Principal Applied AI Scientist

This is a fully remote position, open to applicants in United States.

📋 Description

• Design, develop, and implement AI-driven applications that convert extensive geospatial data into actionable insights and predictive intelligence.

• Construct and manage comprehensive AI/ML pipelines that encompass data ingestion, preprocessing, feature engineering, model training, evaluation, and production inference.

• Operationalize reasoning models, vision-language models, and multimodal AI systems that integrate imagery, geospatial signals, and structured data.

• Develop enterprise-level training and experimentation frameworks featuring automated pipelines, experiment tracking, benchmarking, and reproducible evaluation processes.

• Generate synthetic datasets and testing frameworks to assess model performance, robustness, and behavior in edge cases.

• Collaborate with domain experts, software engineers, product managers, research collaborators, and technology partners.

• Enhance models and inference systems for scalability, latency, cost-effectiveness, and reliability on contemporary cloud infrastructure.

• Implement and sustain production inference systems, including monitoring, model versioning, retraining workflows, and performance tracking.

• Monitor advancements in foundation models, generative AI, multimodal learning, and reasoning systems, translating them into practical applications.

• Uphold engineering standards through code reviews, documentation, disciplined experimentation, and collaborative problem-solving.

• Contribute to the development of next-generation Earth AI capabilities.

⛳️ Requirements

• U.S. Person status is required: U.S. citizen, permanent resident, Asylee, or Refugee.

• MS or PhD in Computer Science, Machine Learning, Artificial Intelligence, Applied Mathematics, or a related technical field, or equivalent practical experience.

• Over 5 years of experience in building and deploying machine learning systems in production settings.

• Proven experience in designing and delivering end-to-end ML pipelines.

• Experience in developing and deploying deep learning models.

• Familiarity with vision-language models, multimodal learning, reasoning models, large language models, computer vision, or geospatial AI.

• Strong programming skills in Python.

• Proficiency with PyTorch, TensorFlow, or JAX.

• Experience in creating reproducible experimentation pipelines.

• Expertise in deploying models using modern cloud infrastructure and containerized systems.

• Knowledge of distributed training, large-scale data processing, and model optimization techniques.

• Ability to collaborate effectively across research, engineering, and product teams.

• Typically requires 8 years of related experience with a Bachelor's degree; or 6 years with a Master's degree; or a PhD with 3 years of experience; or equivalent experience.

• Preferred: experience with geospatial data, remote sensing, satellite imagery, or Earth observation systems.

• Preferred: experience in building or fine-tuning foundation models, multimodal models, or agentic AI systems.

• Preferred: familiarity with Google Cloud Platform (GCP).

• Preferred: experience in implementing model monitoring, evaluation pipelines, and automated retraining systems.

• Preferred: contributions to open-source AI projects, research publications, or patents.

🏝️ Benefits

• Robust 401(k) plan with company matching.

• Mental health resources available.

• Assistance with student loan repayments.

• Reimbursement for adoption expenses.

• Pet insurance coverage.

• Incentive eligibility based on contributions, company performance, and/or individual results achieved.