience developing, deploying, and maintaining production AI applications.\nStrong software engineering fundamentals, including clean code, modular design, debugging, and testing. o RAG architectures.\nExperience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn.\nGood understanding of NLP concepts.\nFamiliarity with API development and integration.\nAbility to work independently as well as in collaborative team environments.\nExperience with vector databases such as Pinecone, Weaviate, FAISS, ChromaDB.\nKnowledge of cloud platforms such as AWS, Azure, or GCP. 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