Senior Software Engineer - Machine Learning & Geospatial

Ocient is a data analytics software solutions company that enables always-on, compute-intensive analysis of complex, large-scale data. They are seeking a Senior Software Engineer to help evolve their Machine Learning capabilities, focusing on closing feature gaps and ensuring ML features behave predictably and perform well at scale.

Responsibilities:

• Design and implement machine learning features used in production customer workflows
• Help identify and close feature and behavior gaps between our ML capabilities and common frameworks (e.g., Spark ML, scikit-learn)
• Proactively evaluate semantic differences, defaults, and edge cases that could surprise customers
• Partner with product, architects, and customer-facing teams to anticipate upcoming customer needs and gaps
• Investigate and resolve issues where ML behavior diverges from user expectations (e.g., model output, metrics, configuration semantics)
• Contribute to other ML initiatives including new models, metrics, performance improvements, and infrastructure work
• Analyze and improve the performance of existing ML code, balancing correctness and stability with customer facing latency
• Write clear design docs, tests, and documentation to make behavior explicit and prevent regressions

Requirements:

• 5+ years of experience building production software systems
• Strong proficiency in at least one backend or systems language (e.g., C++, Java, Scala)
• Experience implementing or integrating machine learning models in production
• Familiarity with ML libraries or frameworks such as Spark ML, scikit-learn, XGBoost, or similar
• Strong instincts around correctness, edge cases, and behavioral consistency
• Ability to work across teams and codebases to turn ambiguous requirements into concrete solutions
• Experience comparing or validating behavior across multiple ML frameworks
• Experience with large-scale data systems or analytical databases
• Familiarity with distributed execution, performance tuning, or numerical stability
• Understanding of spherical geometry and its application to geospatial analytics