AI/ML Manager

Join to apply for the AI/ML Manager role at LeoLabs Get AI-powered advice on this job and more exclusive features. Why LeoLabs? At LeoLabs, we’re building the living map of activity in space. Through our proprietary global radar network and AI-enabled analytics platform, we collect millions of measurements daily on more than 241,000 objects in low earth orbit (LEO). Our radar‑powered intelligence protects billions in assets, monitors adversarial behaviour, and ensures safe operations for commercial and governmental missions. We’re not just building technology, we are redefining global security, safety, and transparency in space. As orbital activity accelerates and threats grow more complex, LeoLabs is a trusted partner for Space Domain Awareness, Space Traffic Management, and Satellite Operations for top‑tier space operators and allied defence organisations. If you’re looking to work on mission‑critical challenges at the forefront of aerospace, national security, and AI, your impact starts here. What You’ll Do: Lead by doing – design, build, and deploy production‑grade ML models and pipelines while mentoring a small team of engineers and data scientists. Architect scalable AI systems – build end‑to‑end AI solutions from data ingestion through inference, ensuring reliability, observability, and performance across distributed environments. Collaborate cross‑functionally – work closely with product, data, and platform engineering teams to translate complex business challenges into ML‑driven solutions. Own the ML lifecycle – oversee model training, validation, deployment, and continuous monitoring using modern MLOps practices and tooling. Experiment and innovate – apply state‑of‑the‑art machine learning and generative AI techniques to improve product capabilities and customer outcomes. Establish best practices – set standards for reproducible research, model explainability, and responsible AI implementation. Optimize performance – tune models and infrastructure for accuracy, latency, and cost. Provide technical leadership and mentorship – guide architectural decisions, design reviews, and technical standards. Communicate impact – present insights to technical and non‑technical stakeholders, influencing product strategy through data‑driven recommendations. Stay ahead of the curve – evaluate emerging ML frameworks, architectures, and tools to accelerate innovation. Qualifications Bachelor’s degree in computer science, applied mathematics, physics, or a related technical field. 6+ years in software engineering, data science, or applied machine learning. 2+ years managing technical teams. Proven experience building and deploying ML models using Python, PyTorch, TensorFlow, or similar frameworks. Experience with data pipelines and orchestration tools such as Databricks. Strong background in sensor data processing, time‑series analysis, and computer vision or tracking algorithms. Experience deploying ML models in production environments, including cloud or containerised deployments (AWS GovCloud, Azure Gov, or on‑prem). Demonstrated leadership, mentorship, and project execution skills. Excellent communication and technical documentation skills. Eligibility for US security clearance. Preferred Qualifications Advanced degree (MS or PhD) in machine learning, aerospace engineering, or a related field. Familiarity with orbital mechanics concepts such as TLEs, ephemerides, conjunction analysis, or space object classification. Experience integrating LLMs, transformers, or generative AI solutions into production systems. Familiarity with vector databases, retrieval‑augmented generation (RAG), or AI agent frameworks. Experience with real‑time inference, model optimisation, and edge deployment. Active US security clearance. Within 1 Month Gain a deep understanding of the company’s ML infrastructure, datasets, and product goals. Review existing models, pipelines, and code bases. Establish trust and cadence with the engineering and data teams. Deliver a proposal outlining quick wins for improving model performance or process efficiency. Within 3 Months Take over day‑to‑day management of the Insights AI/ML team. Lead implementation of at least one model improvement or new ML feature from design through deployment. Define standards for model reproducibility, code quality, and experiment tracking. Partner with data engineering to ensure robust, high‑quality data pipelines. Within 6 Months Own the end‑to‑end lifecycle of multiple ML systems and features. Demonstrate measurable impact such as improved model accuracy, reduced latency, or new product capability. Mentor team members and contribute to hiring and growth of the AI/ML capability. Within 12 Months Lead the roadmap for AI/ML initiatives across the product line. Establish best practices for experimentation, model governance, and continuous improvement. Deliver multiple ML‑powered features in production with clear business ROI. Serve as the technical authority and go‑to‑expert for all AI‑related initiatives within the organisation. Perks & Benefits Global workforce: flexible remote/hybrid opportunities. Work on complex, meaningful missions with real‑world impact. Unlimited paid time off for most roles. Competitive salary and equity packages. Comprehensive health, dental, and vision coverage. Access to the forefront of commercial space operations and defence innovation. All qualified applicants will receive consideration for employment without regard to race, colour, religion, sexual orientation, gender identity, national origin, disability, or status as a protected veteran. Seniority Level Mid‑Senior level Employment Type Full‑time Job Function Accounting / Auditing and Finance Industries Defense and Space Manufacturing #J-18808-Ljbffr