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 practical insights and predictive intelligence.

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

• Transform reasoning models, vision-language models, and multimodal AI systems that integrate imagery, geospatial signals, and structured data into production-ready solutions.

• Create enterprise-grade training and experimentation frameworks featuring automated pipelines, experiment tracking, benchmarking, and reproducible evaluations.

• Develop synthetic datasets and testing frameworks to assess model performance, robustness, and edge-case scenarios.

• Collaborate with domain experts, software developers, product managers, and research partners to convert Earth intelligence challenges into actionable AI solutions.

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

• Implement and uphold production inference systems, encompassing monitoring, model versioning, retraining workflows, and performance assessment.

• Keep abreast of developments in foundation models, generative AI, multimodal learning, and reasoning systems, applying research advancements to practical applications.

• Uphold engineering standards through code reviews, documentation, experimental discipline, and collaborative problem-solving.

• Contribute to the development of next-generation Earth AI capabilities through partnerships with research institutions and technology collaborators.

⛳️ Requirements

• MS or PhD in Computer Science, Machine Learning, Artificial Intelligence, Applied Mathematics, or a related technical discipline, 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, including data processing, training automation, evaluation frameworks, and scalable inference.

• Direct experience in developing and deploying deep learning models in vision-language contexts, multimodal learning, reasoning models, large language models, computer vision, or geospatial AI.

• Strong programming proficiency in Python.

• Familiarity with contemporary ML frameworks such as PyTorch, TensorFlow, or JAX.

• Experience in constructing reproducible experimentation pipelines, including model evaluation, dataset versioning, and experiment tracking.

• Experience in deploying models in production environments using current cloud infrastructure and containerized systems.

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

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

• Must be a U.S. Person: U.S. citizen, permanent resident, Asylee, or Refugee.

• 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), including large-scale AI/ML infrastructure.

• 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) with company match.

• Mental health resources.

• Student loan repayment assistance.

• Adoption reimbursement.

• Pet insurance.

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

• Inclusive workplace.

• Reasonable accommodations for applicants with disabilities.