Applied Scientist - Remote Sensing & Analytics

Orbital Sidekick (OSK) is revolutionizing how the world understands and interacts with our planet. We are the leading hyperspectral satellite data and analytics company building the most advanced space-based infrastructure and proprietary "Spectral Intelligence™" platform. Our constellation of Global Hyperspectral Observation Satellites (GHOSt™) delivers unparalleled, persistent monitoring capabilities, capturing an unparalleled 500 bands of light to reveal the chemical fingerprints of targets on Earth. We provide actionable insights to critical sectors including Energy, Mining, Agriculture & Forestry, Environmental & Emergency Monitoring, and Defense & Security, helping our clients optimize sustainable operations, mitigate risk, and enhance situational awareness globally.

We're seeking an Applied Machine Learning Engineer who thrives at the intersection of theory and practice. You'll operate as both an applied scientist and systems builder, taking end-to-end ownership of ML solutions. We're looking for someone who can spot inefficiencies, architect solutions, and build the tools needed to scale our capabilities.

This role is perfect for builders who are equally comfortable diving into ML theory, developing internal tools from scratch, and architecting production pipelines. You'll have the autonomy to identify gaps, propose solutions, and drive them to completion in a fast-moving startup environment.

• Identify and solve real problems: Collaborate with scientists to understand needs, then design and build the infrastructure to address them
• Build production ML systems: Develop robust pipelines using orchestrators (Prefect, Airflow, Dagster) that move models from research to production
• Create internal tools: Build developer-friendly tools that accelerate team productivity and model development workflows
• Own the ML infrastructure: Design and maintain model repositories, experiment tracking, monitoring, and deployment systems
• Bridge theory and practice: Apply ML theory to solve practical problems while building scalable, production-ready solutions
• Optimize for impact: Focus on cloud resource optimization, model performance, and system reliability that directly supports product goals
• Drive continuous improvement: Establish CI/CD, automated testing, and monitoring systems that ensure robust, reliable deployments

• 3+ years of experience as an applied ML engineer or research engineer
• BS, MS, or PhD in Computer Science, Engineering, Physics, Mathematics, or related field
• Theory meets practice: Strong foundation in ML theory combined with hands-on experience building production systems
• Full-stack mindset: Comfortable developing internal tools, APIs, and user interfaces that solve real problems
• Pipeline expertise: Proven experience architecting and maintaining complex workflows in orchestration frameworks
• Ownership mentality: Track record of identifying needs, proposing solutions, and driving projects to completion
• Production experience: Hands-on experience deploying, monitoring, and maintaining ML models in cloud environments (AWS)

• Python, PyTorch, Weights & Biases, MLFlow, DVC, Ray, Dask
• Experience with workflow orchestrators (Prefect, Airflow, Dagster)
• Cloud platforms (AWS) and containerization (Docker, Kubernetes)
• Software engineering best practices (testing, CI/CD, version control)

• Experience building internal tools that other engineers love to use
• Background in geospatial analytics, remote sensing, or hyperspectral data
• Open source contributions or side projects that demonstrate building instincts
• History of taking research prototypes to production scale
• Passion for environmental applications and real-world impact

• Pioneering Technology: Be part of a company at the cutting edge of hyperspectral technology, making a real impact on industries and global challenges.
• Growth Opportunity: Join a rapidly expanding team with ample opportunities for professional development and career advancement within the sales organization.
• Impactful Work: Contribute to solutions that address critical issues in sustainability, security, and resource management.
• Collaborative Culture: Work alongside a passionate and innovative team of engineers, data scientists, and industry experts.

Location: San Francisco, CA (Hybrid model with a strong emphasis on collaboration in the office).

ITAR Requirements: U.S. Government space technologies export/ITAR regulations apply here, applicant must be a U.S. citizen or a lawful permanent resident of the U.S., or eligible to obtain the required authorizations from the U.S. Department of State.

Orbital Sidekick is committed to building a community where everyone belongs and we invite people from all backgrounds to apply. We are an equal opportunity employer committed to providing employment opportunities regardless of race, religious creed, color, national origin, ancestry, physical disability, mental disability, medical condition, marital status, sex, sexual orientation, gender, gender identity, gender expression, pregnancy, age, military or veteran status, or any other protected classification, in accordance with applicable federal, state, and local laws.