Data Management Specialist
Modern Intelligence is building the foundational AI for defense. Over the next decade, the US military and our allies will 10x the number of sensors we field to see the battlefield but cannot 10x the number of service members manually watching sensor feeds – The way sensor data is processed today.
Our first product Cutlass is an automated targeting AI that detects, remembers, and shares targets in real time by watching any sensor on any network – Delivering modular, insightful knowledge of where adversaries are on any drone, ship, vehicle, satellite, or command center. Our AI research helps Cutlass learn targets with little data, little compute, and the most intuitive, humane knowledge. Cutlass has been tested in more than DOD exercises on sea, land, and air and industry partnerships.
We have raised more than $12M from investors such as Bedrock, Vine, Contrary, Air Street, Caffeinated, Champion Hill, Swell, Myelin and others and our team members come from backgrounds like Naval Special Warfare, USAF, biotech, classified prime projects, and ML research programs.
We are gathering the most ambitious AI researchers, software engineers, and mission leaders in defense because we believe defense is the future of defense, and defense is the future of AI.
This role requires US citizenship due to federal contracting guidelines.
Job Description
We are looking for a detail-oriented and technically skilled Data Management Specialist to oversee the lifecycle of our video and image data from pre-processing and annotation, to postprocessing and model deployment. This role is crucial in ensuring the efficiency and quality of our data pipelines and machine learning workflows. Responsibilities
Manage training and operational documentation for both outsourced and in-house labelers.Manage current data annotation platform: video uploads, dataset creation, design custom ontologies, and maintain labeling standards.Oversee rigorous data QA/QC and provide feedback for annotation corrections.Automate and optimize robust pre-processing and post-processing pipelines for video and image data.Build data visualization tools, and expand existing tools for data manipulation, including file conversion, down sampling, clipping, and re-stitching video clips.Manage and mentor a small team of interns in data annotation, data management and maintaining current data scraping and processing tools.Lead technical meetings with internal teams and external data annotation teams to discuss updates and feedback.Create a new data architecture for all current data, manage and clean data inventory to enhance data transparency and accessibility, and refactor old data paths.Develop and implement CI/CD integrations for regular data audits and reporting.Establish and maintain MLOps strategies to integrate data, code, and models within a controlled ecosystem.Oversee the CI/CD pipelines for ML data to ensure reproducibility and version control.Write and maintain documentation for data pipelines, data architecture, and data annotation.Coordinate with labeling companies and manage project scoping for grants and contracts.Explore and implement cloud solutions for data storage and management. Benefits:
Full medical, dental, and vision benefitsDiscretionary PTOPaid Parental LeavePerformance Bonuses Catered lunch Requirements:
Advanced proficiency in Python, especially in data processing and automation tasks.Strong experience with video data management and processing.Experience with SQL for database management.Familiarity with MLOps practices and CI/CD methodologies.Familiarity with AWS or other cloud platforms.Excellent communication skills for effective training and collaboration.Previous start-up experience, or comfort working in a fast-paced environment. Qualifications:
Master’s degree in Computer Science, Data Science, or a related field. At least 3 years of experience in data management or ML operations, with a demonstrated track record.
This role requires US citizenship due to federal contracting guidelines.
To apply, send a resume or CV to hiring@modernintelligence.ai. Cover letters are not necessary, but are welcome if they provide meaningful information about you as a candidate that is not conveyed otherwise.
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