DataNimbus - Senior Machine Learning Engineer - LLM/RAG

DataNimbus; Hyderabad; On-site; INR 1,500,000 - 2,000,000; Full time

Job summary

DataNimbus in Hyderabad is looking for an experienced Data Scientist to build and enhance customer data science workloads using the latest MLOps practices. You will develop LLM solutions and provide mentorship to data teams.

The ideal candidate should have over 6 years of experience in data science, expertise in machine learning tools, and a graduate degree in a related field. A passion for collaboration and teaching is essential.

Qualifications

• 6+ years of hands-on industry data science experience.
• Experience with production-grade ML deployments on AWS, Azure, or GCP.
• Graduate degree in Computer Science, Engineering, Statistics, or equivalent.

Responsibilities

• Build customer data science workloads and apply MLOps best practices.
• Develop LLM solutions on customer data.
• Advise teams on data science topics and provide technical mentorship.

Skills

Data Science Experience

MLOps Best Practices

Machine Learning Tools

NLP Techniques

Technical Communication

Education

Graduate Degree in Quantitative Discipline

Tools

pandas

mlflow

scikit-learn

TensorFlow/PyTorch

AWS

Azure

GCP

Job description

DataNimbus is a cloud-native data and AI company focused on delivering scalable solutions and driving growth for its customers.

Responsibilities

• Build and increase customer data science workloads and apply best MLOps to productionize these workloads across a variety of domains.
• Develop LLM solutions on customer data such as RAG architectures on enterprise knowledge repositories, querying structured data with natural language, and content generation.
• Advise data teams on data science topics such as architecture, tooling, and best practices.
• Provide technical mentorship to the larger ML Subject Matter Expert community.

Qualifications

• 6+ 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 latest techniques in NLP 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, lifelong learning, and driving value through ML.
• Can meet expectations for technical training and role‑specific outcomes within 3 months of hire.