Senior / Lead ML(Ops) Software Engineer

Position Overview

As the Senior / Lead ML(Ops) Software Engineer at Atlas AI, you will be a key member of the core team responsible for defining, building, testing, and delivering our GeoAI platform. This platform enables both internal and external Data Scientists (DS) and Machine Learning Engineers (MLE) to implement Geospatial AI models. Reporting to the Head of Engineering, you will work closely with peer software engineers, domain experts, data scientists, machine learning engineers, product designers, and product marketers. Your role will be at the intersection of leading AI research activities and software engineering, advancing our product roadmap.

Key Responsibilities

• Design and Development: Own the design, development, deployment, and support of our cloud-scale training services for GeoSpatial Machine Learning models.
• Subject Matter Expertise: Ensure that the Software Engineering team builds and delivers solutions that effectively address how DS and MLE approach GeoSpatial problems in the real world.
• Collaboration: Engage with internal collaborators and end-use partners and customers to understand needs, plan solutions, and lead the development of deliverables.
• Feedback Loop: Close the feedback loop with Solutions, Engineering, and Innovation teams to deliver customer experience and market insights.
• Architecture: Architect and develop serverless solutions that integrate products within and across cloud platforms (e.g., GCP, AWS, Azure) to meet customer needs.
• API Development: Lead client-oriented API design and development, working with designers, product managers, and fellow engineers to build APIs supporting key functionality and use cases.
• Standards and Processes: Actively participate in improving engineering standards, tooling, and processes.
• Decision Making: Leverage your experience in early-stage startups to make informed decisions balancing speed and quality.

What You'll Bring

• Experience: Three or more years of recent work experience as a practicing Data Scientist or Machine Learning Engineer using PyTorch, sklearn, and lightgbm.
• Backend Engineering: Two or more years of recent work experience as a practicing Backend Software Engineer using Python, GDAL, and other GeoSpatial tools deployed in the cloud as serverless applications or orchestrated workflows.
• Earth Observation: At least three years of recent work experience building around Earth Observation use-cases.
• Technical Ownership: Demonstrable experience with Python, Pandas, PyTorch, GDAL, and building distributed computing infrastructure.
• Self-Starter: Comfortable working independently in an entrepreneurial, start-up environment.
• Communication: Exceptional interpersonal communication, both written and oral.

Preferred Experiences

• Applying Geospatial libraries and datasets at scale for user-facing applications.
• Developing enterprise PaaS and SaaS products.
• Working in early-stage startup environments.
• Developing on Google Cloud Platform.
• Comfort working in a distributed team environment.

Why Join Us

At Atlas AI, you'll be part of a dynamic team dedicated to making a tangible impact on the world. We bring together world-class scientific leadership in AI with top-notch engineering and data science disciplines to build rigorous, scalable systems for large enterprise customers. Our collaborative environment fosters innovation and empowers you to work on groundbreaking projects that drive real change, from advancing sustainable energy solutions to optimizing global supply chains for vulnerable communities.

We are a highly values-driven organization, guided by our core principles of Integrity, Innovation, Impact, Collaboration, and Empowerment. If you are passionate about using technology to solve critical global challenges and are eager to contribute to a mission-driven company, Atlas AI is the place for you. Join us and be at the forefront of innovation, helping to build a more resilient and equitable future.

Atlas AI is an equal opportunity employer. All applicants will be considered for employment regardless of race, color, national origin, religion, sex, age, disability, sexual orientation, gender identity, veteran or disability status.