Machine Learning Architect

DataNimbus Inc.; Town of Texas (WI); Hybrid; USD 140,000 - 190,000; Full time

Job summary

DataNimbus Inc. seeks an experienced ML Architect to build and scale data science workloads, productionize models, and provide guidance on architecture, tooling, and best practices across the data science lifecycle.

You will develop LLM solutions on customer data, including RAG architectures over enterprise knowledge repositories and natural-language querying of structured data, while collaborating with teams on optimal tooling and processes.

Qualifications

• 6+ years hands-on data science experience in industry.
• Experience deploying production-grade ML on cloud platforms with drift monitoring.
• Databricks Certification or ML/Cloud AI Certification required, or 1+ years Databricks experience.

Responsibilities

• Build and scale customer data science workloads with MLOps best practices.
• Develop LLM solutions on customer data including RAG over knowledge bases.
• Advise data teams on architecture, tooling, and best practices across the lifecycle.

Skills

Pandas

MLflow

Scikit-learn

Gensim

NLTK

TensorFlow

PyTorch

Drift monitoring

Education

Graduate degree in CS/Engineering/Statistics/OR OR Operations Research

Tools

Databricks

AWS

Azure

GCP

Job description

Responsibilities:

• Build and scale customer data science workloads, applying MLOps best practices to productionize models across diverse domains.
• Develop LLM solutions on customer data, including RAG architectures over enterprise knowledge repositories, natural-language querying of structured data, and content generation.
• Advise data teams on architecture, tooling, and best practices across the data science lifecycle.

Requirements:

• 6+ years (ML Architect) of hands-on industry data science experience with pandas, MLflow, scikit-learn, gensim, NLTK, and TensorFlow/PyTorch.
• Proven experience deploying production-grade ML on AWS, Azure, or GCP, including drift monitoring.
• Databricks Certification or an ML/Cloud AI Certification required, or 1+ years of current, hands-on Databricks experience instead of certification.
• Graduate degree in a quantitative discipline (CS, engineering, statistics, or operations research) or equivalent practical experience.

Nice to Have:

• Apache Spark experience at scale.
• Deep Databricks platform expertise.