{"id":2428942,"url":"https://alion.io/job/bharti-airtel-senior-lead-engineer-data-science","title":"Senior Lead Engineer - Data Science","company":{"id":2659,"name":"Bharti Airtel","domain":"airtel.in","url":"https://alion.io/company/airtel","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":"lead","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Gurgaon, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":30000,"max_usd":64000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":20},"experience_years_min":7,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"AutoGen","optional":false},{"name":"AWS","optional":false},{"name":"BentoML","optional":false},{"name":"CI/CD","optional":false},{"name":"Computer Vision","optional":false},{"name":"CrewAI","optional":false},{"name":"Diffusion Models","optional":false},{"name":"Docker","optional":false},{"name":"Embeddings","optional":false},{"name":"FAISS","optional":false},{"name":"Fine-tuning","optional":false},{"name":"GitHub Actions","optional":false},{"name":"Hugging Face","optional":false},{"name":"Hybrid Search","optional":false},{"name":"Knowledge Distillation","optional":false},{"name":"Kubernetes","optional":false},{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"LangSmith","optional":false},{"name":"llama.cpp","optional":false},{"name":"LLMOps","optional":false},{"name":"LoRA","optional":false},{"name":"Machine Learning","optional":false},{"name":"MLFlow","optional":false},{"name":"Model Distillation","optional":false},{"name":"OpenAI","optional":false},{"name":"OpenCV","optional":false},{"name":"PEFT","optional":false},{"name":"Pinecone","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Qdrant","optional":false},{"name":"QLoRA","optional":false},{"name":"Quantization","optional":false},{"name":"RAG","optional":false},{"name":"Ray","optional":false},{"name":"SFT","optional":false},{"name":"SQL","optional":false},{"name":"Terraform","optional":false},{"name":"Transformers","optional":false},{"name":"Triton","optional":false},{"name":"TypeScript","optional":false},{"name":"vLLM","optional":false},{"name":"Weaviate","optional":false}],"status":"live","first_seen_at":"2026-10-13T07:59:29Z","employer_posted_date":null,"last_verified_at":"2026-10-13T07:59:29Z","board_verified":false,"closed_at":null,"days_open":18,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":18},"description":"Role Overview:\nWe are seeking for Senior Lead Engineer - Data Science for building end-to-end AI systems, spanning traditional machine learning, Generative AI (LLMs, Diffusion Models), and Agentic AI architectures (e.g., LangGraph, CrewAI, AutoGen) along with good experience with fine tuning, computer vision frameworks such as OpenCV. You will drive system design, architecture, and delivery of intelligent services embedded into production systems.\n\nKey Responsibilities:\nSystem Architecture & Engineering Oversight\nArchitect scalable pipelines for training/fine-tuning open source LLMs \nBuilding framework for reducing Agent hallucinations, low latency and reliable output\nRAG pipelines with semantic chunking, hybrid retrieval, and context injection.\nImplement vector indexing (FAISS, Pinecone, Weaviate) with hybrid search.\nOwn LLMOps stack: prompt versioning, evaluation, monitoring, and drift detection.\nDevelop and optimize deep learning models for computer vision tasks such as Image classification/Face Authentication\n\nTechnical Delivery & Innovation\nBuild GenAI applications serving organisational use cases and reduce human dependencies\nModel serving with vLLM, Triton; use of async inference and caching.\n\nTeam Leadership & Execution\nLead multidisciplinary teams; define technical roadmaps.\nEnsure CI/CD, modular ML design, containerization.\nCollaborate with Product and Research to align business outcomes.\n\nLanguages: Python, TypeScript, SQL, optionally Go/Rust\nML/AI: PyTorch, HuggingFace, LangChain/LangGraph, OpenAI APIs, llama.cpp, OpenCV\nLLMOps: MLflow, LangSmith, BentoML, Weights & Biases\nInfra: Docker, Kubernetes, Ray, AWS/GCP\nVector DBs: FAISS, Qdrant, Weaviate, Elasticsearch\nDevOps: GitHub Actions, Terraform, ArgoCD\n\nRequirements:\n7+ years in ML/AI; 2+ years in leadership.\nProduction experience with GenAI and agent-based systems.\nDeep understanding of LLMs, embeddings, attention, prompt engineering.\nExperience with scalable AI infra and high-throughput serving.\nStrong experience in building CV pipelines for classification, detection and face recognition\nBuilding end-to-end AI systems, spanning traditional machine learning, Generative AI (LLMs,Diffusion Models), and Agentic AI architectures (e.g., LangGraph, CrewAI, AutoGen)\nStrong fundamentals in Machine Learning, Deep Learning and Generative AI\nHands-on experience in data cleaning, normalization, preprocessing and feature engineering\nExperience in dataset creation, curation, labeling and quality validation\nStrong understanding of Transformers, attention, embeddings and tokenization\nHands-on experience in training and fine-tuning SLMs/LLMs\nExperience with SFT, LoRA/QLoRA, PEFT and instruction tuning\nStrong hands-on with Python, PyTorch and Hugging Face\nExperience in model evaluation, benchmarking, error analysis and hyperparameter tuning\nUnderstanding of model compression, quantization, distillation and inference optimization\nAbility to take models end-to-end from data preparation to training, evaluation and production deployment.\nOSS contributions to GenAI/Agentic frameworks.\nIndustry-specific RAG experience (legal, finance, healthcare).\nKnowledge of vector compression, neuro-symbolic reasoning.\n\nWhy Join Us:\n Join a high-caliber team pushing boundaries in AI/LLMs.\n 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