What do we want you to do:

- Build and increase customer data science workloads and apply the best MLOps to productionize these workloads across a variety of domains

- Develop LLM solutions on customer data such as RAG architectures on enterprise knowledge repos, querying structured data with natural language, and content generation

- Advise data teams on several data science such as architecture, tooling, and best practices

- Provide technical mentorship to the larger ML Subject Matter Expert community

What would help make your case:

- 7 13 years of hands-on industry data science experience, using typical machine learning and data science tools including pandas, mlflow, scikit-learn, gensim, nltk, and TensorFlow/PyTorch

- Experience building production-grade machine learning deployments on AWS, Azure, or GCP including drift monitoring

- Experience with the latest techniques in natural language processing including vector databases, fine-tuning LLMs,



and deploying LLMs with tools such as HuggingFace, Langchain, and OpenAI

- Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research) or equivalent practical experience

- Experience communicating and teaching technical concepts to non-technical and technical audiences alike

- Passion for collaboration, life-long learning, and driving value through ML

- [Preferred] Experience working with Apache Spark™ to process large-scale distributed datasets

- [Preferred] Experience working with the Databricks platform

- [Preferred] 4+ years customer-facing experience in a pre-sales or post-sales role

- Can meet expectations for technical training and role-specific outcomes within 3 months of hire.

📌 ML Architect (Hyderabad)
🏢 DataNimbus
📍 Hyderabad