About the Role
We are seeking a Senior Data Scientist / ML Engineer specializing in Generative AI to design, develop, and deploy advanced AI/ML solutions that deliver measurable business value.
The ideal candidate has strong expertise across machine learning, deep learning, NLP, and Generative AI, combined with hands-on experience building production-grade AI applications. This role requires someone who can move effectively from experimentation and prototyping to scalable production deployment.
Key Responsibilities
Design, develop, and productionize Generative AI and machine learning solutions for complex business problems.
Build LLM-powered applications including RAG, AI agents, conversational AI, summarization, classification, and information extraction.
Develop and optimize prompt engineering, model selection, evaluation, and inference strategies.
Work with commercial and open-source LLMs such as GPT, Claude, Gemini, Llama, Mistral, or equivalent models.
Design and implement RAG pipelines, including document ingestion, chunking, embeddings, vector search, reranking, and context optimization.
Fine-tune and adapt foundation models using techniques such as PEFT, LoRA, and supervised fine-tuning.
Develop traditional ML and deep-learning models when appropriate.
Build scalable ML/GenAI pipelines and deploy models through APIs and cloud infrastructure.
Establish evaluation frameworks covering accuracy, relevance, hallucination, latency, cost, safety, and reliability.
Monitor and optimize models and GenAI applications in production.
Collaborate closely with software engineers, product managers, data engineers, and business stakeholders.
Conduct experimentation, statistical analysis, A/B testing, and model benchmarking.
Stay current with advances in LLMs, agentic AI, multimodal AI, retrieval systems, and ML engineering.
Required Qualifications
Bachelor's or master's degree in computer science, Data Science, Statistics, Artificial Intelligence, or a related field.
10+ years of experience in Data Science, Machine Learning, AI Engineering, or a related discipline.
Strong programming skills in Python and experience with PyTorch, TensorFlow, scikit-learn, or similar frameworks.
Strong understanding of machine learning and statistical concepts.
Demonstrated hands-on experience with Generative AI and Large Language Models.
Experience developing RAG-based applications and/or AI agents.
Strong knowledge of embeddings, vector search, semantic retrieval, and information retrieval.
Solid understanding of NLP, transformers, attention mechanisms, and deep learning.
Experience taking ML/AI solutions from prototype through production.
Experience with at least one major cloud platform: AWS, Azure, or GCP.
Strong SQL and data manipulation skills.
Experience with Git, APIs, Docker, CI/CD, and modern software engineering practices.
Preferred Qualifications
Experience with LLM fine-tuning, PEFT/LoRA, DPO, RLHF, or model distillation.
Experience with LangChain, LlamaIndex, Semantic Kernel, or comparable GenAI frameworks.
Experience with vector databases such as Pinecone, Weaviate, Milvus, FAISS, or pgvector.
Experience building agentic workflows, tool calling, and multi-agent systems.
Knowledge of MLOps/LLMOps, model monitoring, observability, and governance.
Experience with multimodal AI involving text, image, audio, or video.
Experience with Kubernetes, Spark, or distributed computing.
Knowledge of responsible AI, privacy, security, and LLM safety practices.