{"id":1227549,"url":"https://alion.io/job/absi-usa-associate-lead-aiml-engineer","title":"Associate Lead AI/ML Engineer","company":{"id":3800495,"name":"Absi Usa","domain":"absi-usa.com","url":"https://alion.io/company/absi-usa","size_band":"1-10","is_staffing_agency":false,"employer_type":"staffing","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"lead","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Pune, 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improve indexing, query relevance, and search accuracy.\n\n- Support taxonomy, ontology, and metadata model creation for better search outcomes.\n\n- Collaborate with business units (Loans, Insurance, Investments) to build AI-enabled search features.\n\n- Conduct analysis of user behavior and system metrics to refine search performance.\n\n- Work with engineers, product managers, and designers to deliver integrated search solutions.\n\n- Develop production-grade ML systems for ranking, personalization, and recommendations.\n\n- Participate in proof-of-concept initiatives with internal and external partners.\n\n- Follow best practices in software engineering including CI/CD, testing, and monitoring.\n\n- Keep abreast of emerging developments in AI/ML to apply them in practical solutions.\n\nIdeal Candidate :\n\nMandatory Experience :\n\n- 3+ years of hands-on experience in Data Science, Machine Learning, Applied AI, NLP, Deep Learning, or Generative AI solutions.\n\n- Strong hands-on experience in Python programming, SQL, data analysis, feature engineering, model development, and production-grade ML applications.\n\n- Experience with Machine Learning and Deep Learning frameworks such as PyTorch, TensorFlow, Keras, Scikit-learn, or equivalent.\n\n- Hands-on experience working on NLP, embeddings, semantic search, text classification, document understanding, recommendation systems, or similar AI/ML use cases.\n\n- Experience working with Large Language Models (LLMs) such as GPT, Llama, Mistral, Claude, Gemini, Phi, or similar foundation models.\n\n- Hands-on experience building or implementing RAG (Retrieval Augmented Generation) systems, vector search, knowledge retrieval, embeddings, chunking, indexing, or semantic retrieval solutions.\n\n- Experience working with Git, CI/CD practices, production environments, and scalable AI/ML systems.\n\nPreferred Experience :\n\n- Experience with MLFlow, Kubeflow, Airflow, Prefect, Feature Stores, Model Registry, or MLOps/LLMOps frameworks.\n\n- Experience working with Vector Databases, Spark, PySpark, distributed ML pipelines, large-scale data processing, or real-time ML systems.\n\n- Familiarity with Docker, Kubernetes, Azure, AWS, GCP, cloud-native AI deployments, and scalable ML architecture.\n\nEligibility :\n\n- Candidates from AI-first startups, Fintech, Banking, Lending, Fraud Analytics, Risk Analytics, Product Companies, SaaS organizations, or data-driven technology companies.\n\n- B.TECH / M.TECH from Tier 1 Colleges (IIT's, NIT's, BITS) are considered.\n\nSkills\nArtificial Intelligence, Machine Learning, Data Science, NLP, Deep Learning, SQL, Python, Generative AI, LLM, Apache 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