PL Network


ML Infrastructure Engineer



Software Engineering, Other Engineering, Data Science
Los Angeles, CA, USA
Posted on Tuesday, June 25, 2024
Forest Neurotech is seeking a ML Infrastructure Engineer to work on the development of a neurotechnology research platform for the world's first minimally invasive, ultrasound-based neural implant.

About Forest Neurotech

Forest Neurotech is developing an ultrasound based BCI and software platform with the aim of catalyzing breakthroughs in both the understanding and personalized treatment of the human brain. Ultrasound is capable of measuring and stimulating brain-wide activity in a minimally invasive manner. This opens new avenues for research into personalized therapies across a range of psychiatric and cognitive disorders. To accelerate these efforts, Forest has secured a partnership with Butterfly Network with exclusive access to the only FDA approved and mass produced Ultrasound-on-Chip. As a non-profit Focused Research Organization (FRO), Forest Neurotech has the freedom to focus solely on advancing science and engineering for the public good. Pioneered by Convergent Research, a member of the Schmidt Futures Network, FROs are designed to overcome key technological bottlenecks for the advancement of science and medicine. Forest was recently featured in Wired and IEEE. Visit www.forestneurotech.org to learn more.


Forest is structured as a Focused Research Organization (FRO). FROs are a new type of startup-nonprofit hybrid organization for pursuing advanced scientific projects not achievable in academia or a VC-backed startup. As an FRO, Forest can execute with the intensity and focus of a founder-led startup, but with the mission and operational flexibility to maximally advance neurotechnology and benefit society rather than focusing on near-term company value.


Forest has five years of runway. Salaries will be competitive with industry.


This is a full time role based on-site in downtown Los Angeles, CA.

Job Description

Forest Neurotech is seeking a passionate and talented ML Infrastructure Engineer to join our innovative team. In this role, you will play a critical part in developing and managing the core infrastructure that enables us to advance our groundbreaking neurotechnology research. Your expertise will enable the processing and analysis of petabyte-scale datasets, supporting the development of our minimally invasive, ultrasound-based neural implant. By contributing to our mission, you will help catalyze breakthroughs in understanding and treating psychiatric and cognitive disorders, ultimately improving brain health and personalized therapies for individuals worldwide.

Key Responsibilities

  • Develop, manage, and optimize end-to-end pipelines for both machine learning and data science projects, ensuring integration and automation of tasks such as data collection, transformation, analysis, and model deployment
  • Implement experiment tracking solutions to document, version, and reproduce experiments, facilitating collaboration, reproducibility, and transparency
  • Enable proper data versioning, storage, and management practices, ensuring data integrity and quality to support the needs of both ML engineers and scientists
  • Manage and optimize on-premises compute and storage systems for efficient processing and analysis of large datasets
  • Implement security best practices to protect data, models, and analytical solutions
  • Collaborate with neuroscientists and engineers to design experiments and analyze data to improve ultrasound methods and the understanding of brain activity patterns and their modulation through focused ultrasound
  • Provide technical guidance and support to the team on data-related issues and best practices


  • Master's degree in Computer Science, Data Science, or a related field. Candidates with experience in data-intensive fields such as astrophysics or high-frequency trading are highly desired
  • 3+ years of experience in ML infrastructure, data engineering, or a related field with a focus on high-performance computing and large-scale data management
  • Proficiency in programming languages commonly used in ML and data engineering, particularly Python
  • Experience with workflow orchestration tools like Prefect, Kedro, and Apache Airflow
  • Experience with experiment tracking and management tools like MLFlow, Weights & Biases, or similar platforms
  • Familiarity with ML frameworks including TensorFlow, PyTorch, and scikit-learn
  • Knowledge of data processing frameworks such as Apache Spark and Hadoop
  • Strong knowledge of Linux operating systems and experience with high-performance computing environments
  • Experience managing on-premises compute and storage systems, including job schedulers like Slurm
  • Solid understanding of networking, data security, and Linux system administration
  • Expertise in DevOps practices, including continuous integration/continuous deployment (CI/CD) pipelines and version control systems like Git
  • Strong skills in data management, including data versioning, storage, and ensuring data quality and consistency
  • Ability to work collaboratively with a multidisciplinary team of neuroscientists, engineers, and data scientists

Please provide a CV, cover letter briefly highlighting the project you are most proud of, and links to relevant profiles (LinkedIn, GitHub) or publications.