Machine Learning Engineer

Senior Machine Learning Engineer / ML Architect | Remote

Redefining how enterprises harness Data & AI

We're building enterprise-scale Azure data platforms that power analytics, reporting, and AI-driven transformation for organizations rethinking how they work with data. If you want your ML work to ship into production — not sit in a notebook — this is that role.

Why This Role Matters

We help organizations simplify complex workflows and adopt cutting-edge technology at scale. Our data science and MLOps practice sits at the center of that mission — turning customer data into deployed, monitored, production-grade AI systems.

What You'll Do

• Build and scale customer data science workloads, applying MLOps best practices to productionize models across diverse domains
• Develop LLM solutions on customer data — 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

What You Bring

• 4–6 years (Senior ML Engineer) or 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 in lieu of certification
• Graduate degree in a quantitative discipline (CS, Engineering, Statistics, Operations Research) or equivalent practical experience

Nice to Have

• Apache Spark experience at scale
• Deep Databricks platform expertise

Why Join Us

• 100% Remote — work from anywhere
• Work on cutting-edge LLM/RAG systems for real enterprise data, not toy demos
• High-impact team shaping how large organizations adopt AI