Senior ML Engineer

DataNimbus; Hyderabad; On-site; INR 1,800,000 - 3,000,000; Full time

Job summary

DataNimbus is seeking a senior data scientist to lead the design and deployment of data science workloads across multiple domains. You will build production-grade ML systems and develop LLM-based solutions on customer data, including RAG architectures and NLP-driven data queries.

You will advise data teams on architecture, tooling, and best practices, and provide technical mentorship to the ML community. Strong collaboration and willingness to teach are essential.

Qualifications

• 6+ years of hands-on data science experience with standard ML tools.
• Experience building production-grade ML deployments on cloud platforms (AWS/Azure/GCP).
• Experience with NLP: vector databases, fine-tuning LLMs, deployment with HuggingFace/LangChain/OpenAI.
• Graduate degree in a quantitative field or equivalent practical experience.
• Ability to communicate complex concepts to varied audiences.
• Demonstrated collaboration and continuous learning mindset.
• Experience with Apache Spark for large-scale data processing.
• Experience with the Databricks platform.
• 5+ years in customer-facing pre-/post-sales roles.
• Ability to meet training/role outcomes within 3 months of hire.

Responsibilities

• Build and scale customer data science workloads across domains.
• Develop LLM solutions on customer data (RAG, NL querying, content generation).
• Advise data teams on architecture, tooling and best practices.
• Provide technical mentorship to ML communities.

Skills

Data science (6+ yrs)

Production ML deployments

NLP/LLMs

Technical mentorship

Cross-functional collaboration

Spark processing

Databricks

Pre-/Post-sales experience

Training & outcomes within 3 months

Education

Master's or PhD in CS/Engineering/Statistics

Tools

Pandas

MLflow

scikit-learn

gensim

nltk

TensorFlow/PyTorch

HuggingFace

LangChain

OpenAI tools

Apache Spark

Databricks

Job description

Responsibilities

• 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 topics such as architecture, tooling, and best practices.


• Provide technical mentorship to the larger ML Subject Matter Expert community.

Requirements

• 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 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.


• Experience working with Apache Spark to process large-scale distributed datasets.


• Experience working with the Databricks platform.


• 5+ years of 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.

This job was posted by Nitya Raj from DataNimbus.