Artificial Intelligence Engineer

AI/ML Engineer – Pharma & Legal Document Intelligence

Experience : 3 years to 5 years

Location: Rajkot (Gujarat) / Hyderabad

Hiring Type : Contract-to-Hire (Initial contract for 6 Months)

About the Role

We at Websmith Solutions are hiring an AI/ML Engineer to design and deploy advanced pharma & legal document intelligence systems. You will leverage Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) to transform patents, molecule structures, regulatory filings, and legal documents into structured, queryable knowledge. The role combines document AI, data engineering, model training, and production deployment.

Key Responsibilities

• Build AI pipelines to parse, summarize, and classify pharma/legal PDFs (patents, molecule structures, court filings).

• Work with SMEs to extract key insights and build chatbots for interactive Q&A.

• Clean and integrate Excel/raw datasets into a central master database.

• Automate ingestion of fresh data from FDA portals, government, and legal websites.

• Customize and fine-tune LLMs on domain-specific data, ensuring high accuracy.

• Deploy and monitor models in production with scalability, reliability, and compliance in mind.

Required Technical Expertise

• Programming & ML Frameworks: Advanced Python, PyTorch/TensorFlow, HuggingFace Transformers, LangChain / LlamaIndex.

• Document Parsing & OCR: PyMuPDF, pdfminer.six, Apache Tika, Tesseract.

• NLP & RAG: embeddings (OpenAI, HuggingFace), vector DBs (FAISS, Pinecone, Weaviate, Milvus), chunking strategies.

• Data Engineering: ETL pipelines, SQL + NoSQL (Postgres, MongoDB), Excel/CSV cleaning & schema design.

• Model Training: fine-tuning transformers, LoRA/PEFT for efficient domain adaptation, dataset annotation/validation.

Nice-to-Have

• Deployment & MLOps: FastAPI/Flask for serving, Docker/Kubernetes for scaling, AWS SageMaker / GCP Vertex AI / Azure ML, MLflow or Kubeflow for monitoring.

• Compliance & Security: secure APIs, encryption, pharma/legal data privacy standards.

• Familiarity with chemical/molecule data formats (SMILES, InChI, RDKit).

• Background in pharma, biotech, or legal domains.

• Prior experience with sensitive, regulated datasets.

Why Join?

• Work on cutting-edge LLM + RAG projects applied to real-world pharma & legal problems.

• Opportunity to own the end-to-end lifecycle: ingestion → training → deployment → monitoring.

• Collaborate with experts across AI, pharma, and legal domains.