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Senior Software Engineer - ML Platform

About Overland AIFounded in 2022 and headquartered in Seattle, Washington,Overland AIis transforming land operations for modern defense. The company leverages over a decade of advanced research in robotics and machine learning, as well as a field-test forward ethos, to deliver combined capabilities for unit commanders. Our OverDrive autonomy stack enables ground vehicles to navigate and operate off-road in any terrain without GPS or direct operator control. Our intuitive OverWatch C2 interface provides commanders with precise coordination capabilities essential for mission success.Overland AI has secured funding from prominent defense tech investors including 8VC and Point 72, and built trusted partnerships with DARPA, the U.S. Army, Marine Corps, and Special Operations Command. Backed by eight-figure contracts across the Department of Defense, we are strengthening national security by iterating closely with end users engaged in tactical operations.

What You'll DoDesign and implement Overland AI’s infrastructure to enable training, evaluating, and deploying machine learning/deep learning models for autonomous vehicles, including:Writing software to enable the fast curation and creation of high-quality labels for various robotics tasks using state-of-the-art AI and human feedback.Design and implement data processing pipelines, dashboards, and visualization tools for model evaluation and dataset insights.Design and implement distributed workflows, including data processing, training, and evaluation (on-prem and cloud).Be responsible for on-prem and cloud infrastructure including data storage, compute resources and access.Leverage CI/CD practices to make the machine learning lifecycle efficient and reproducible.Collaborate closely with experts in Perception and Behavior Planning.Minimum QualificationsBachelor's degree in computer science, engineering, or related discipline and 5+ years of relevant experienceStrong programming skills in Python, including unit and integration testingStrong understanding of data processing pipelines for training ML modelsExperience with batch processing tools, such as Spark, Beam, Ray, etc.Experience with data stores and databases, such as MinIO, Postgres, Redshift/BigQuery, etc.You excel in a small-team atmosphere, taking ownership of problems and working with your colleagues to solve problems across disciplines.Desired Experience & QualificationsPrior industry experience in a similar software infrastructure or MLOps teamContributions to any related open source software projectLocation:The preferred location for this position is Seattle, WACompensation And BenefitsPay Range:Pay Range:$200,000 - $240,000 annuallyActual level and base salary will bedeterminedon a case-by-case basis and may vary based on the following considerations: job-related knowledge and skills, education, and experience.Overland AI believes in creating a work environment that you look forward to embracing every day. Benefits incldue:Equity compensationBest-in-class healthcare, dental and vision plans.Flexible PTO401k with company matchParental leaveMonthly wellness stipendOne-time workplace & productivity reimbursementOverland AI is an Equal Opportunity Employer. We do not discriminate on the basis of race, color, religion, creed, sex, sexual orientation, gender identity or expression, national origin, age, marital status, disability, genetic information, protected veteran or military status, or any other status protected by applicable law.This position may involve access to export-controlled technology. Employment is contingent on the ability to comply with U.S. export control laws.Overland AI provides reasonable accommodations for qualified individuals with disabilities and disabled veterans during the application process. Please contact [peopleops@overland.ai]to request an accommodation.

CompanyRemote
Senior Software Engineer - ML Platform
$100,000 – $150,000Published by Company
Overland AI · Unknown · Seattle, WA · $200,000 - $240,000

About Overland AI

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$100k – $150kCompany · Remote