{"id":1227432,"url":"https://alion.io/job/absi-usa-data-scientist-ai-engineer","title":"Data Scientist / AI 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":"middle","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Pune, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":19500,"max_usd":48000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":22},"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Azure","optional":false},{"name":"Claude","optional":false},{"name":"ElasticSearch","optional":false},{"name":"Embeddings","optional":false},{"name":"FAISS","optional":false},{"name":"FastAPI","optional":false},{"name":"Flask","optional":false},{"name":"Gemini","optional":false},{"name":"Hybrid Search","optional":false},{"name":"Keras","optional":false},{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"LLM","optional":false},{"name":"LLMOps","optional":false},{"name":"Machine Learning","optional":false},{"name":"Mistral","optional":false},{"name":"NER","optional":false},{"name":"NLP","optional":false},{"name":"OpenAI","optional":false},{"name":"Pinecone","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"RAG","optional":false},{"name":"Scikit-learn","optional":false},{"name":"Semantic Search","optional":false},{"name":"Semantic Search","optional":false},{"name":"Sentiment Analysis","optional":false},{"name":"TensorFlow","optional":false},{"name":"Weaviate","optional":false},{"name":"Apache Kafka","optional":true},{"name":"Azure AKS","optional":true},{"name":"Docker","optional":true},{"name":"Kubernetes","optional":true},{"name":"PostgreSQL","optional":true},{"name":"Redis","optional":true}],"status":"live","first_seen_at":"2026-09-24T09:59:50Z","employer_posted_date":null,"last_verified_at":"2026-09-24T09:59:50Z","board_verified":false,"closed_at":null,"days_open":5,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":5},"description":"Roles & Responsibilities:\n\n- Design and develop intelligent AI-based applications using advanced NLP and LLM techniques to solve real-world business challenges in financial services.\n\n- Build and optimize Retrieval-Augmented Generation (RAG) pipelines leveraging structured and unstructured financial data.\n\n- Integrate and orchestrate LLMs/SLMs for question-answering, summarization, semantic search, and document understanding.\n\n- Develop and maintain RESTful APIs (sync and async) to serve NLP models and chatbot interfaces using frameworks like FastAPI, Flask, etc.\n\n- Should have knowledge of advanced prompting techniques.\n\n- Implement semantic search, hybrid search, and text retrieval systems using Elasticsearch and vector databases (e.g., FAISS, Pinecone, Weaviate).\n\n- Perform NLP tasks such as entity recognition, text classification, intent detection, embedding generation, and sentiment analysis where required.\n\n- Monitor and fine-tune LLM/SLM performance with real-world user data to improve relevance, latency, and accuracy.\n\n- Exposure to LLMOps tools for monitoring, evaluation, and versioning of AI models in production.\n\n- Build, train, and evaluate deep learning models for NLP tasks including classification, NER, summarization, and embedding generation.\n\n- Develop traditional machine learning models (e.g., regression, decision trees, clustering) for structured data analysis and prediction tasks.\n\n- Interact with cross-functional teams to understand system issues and follow up with respective teams to get them fixed.\n\n- Understand and identify areas of improvement across businesses and participate in solution identification and implementation.\n\n- Should be able to work as an Individual Contributor on new and existing projects.\n\n- Positive and problem-solving attitude, must work as an independent contributor.\n\nIdeal Candidate:\n\n1. Profile:\n\n- Strong Data Scientist / AI Engineer / Generative AI Engineer profile.\n\n2. Mandatory Experience:\n\n- 1. Must have 3+ years of hands-on experience in Data Science, Artificial Intelligence, Machine Learning, Deep Learning, NLP, or Generative AI application development.\n\n- 2. Must have strong hands-on experience in Python programming, backend development, API development, and production-grade application support.\n\n- 3. Must have experience working with Machine Learning and Deep Learning frameworks such as PyTorch, TensorFlow, Keras, or Scikit-learn.\n\n- 4. Must have hands-on experience in NLP use cases such as text classification, sentiment analysis, entity recognition (NER), semantic search, embeddings, or document understanding.\n\n- 5. Must have experience working with Large Language Models (LLMs) such as GPT, LLaMA, Mistral, Phi, Claude, Gemini, or similar models.\n\n- 6. Must have hands-on experience building or implementing Retrieval Augmented Generation (RAG) solutions, vector search, semantic search, or knowledge-based AI applications.\n\n- 7. Must have experience with Prompt Engineering and Generative AI frameworks such as LangChain, LangGraph, AI Agents, Azure OpenAI, or similar technologies.\n\n- 8. Must have experience developing, consuming, or integrating APIs using Python frameworks such as FastAPI, Flask, or similar technologies.\n\n3. Compensation & Requirements:\n\n- 1. Mandatory (CTC) - The CTC breakup offered will be 75% fixed + 25% variable, as per company policy.\n\n- 2. Mandatory (Age) - Candidate should be below 28 years.\n\n- 3. Mandatory (Pedigree) - B.TECH / M.TECH from Tier 1 Colleges (IIT's, NIT's, BITS) are considered.\n\n4. Preferred Experience:\n\n- 1. Experience with LLMOps/MLOps tools for monitoring, evaluation, experimentation, and versioning of AI models.\n\n- 2. Exposure to Azure OpenAI, Azure Kubernetes Service (AKS), Kubernetes, cloud-native AI deployments, or distributed systems.\n\n- 3. Experience working with PostgreSQL, MongoDB, Redis, Kafka, or large-scale data platforms.\n\n- 4. Familiarity with Docker, Kubernetes, cloud platforms, and scalable deployment architecture.\n\n- 5. Candidates from AI-first startups, product companies, SaaS organizations, fintech, or data-driven technology companies.\nSkills\nMachine Learning, Python, Generative AI, NLP, Data Scientist, Artificial Intelligence, LLM","description_format":"text","description_chars":4218,"description_truncated":false,"requirements":{"experience_years_min":3,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["IT Consulting & Digital Transformation"],"lifecycle":[{"event":"open","at":"2026-09-25T13:06:44Z"}],"liveness":{"score":88,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.884,"p_room":1,"age_days":4,"expected_fill_days":26,"reasons":["seen:4","velocity","win:early"],"computed_at":"2026-09-29T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/absi-usa-data-scientist-ai-engineer","json_url":"https://alion.io/job/absi-usa-data-scientist-ai-engineer.json","meta":{"generated_at":"2026-09-30T01:27:04Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":984,"day_limit":5000,"remaining_today":4016,"minute_limit":60,"resets_at":"2026-10-01T00:00:00Z"}}}