Senior ML Engineer

9 hours ago

Uttar Pradesh Lucknow India EBC Technologies Full time ₹ 12,00,000 - ₹ 24,00,000 per year


Senior ML Engineer Role Overview You will lead the creation and productionization of our AI-driven search pipeline — from building vector indexes and deploying RAG-based systems to designing scalable APIs. You'll work closely with our engineering team to ingest structured legal data, vectorize it, and ensure seamless integration with our user-facing web application. This role requires both deep technical expertise, a product-focused mindset and an enthusiasm to learn new techniques in the fast changing AI landscape. Key Responsibilities 1. AI Based Search Development & Optimization
  • Design and build AI-powered search models that improve retrieval and ranking of legal documents.
  • Implement retrieval-augmented generation (RAG) workflows using pre-trained LLMs (e.g., OpenAI GPT-4).
  • Fine-tune LLMs for legal use cases where necessary (experience with custom LLM training is a strong plus).
  • Improve search quality through relevance testing, feedback loops, and query understanding.
  • Research and implement any new techniques for improving search result relevancy.
2. Data Processing & Vector Indexing
  • Build pipelines to ingest, chunk, and vectorize legal texts (case law, statutes, etc.).
  • Create and maintain indexes in Vector Databases, supporting fast and relevant results.
  • Maintain an evolving legal search index by ingesting new documents on a weekly basis.
3. Model Deployment & API Development
  • Deploy ML models into production using Azure cloud infrastructure.
  • Develop REST APIs (with FastAPI or Flask) to expose model functionality to the application layer.
  • Monitor and optimize latency, scalability, and reliability of deployed solutions.
4. Collaboration & Product Integration
  • Work closely with product managers and full-stack engineers to ship ML-backed features.
  • Participate in design reviews and own technical decisions around AI architecture.
  • Track and improve system performance using user feedback, telemetry, and experimentation.
Tech Stack & Tools
  • ML/NLP: Python, PyTorch/TensorFlow, Hugging Face, Azure OpenAI APIs
  • Vector Search: Azure AI Search (primary), experience with FAISS, Pinecone or Elasticsearch a plus
  • Deployment: Azure (App Services, Azure Functions, Blob Storage, Key Vault)
  • Data Processing: Pandas, NumPy, spaCy, NLTK
  • APIs: REST APIs built with FastAPI or Flask
Required Skills & Experience
  • 5+ years of experience in machine learning, NLP, or AI-based search systems.
  • Strong knowledge of vector search, document embeddings, and retrieval techniques.
  • Experience building and scaling RAG pipelines with LLMs.
  • Proficiency with Azure AI Search for document indexing and search optimization.
  • Demonstrated ability to deploy models to production and build robust APIs.
  • Familiarity with search ranking algorithms (BM25, hybrid search, learning-to-rank).
  • Experience working with document-heavy datasets in legal, academic, or enterprise domains.
  • Experience with fine tuning models and creation of datasets used in fine tuning.
  • On-site position for Lucknow, India.
Nice to Have
  • Background in legal tech, contract analysis, or legal document retrieval.
  • Exposure to open-source search frameworks like Elasticsearch or OpenSearch.
  • Knowledge of observability, logging, and system performance profiling.


Notice Period:
1 Month or less

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