Software Engineer [ Data Pipelines & Interface ]

About The Role We are hiring Software Engineers to build the data platform that powers our research and model‑development efforts. You will help design and maintain the systems that move data from acquisition through transformation and storage into reliable downstream interfaces for analytics, research workflows, model training, and long‑term archival use. This includes database design and administration, ETL/ELT pipelines, ingestion services, data modeling, schema evolution, observability, and performance optimization across both SQL and NoSQL systems. This role sits at the intersection of software engineering, data engineering, and scientific infrastructure. You will work closely with researchers, ML engineers, and infrastructure teams to ensure that our data systems are robust enough for production use, flexible enough for evolving research needs, and maintainable enough to serve as a foundation for years of scientific and engineering work. You will have substantial autonomy in shaping how our long‑lived scientific data platform is represented, administered, and evolved as the company scales. You’ll Thrive In This Role If You Are excited about working in a fast‑paced, production‑focused research lab that often requires switching between many hats Have significant software engineering experience and can move quickly without sacrificing rigor Are able to balance research goals with practical engineering constraints Enjoy pair programming and deeply collaborative work Are eager to learn more about machine learning research in a novel scientific domain Are enthusiastic to work at an organization that functions as a single, cohesive team pursuing large‑scale AI research Have ambitious goals for AI progress and are excited to create the best outcomes over the long term We Offer The chance to work on one of the most scientifically consequential AI projects being pursued today A small, world‑class team where your contributions directly shape the science and the company Competitive compensation and benefits, along with visa sponsorship Strong mentorship and career development Salary Range

$160,000 - $240,000 USD

Based on experience. We additionally offer a competitive equity package and comprehensive benefits, as well as visa sponsorship for international candidates. Minimum Qualifications Bachelor’s degree or equivalent experience in Computer Science, Machine Learning, Computational Neuroscience, or a related field Strong software engineering skills and strong working proficiency in Python and database query languages Experience designing, building, and maintaining production object stores and ETL/ELT pipelines Deep familiarity with relational and NoSQL database systems, including schema design, indexing, query optimization, and administration Experience designing durable data models and schemas for complex, evolving datasets Experience maintaining data platforms in production environments, including tools for monitoring, observability, troubleshooting, and incident response Experience building high‑throughput ingestion systems and optimizing data movement across storage, compute, and network boundaries Familiarity with workflow orchestration tools (e.g. Airflow, Dagster, Prefect) Experience collaborating closely with various teams simultaneously (e.g. research, ML, scientific, etc.) to translate ambiguous requirements into robust, consensus‑driven data pipeline specs Nice to Have Experience serving as a database administrator (DBA) or having substantial DBA‑style ownership of production data systems Experience with scientific, biomedical, behavioral, or neural datasets, especially where data provenance and long‑term reuse matter Experience with performance‑critical compiled or systems languages (e.g. Rust, Zig, C++) Experience with containerization, and scaling container orchestration (e.g. via Docker, Kubernetes) Experience with provisioning and managing distributed GPU compute infrastructure (e.g. via Ray, Dstack, Skypilot) Proficiency with MLOps platforms for experiment tracking and reproducibility (e.g. MLflow, W&B) Background in scientific computing, computational neuroscience, life sciences, or ML‑adjacent research environments #J-18808-Ljbffr Metamorphic