Sr. Data Scientist - AI/ML

As a Senior Data Scientist at AuxoAI, you will be responsible for designing, deploying, and scaling production-grade ML systems. Your expertise in AI, machine learning engineering (MLE), and generative AI will be crucial in this role. You will have the opportunity to work on large language model (LLM)-based pipelines, AI copilots, and agentic workflows. This position is perfect for someone who enjoys combining cutting-edge research with production rigor and is passionate about mentoring while creating impactful AI applications. Your key responsibilities will include: - Owning the full ML lifecycle: from model design to training, evaluation, and deployment - Designing production-ready ML pipelines with CI/CD, testing, monitoring, and drift detection - Fine-tuning LLMs and implementing retrieval-augmented generation (RAG) pipelines - Building agentic workflows for reasoning, planning, and decision-making - Developing real-time and batch inference systems using Docker, Kubernetes, and Spark - Leveraging state-of-the-art architectures like transformers, diffusion models, RLHF, and multimodal pipelines - Collaborating with product and engineering teams to integrate AI models into business applications - Mentoring junior team members and promoting MLOps, scalable architecture, and responsible AI best practices Qualifications required for this role: - 6+ years of experience in designing, deploying, and scaling ML/DL systems in production - Proficiency in Python and deep learning frameworks such as PyTorch, TensorFlow, or JAX - Experience with LLM fine-tuning, LoRA/QLoRA, vector search (Weaviate/PGVector), and RAG pipelines - Familiarity with agent-based development (e.g., ReAct agents, function-calling, orchestration) - Solid understanding of MLOps: Docker, Kubernetes, Spark, model registries, and deployment workflows - Strong software engineering background with experience in testing, version control, and APIs - Proven ability to balance innovation with scalable deployment - B.S./M.S./Ph.D. in Computer Science, Data Science, or a related field If you have open-source contributions, GenAI research experience, or have worked on applied systems at scale, it would be considered a bonus.,