Senior AI Engineer, LeoLabs

• S. or M.S. in Computer Science, Artificial Intelligence, Machine Learning, Engineering, Mathematics, Physics, or equivalent experience
• 5-7 years of experience in software engineering, machine learning engineering, or applied AI roles
• Up-to-date familiarity with the latest developments in Agentic AI
• Strong proficiency in Python and modern ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn)
• Advanced experience with SQL and large-scale data processing
• Proven experience developing and deploying production-grade machine learning models
• Experience working with large-scale distributed data platforms (e.g., Databricks, Spark)
• Strong understanding of statistical modeling, machine learning algorithms, and experimental design
• Experience designing and implementing feature engineering pipelines and training workflows
• Familiarity with MLOps practices, including model versioning, monitoring, and lifecycle management
• Strong problem-solving skills and ability to translate ambiguous real-world problems into scalable AI solutions
• Excellent communication skills, with the ability to influence technical and non-technical stakeholders

Desirable

• We are seeking an experienced and mission-driven Senior AI Engineer to join LeoLabs’ growing Insights team
• You will play a critical role in designing, building, and operating AI- and machine learning-powered systems that enable real-time space domain awareness and drive customer-facing insights
• You will work at the intersection of machine learning, data engineering, and software engineering—developing scalable pipelines, deploying models into production, and integrating AI capabilities into operational systems
• This includes transforming large-scale sensor and orbital datasets into intelligent systems that detect atterns, identify anomalies, and generate predictive insights
• This role is highly hands-on and systems-oriented, with a focus on helping to define and drive LeoLabs’ utilization of the latest Agentic AI technology
• You will own the full lifecycle of AI solutions—from data and feature pipelines to model deployment, monitoring, and continuous improvement—while helping define best practices for applied AI across LeoLabs
• Within 1 Month, You’ll:
• Complete onboarding to gain deep familiarity with LeoLabs’ mission, products, and data ecosystem
• Set up development environments, data access, and ML tooling within the Databricks platform
• Review existing data pipelines, feature engineering workflows, and deployed models
• Begin contributing to model evaluation, analysis, or incremental improvements
• Within 3 Months, You’ll:
• Develop a strong understanding of LeoLabs’ data architecture, AI/ML use cases, and operational constraints
• Lead development of new models or enhancements to existing systems
• Design and implement feature pipelines and training datasets for key problem areas
• Partner with data engineering to improve data quality, scalability, and pipeline reliability
• Within 6 Months, You’ll:
• Own end-to-end delivery of AI/ML solutions, from problem framing through production deployment
• Deploy and monitor models in production, ensuring reliability and performance
• Optimize model performance through advanced feature engineering, tuning, and experimentation
• Mentor junior team members and contribute to team best practices
• Within 12 Months, You’ll:
• Act as a technical leader in applied AI/ML within the Insights team
• Drive adoption of best practices in model development, MLOps, and reproducibility
• Identify and lead high-impact Agentic AI initiatives that enhance space domain awareness capabilities