We are seeking a Data Scientist with experience to design, build, and deploy GenAI and LLM-powered solutions. The role combines applied ML, prompt engineering, and MLOps to deliver scalable, production-grade AI systems.
Key Responsibilities
Develop and deploy LLM-based applications (RAG, chatbots, copilots, summarization, search)
Fine-tune, evaluate, and optimize LLMs and transformer models
Design prompt engineering strategies and guardrails for safe, reliable outputs
Build retrieval pipelines using vector databases (FAISS, Pinecone, etc.)
Implement end-to-end ML pipelines (data 12 model 12 deployment 12 monitoring)
Collaborate with engineering teams to integrate models via APIs and microservices
Monitor model performance, drift, and costs; implement feedback loops
Ensure responsible AI practices (bias mitigation, explainability, governance)
Required Skills & Qualifications
3-6 years of experience in Data Science / ML Engineering / Applied AI
Strong programming in Python
Hands-on experience with LLMs (OpenAI, Azure OpenAI, etc.)
Experience with transformers, embeddings, and NLP pipelines
Familiarity with RAG architectures and vector search
Solid foundation in ML algorithms, statistics, and evaluation metrics
Strong SQL and data handling skills
MLOps & Engineering Skills
Experience with model deployment (FastAPI, Flask, Docker, Kubernetes)
Exposure to CI/CD pipelines for ML (GitHub Actions, Azure ML, SageMaker, etc.)
Experience in model monitoring, logging, and versioning (MLflow, Weights & Biases)
Knowledge of data pipelines (Airflow, Spark)
Familiarity with cloud platforms (AWS, Azure, or GCP)
Preferred Qualifications
Experience fine-tuning LLMs (LoRA, PEFT techniques)
Exposure to multi-modal models (text + image/audio)
Knowledge of AI safety, hallucination mitigation, and evaluation frameworks
Domain experience in enterprise use cases (support, search, analytics, automation)
Soft Skills
Strong problem-solving and experimental mindset
Ability to translate ambiguous business problems into AI solutions
Excellent communication with technical & non-technical stakeholders
Education
Bachelor's or Master's in Computer Science, AI, Data Science, Statistics, or a related field
