Duration: 6 months
Role Overview
We are seeking an AI/ML Engineer with hands-on experience building, fine-tuning, and deploying LLM-based solutions. You will work on NLP/GenAI use cases such as classification, summarization, and retrieval-augmented generation (RAG), partnering with product and engineering teams to deliver scalable, secure, and measurable outcomes.
Required Qualifications
6+ years of overall experience in software development, data analytics, data science, or ML engineering.
2+ years of hands-on experience with deep learning for NLP/GenAI.
Strong Python proficiency, including writing production-quality, testable, maintainable code.
Experience with deep learning frameworks and libraries: PyTorch or TensorFlow; Hugging Face Transformers.
Solid understanding of deep learning architectures and modern NLP/LLM concepts (tokenization, attention/transformers, fine-tuning approaches).
Experience building rapid prototypes and APIs using FastAPI/Flask and/or Streamlit.
Preferred Qualifications
Experience with LLM orchestration frameworks (LangChain, LlamaIndex, Semantic Kernel, or similar).
Experience with vector databases and embedding workflows (e.g., FAISS, Pinecone, Weaviate, Chroma, Azure AI Search).
Experience deploying and scaling ML/LLM workloads on cloud platforms (Azure preferred; GCP/AWS acceptable).
Familiarity with agentic architectures and multi-agent patterns (e.g., AutoGen or similar).
Healthcare domain knowledge and/or experience building solutions in regulated environments.
Standard Technical Skills
MLOps & Deployment: Model packaging and serving, CI/CD, containers (Docker), orchestration (Kubernetes), experiment tracking (MLflow), model registry, monitoring/observability.
LLM Evaluation: Offline/online evaluation, prompt/version management, automated testing, hallucination and factuality checks, retrieval evaluation, human-in-the-loop review.
Software Engineering: Git, code reviews, unit/integration testing (pytest), REST APIs, basic system design, performance optimization.
Security & Compliance: Secure coding, secrets management, PII/PHI handling, access control; familiarity with responsible AI principles is a plus.
Skills: Digital : Python ~ Digital : Machine Learning ~ AI Agents ~ AI & Gen AI – Products & Tools