Design and implement production ML features, close behavior gaps with common frameworks, investigate divergences, improve performance and stability, and document designs and tests for geospatial and large-scale ML workflows.
About Ocient:
Ocient is building OcientAIQ™ – a complete ecosystem for delivering trusted agentic AI solutions at petabyte scale, for the organizations that can't afford to get AI wrong. Our customers protect networks, secure nations, and power the global economy. The problems we solve are genuinely hard, and the work matters.
Founded in 2016 by the team that built Cleversafe (acquired by IBM in 2015), Ocient is headquartered in Chicago with a remote-first global team. We are a carbon-neutral company backed by leading investors including Greycroft, OCA Ventures, In-Q-Tel, and Buoyant Ventures.
Job Title: Senior Software Engineer - Machine Learning & Geospatial
Location: 100% Remote (US Based Only)
- We cannot sponsor or transfer any visas, of any kind, at this time*
Hiring Manager: Senior Engineering Manager
Estimated salary range: $165,000 to $190,000
- The salary offered for this position will be based on a candidate’s experience and skill demonstrated during interviews and other evaluations
Job Description:
We’re looking for a Senior Software Engineer to help evolve our Machine Learning capabilities, with a particular focus on closing feature gaps and behavioral differences relative to widely used ML frameworks (e.g., Spark ML, scikit-learn), while continuing to deliver new ML functionality.
This role is ideal for someone who enjoys working across model behavior, system design, and customer expectations — ensuring that ML features behave predictably, perform well at scale, and align with how users expect industry-standard tools to work.
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.
Ideal Qualifications:
- 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.
An Exceptional Candidate Will Have:
- 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.
What success looks like:
- Customers see fewer surprises when using ML features compared to familiar frameworks.
- ML behavior, defaults, and limitations are well-documented and intentional.
- Feature gaps are identified early, not discovered under customer pressure.
- You deliver across parity work and broader ML initiatives, balancing short-term needs with long-term quality.
Interview Requirements: All interviews are conducted via video and require candidates to have their camera on for the duration of the session. The use of video filters, face-altering effects, or virtual backgrounds is not permitted for security and verification purposes.
We are not open to using an agency or staffing company at this time. We do not accept unsolicited agency or staffing resumes and we are not responsible for any fees related to unsolicited resumes.
Ocient is an equal employment opportunity employer. All qualified applicants will receive consideration for employment without regard to race, creed, color, religion, sex (including pregnancy status), sexual orientation, gender identity, national origin or ancestry, ethnicity, citizenship status, age, physical or mental disability, veteran status, marital status, parental status, genetic information, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, please contact [email protected] for more information.
All official Ocient job postings and recruiting communications will come directly from our team via our Careers page, LinkedIn, or from an ocient.com email address. If you receive communication about a role from any other source, please treat it with caution and direct questions to [email protected].
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