We are seeking a highly skilled and forward-thinking Senior AI & Machine Learning Developer with 6+ years of experience to lead the design, development, and deployment of cutting-edge artificial intelligence and machine learning solutions. In this role, you will bridge the gap between advanced research and production-grade software, with a heavy emphasis on Generative AI, Large Language Models (LLMs), and robust Data Engineering.

You will work closely with cross-functional teams to architect scalable AI pipelines, optimize model deployment, and foster a culture of technological innovation.

Core Responsibilities :

- Architecture & Implementation : Design, fine-tune, and deploy state-of-the-art Generative AI models and Large Language Models (LLMs) to solve complex business problems.

- Advanced Techniques : Implement advanced Retrieval-Augmented Generation (RAG) frameworks, agentic workflows, and prompt engineering methodologies to optimize model accuracy, context-awareness, and response quality.

- Model Customization : Execute parameter-efficient fine-tuning (PEFT, LoRA, QLoRA) on open-source foundations (e.g., Llama, Mistral, Mixtral) and leverage commercial APIs (e.g., OpenAI, Anthropic) effectively.

- Pipeline Development : Build and maintain scalable, high-throughput data pipelines (ETL/ELT) to ingest, process, and clean structured and unstructured data for training and inference.

- Vector Infrastructure : Architect and optimize vector databases (e.g., Pinecone, Milvus, Qdrant, Chroma) for highly efficient semantic search, document indexing, and fast retrieval.

- Data Governance : Ensure robust data privacy, compliance, and security standards across all data layers, particularly when handling sensitive information in AI contexts.

- Productionalization : Transition prototype models into highly available, secure, and production-ready microservices using frameworks like FastAPI, Flask, or Docker.

- Performance Tuning : Optimize models for inference latency and throughput using technologies such as TensorRT, vLLM, DeepSpeed, or quantization techniques (AWQ, GPTQ).

- Monitoring & Observability : Set up comprehensive MLOps pipelines using tools like MLflow, Weights & Biases, or LangSmith to monitor data drift, model latency, LLM evaluation metrics, and overall system health.

- Technical Leadership : Mentor and guide junior machine learning engineers, promoting best practices in clean coding, version control (Git), and agile AI development.

- Cross-Functional Alignment : Collaborate with Product Managers, Frontend/Backend Developers, and Domain Experts to seamlessly translate business requirements into technical AI blueprints.

- R&D Mindset : Stay at the absolute forefront of AI research. Proactively evaluate emerging papers, frameworks, and open-source projects to run Proof-of-Concepts (PoCs) that keep our systems ahead of the curve.

Required Skills & Qualifications :

- Experience : Minimum 6+ years of professional experience in Machine Learning, Software Engineering, or Data Science roles, with at least 2+ years dedicated to Generative AI and LLM implementation.

- Programming Mastery : Expert-level proficiency in Python and its core AI ecosystem (NumPy, Pandas, Scikit-Learn).

- Deep Learning Frameworks : Hands-on mastery of PyTorch or TensorFlow/Keras.

- GenAI Stack : Extensive experience with LangChain, LlamaIndex, Hugging Face Transformers, and building custom autonomous agent frameworks.

- Cloud & MLOps Infrastructure : Strong experience with major cloud platforms (AWS, Azure, or GCP) and infrastructure tools like Docker, Kubernetes, and CI/CD pipelines.

- Experience building enterprise-grade applications within highly regulated domains (e.g., Fintech, Payments, E-commerce, or Healthcare/Pharma).

- Prior experience in product-based engineering environments scaling systems to millions of users.

- Contributions to open-source GenAI projects or published research papers in top-tier ML conferences (NeurIPS, ICML, CVPR, ACL).

- An opportunity to work on bleeding-edge AI initiatives with highly visible product impact.

- A collaborative, fast-paced culture that values continuous learning and creative problem-solving.

- Competitive compensation package, comprehensive healthcare, and flexible work arrangements.