Senior ML Engineer

DataNimbus Inc.; Hyderabad; On-site; INR 4,000,000 - 6,500,000; Full time

Job summary

DataNimbus Inc. in Hyderabad is seeking a Senior ML Engineer with 7+ years of hands-on experience to drive data science workloads end-to-end. You will build production-grade ML deployments, develop LLM solutions on customer data, and mentor other team members.

You will work with cutting-edge tools across AWS/Azure/GCP, vector databases, and modern MLOps to deliver scalable data+AI solutions for global customers.

Qualifications

• 7+ years of hands-on data science experience with ML tools.
• Production-grade ML deployments on cloud platforms (AWS/Azure/GCP).
• Experience with NLP techniques, vector databases, and LLM deployment.
• Ability to communicate complex concepts to diverse audiences.

Responsibilities

• Build and productionize customer data science workloads across domains.
• Develop LLM solutions on customer data (RAG, NLP querying).
• Advise data teams on architecture, tooling, and best practices.

Skills

Excellent communication

Customer-facing experience

Mentorship

Tools

Pandas

MLflow

Scikit-learn

Gensim

NLTK

TensorFlow

PyTorch

HuggingFace

LangChain

OpenAI

Spark

Databricks

Vector databases

Job description

Title: Senior ML Engineer(7+ years exp.)

About DataNimbus:

At DataNimbus, we are on a mission to redefine how organizations leverage Data and AI to drive growth, innovation, and effciency. Our pioneering products, such as DataNimbus Designer (a cloud-native ETL designer), datanimbus.io (a comprehensive data and integration platform), FinHub.ai (payment modernization platform) empower businesses to simplify complex workflows, adopt cutting-edge technology, and achieve sustainable scalability.

With headquarters in the U.S. and offces in India and Canada, DataNimbus operates globally, fostering a culture of responsible innovation, adaptability, and customer-centricity. We pride ourselves on being a trusted partner for customers navigating the complexities of Data+AI and payment modernization.

Why Join DataNimbus?

At DataNimbus, we believe in shaping a sustainable, AI-driven future while offering an environment that prioritizes learning, innovation, and growth. Our core values—Customer-Centricity, Simplicity, Curiosity, Responsibility, and Adaptability—are the foundation of our workplace, ensuring every team member can make a meaningful impact. Joining DataNimbus means being part of a dynamic team where you can

• Work with cutting-edge technologies and revolutionize workflows in Data+AI solutions.
• Contribute to solutions that are trusted by global businesses for their scalability, security, and efficiency.
• Grow personally and professionally in a culture that values curiosity and continuous learning.

If you’re passionate about innovation, ready to solve complex challenges with simplicity, and eager to make a difference, DataNimbus is the place for you.

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:

• 6years 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.
• 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] 5+ 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.

Interested?