{"id":1279276,"url":"https://alion.io/job/ajni-consulting-data-scientist","title":"Data Scientist","company":{"id":3801621,"name":"Ajni Consulting","domain":"prometheusconsulting.in","url":"https://alion.io/company/ajni-consulting","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":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":22000,"max_usd":44000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":51},"experience_years_min":5,"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":"ElasticSearch","optional":false},{"name":"Embeddings","optional":false},{"name":"GCP","optional":false},{"name":"Hallucination","optional":false},{"name":"Kubernetes","optional":false},{"name":"LangChain","optional":false},{"name":"LlamaIndex","optional":false},{"name":"LLM","optional":false},{"name":"LLM Evaluation","optional":false},{"name":"LLMOps","optional":false},{"name":"Milvus","optional":false},{"name":"Pinecone","optional":false},{"name":"RAG","optional":false},{"name":"Reranking","optional":false},{"name":"Semantic Kernel","optional":false},{"name":"Weaviate","optional":false}],"status":"live","first_seen_at":"2026-08-25T08:20:23Z","employer_posted_date":null,"last_verified_at":"2026-08-25T08:20:23Z","board_verified":false,"closed_at":null,"days_open":38,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":38},"description":"Job Description : \n\nAs a Data Scientist, you will identify business trends and solve complex problems using large-scale data and advanced AI techniques. You will design, develop, and deploy high-impact solutions ranging from classical ML/DL to LLM-powered applications including RAG-based architectures and Agentic AI systems.\n\nKey Responsibilities :\n\n- Analyze existing digital products to understand current intelligent models and improve their performance, reliability, and scalability.\n\n- Enhance traditional ML and DL pipelines by incorporating LLM-based capabilities such as summarization, Q&A, reasoning, decision support, and copilots.\n\n- Design and implement LLM-based solutions using Retrieval-Augmented Generation (RAG) to ground responses on enterprise data.\n\n- Build Agentic AI workflows that enable multi-step task planning, tool and API invocation, and contextual memory management.\n\n- Develop agent orchestration patterns such as multi-agent collaboration, deterministic workflow engines, and fallback mechanisms.\n\n- Drive innovation through experimentation and contribute to invention disclosures and patents.\n\n- Design and implement AI solutions for IoT, robotics, and automation use cases.\n\n- Build and maintain scalable pipelines for model training, evaluation, and deployment.\n\n- Manage experiment tracking, model versioning, and model registries.\n\n- Define and track LLM-specific evaluation metrics including groundedness, faithfulness, hallucination rate, and safety.\n\n- Monitor retrieval system quality using metrics such as precision, recall, and latency.\n\nRequired Qualifications :\n\n- Masters degree in Computer Science, Electrical Engineering, Applied Mathematics, Statistics, or a related field (PhD preferred).\n\n- Strong oral and written communication skills.\n\n- Demonstrated ability to take ambiguous objectives and design innovative, flexible solutions.\n\n- Proven track record of delivering impactful outcomes.\n\nTechnical Skills :\n\n- Expertise in Large Language Models (LLMs) and building production-grade applications.\n\n- Hands-on experience with RAG architectures, embeddings, vector search, and reranking mechanisms.\n\n- Experience building tool-using agents and multi-step agent workflows.\n\n- Familiarity with vector databases (e.g., Pinecone, Milvus, Weaviate, Elasticsearch).\n\n- Experience with agent frameworks (e.g., LangChain, Semantic Kernel, LlamaIndex).\n\n- Experience with LLMOps tooling: prompt management, evaluation harnesses, and observability.\n\n- Cloud experience (Azure/AWS/GCP), containerization (Docker), and Kubernetes.\n\nBehavioral Competencies :\n\n- Strong ownership mindset and proactive leadership.\n\n- Collaborative team player with an innovation-first approach.\n\nSkills\nMachine Learning, Data Science, LLM, RAG, Agentic AI, Artificial Intelligence, Data Scientist, VectorDB","description_format":"text","description_chars":2827,"description_truncated":false,"requirements":{"experience_years_min":5,"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":[],"lifecycle":[{"event":"open","at":"2026-09-26T02:00:24Z"}],"liveness":{"score":16,"band":"cold","label":"Long shot","p_open":0.6,"p_active":0.58,"p_room":0.45,"age_days":37,"expected_fill_days":24,"reasons":["seen:37","win:tail"],"computed_at":"2026-10-02T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/ajni-consulting-data-scientist","json_url":"https://alion.io/job/ajni-consulting-data-scientist.json","meta":{"generated_at":"2026-10-02T15:05:57Z","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":"search","counted_by":"address","units_charged":0,"used_today":0,"day_limit":null,"remaining_today":null,"minute_limit":null,"resets_at":"2026-10-03T00:00:00Z"}}}