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Software Engineer III/IV – Machine Learning & Algorithms Engineer

Department: 4000 - Data and Technology
Location: Seattle

Software Engineer III/IV – Machine Learning & Algorithms Engineer

Our mission at the Allen Institute for Brain Science is to accelerate the understanding of how the human brain works in health and disease. Using a team science approach, we strive to drive technological innovations and discover fundamental brain properties through the integration of experiments and simulation. We generate large-scale neuroscience datasets, online search, visualization, and analysis utilities, and APIs. Our data is freely and openly shared with the public at www.brain-map.org.

We are seeking an exceptional, energetic and experienced machine learning and algorithms engineer who has a track record of building scalable and distributed production software. The ideal candidate has experience in implementing data architecture and pipelines to enable intelligent applications on top of petabytes of diverse data. We seek to lay an informatics architecture and a compute framework for brain science research.

The informatics architecture will support the whole data science life cycle from ingestion, mapping, refinement to publishing and serving, encompassing provenance of the data and integrate across datasets, modalities and scales from micro- to macro-scale and from raw data (sequences, images, time-series) to derived models (cell types, circuits, brain organization). You will be working with subject matter experts to gather requirements, assess different algorithms and methods for fit for purpose, implement rapid prototypes to flush and validate concepts. This role is part of a team doing big and open science. You will interact regularly with neuroscientists and work closely with a wide variety of engineers, collaborating in a large team working on new discoveries about the brain.

The Allen Institute believes that team science significantly benefits from the participation of diverse voices, experiences and backgrounds. High-quality science can only be produced when it includes different perspectives. We are committed to increasing diversity across every team and encourage people from all backgrounds to apply for this role.

Essential Functions

  • Work as part of the informatics solutions development team to define the informatics architecture for the Allen Institute for Brain Science products and related activities
  • Work with subject matter experts to gather requirements and use cases and design architecture and modules capable of scaling out to meet anticipated growth
  • Create robust and efficient data pipelines to extract and transform data to quantitative features, knowledge and visualization to support new interactive modes of engagement of the data
  • Analysis of current technologies and assess their fit for purpose
  • Implement rapid prototypes to flush out concepts and to obtain metrics supporting the fit for purpose. Responsibility includes identifying, curation and transforming relevant datasets
  • Develop and maintain documentation to clarify architecture requirements and rationale
  • Work with development teams to clarify requirements and rationale
  • Identify and build working relationships and partnerships with external collaborators, system vendors, and users
  • Support internal and external teams as they integrate heterogenous unstructured, semi-structured and well-structured data into the data pipelines and master repository
  • Participate in writing, presenting and reviewing strategic and operational reports

Required Education and Experience

  • Bachelor’s Degree in Machine learning, Statistics, Computer Science, Mathematics, Physics, or related field
  • Minimum 5 years of relevant experience in a software environment
  • Broad, deep and current knowledge of modern machine learning (ML) and algorithms techniques
  • Experience with advanced algorithms and ML development
  • Strong software development skills, with proficiency in Python and C++ preferred
  • Deep understanding of software development life cycle
  • Experience building information systems that incorporate production databases
  • Experience in operationalizing and optimizing machine learning (ML) methods and algorithms in a production environment
  • Experience in supporting ML models in production such as monitoring, retraining or tweaking for staleness and accuracy due to data changing, new data, assumptions etc.
  • Working experience in a cloud environment

Preferred Education and Experience

  • Experience with research in biological sciences
  • Advanced degree in Machine learning, Statistics, Computer Science, Mathematics, Physics, or related field
  • Familiarity with entire software toolchain, including source code management (git), build systems, debuggers, linkers, and profiling tools
  • Exceptional problem-solving abilities will be essential for success
  • Strong communication skills to concisely communicate to provide context, offers insights and minimizes misinterpretation

Physical Demands

  • Fine motor movements in fingers/hands to operate computers and other office equipment

Position Type/Expected Hours of Work

 

  • Allen Institute is a Washington State Employer. This role will be performed in Washington State. 
  • This role is currently able to work remotely, in Washington State, due to COVID-19 and our focus on employee safety. We continue to evaluate the safest options for our employees. As restrictions are lifted in relation to COVID-19, this role will return to work onsite. (Temporary to address COVID)

 

It is the policy of the Allen Institute to provide equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state or local law. In addition, the Allen Institute will provide reasonable accommodations for qualified individuals with disabilities.

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