Job Description:
• 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 – Evaluating emerging ML frameworks, architectures, and tools to accelerate innovation
Requirements:
• 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 (e.g., 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 containerized 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.
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 defense innovation
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