Software Engineer II

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The mission of the Allen Institute is to understand the principles that govern life, and to advance health. Our creative and multi-dimensional teams focus on answering some of the biggest questions in bioscience. We accelerate foundational research, catalyze bold ideas, develop tools and models, and openly share our science to make a broad, transformational impact on the world.

The mission of the Allen Institute for Neural Dynamics is focused on fundamental discoveries in systems neuroscience. We are interested in how the brain builds our understanding of the complex world to guide the flexible behaviors that address our biological needs. The answers will be in terms of defined neuron types and circuits interacting across the whole brain and body. We will develop next-generation methods and theories and employ a team-based approach to discovery neuroscience.

Knowledge, data, models, and tools will be widely shared to support the development of therapies for brain disorders.

We are seeking a motivated, team-oriented engineer to build and maintain data processing pipelines for multimodal data, including measurements (optical and electrical) of neural activity and behavioral video. The engineer will ensure that the pipelines produce high quality outputs ready for data-driven discovery, with rich metadata and building on high-performance, cloud-compatible file formats. The pipelines will be robust, open-source, and modular to ensure they are sustainable and usable by the broader community.

The engineer will develop automated quality control (QC) for raw and processed data, including reports and dashboards to deliver rapid feedback to scientists. With the goal of scaling scientific workflows, the engineer is expected to collaborate with engineering teams working on scientific instrumentation and infrastructure.

At the Allen Institute, we believe that science is for everyone – and should be open to everyone. We are dedicated to combating biases and reducing barriers to STEM careers more broadly.

We also believe that science is better when it includes different perspectives and voices. We strive to make the Allen Institute a place where everyone feels like they belong and are empowered to do their best work in a supportive environment.

We are an equal opportunity employer and strongly encourage people from all backgrounds to apply for our open positions.

Essential Functions

• Develop state-of-the-art, large-scale data processing pipelines on-prem and in the cloud
• Adopt and contribute to open-source tools, including data analysis methods and metadata standards for scientific data
• Develop and benchmark data processing algorithms to extract information from biological images and time series data
• Collaborate with teams of scientists, project managers and software engineers within the Allen Institute and external partners
• Participate in institute-wide initiatives, workshops, and seminars to promote engineering excellence, collaboration and knowledge sharing

Note:

Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. This description reflects management’s assignment of essential functions; it does not proscribe or restrict the tasks that may be assigned.

Required Education and Experience

• Bachelor’s degree in engineering, physics, biology, mathematics, or a related field; or equivalent combination of education and experience
• Minimum 1 year of work experience with Python

Preferred Education and Experience

• 2 + years experience with Python
• Experience with Git version control (e.g., Git Hub, Git Lab, Bitbucket) and CI/CD pipelines (e.g., Jenkins, Git Hub Actions, Git Lab CI)
• Experience with data structures, algorithms, and software design principles
• Experience developing data processing algorithms for biological data – digital signal processing, applied mathematics, linear algebra, and optimization
• Experience training machine learning models for processing biological data
• Experience with and strong interest in agentic software…