Scientific Data Engineer – Image-Based Machine Learning

Scientific Data Engineer – Image-Based Machine Learning

The mission of the Allen Institute for Cell Science is to create multi-scale visual models of cell organization, dynamics, and activities. Our approach encompasses large-scale data collection, observation, theory, and predictions to understand cellular behavior in normal and pathological contexts. As a division within the Allen Institute, the Allen Institute for Cell Science uses a team-oriented approach, focusing on accelerating foundational research, developing standards and models, and cultivating new ideas to make a transformational impact on science.

The goal of the Computational Cell Science team is to develop scalable, quantitative image-based analysis frameworks of cell organization, activity, and function. This Scientific Data Engineer position will contribute to developing and implementing Machine Learning solutions for the quantitative analysis of complex microscopy images. This Engineer will work closely with our interdisciplinary team of experimental and computational scientists. This role offers a unique opportunity to gain hands-on experience in both traditional Machine Learning techniques and cutting-edge deep learning models in the context of cell biology.

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 closely with other Data Engineers and scientists to design and implement Machine Learning pipelines tailored for the development of microscopy image-based analysis frameworks
• Preprocess and clean large-scale microscopy datasets, ensuring data quality and integrity for downstream analysis
• Develop, optimize, and fine-tune Machine Learning models, including traditional algorithms and deep learning architectures and validate results in application-appropriate manner
• Participate in code reviews and contribute to the development of efficient and maintainable codebases
• Work closely with other teams in the institute to scale-up analysis protocols into a high throughput computational pipeline
• Ensure seamless integration and sharing of resources and data across teams
• Stay updated with the latest advancements in Machine Learning and image analysis techniques, and proactively propose innovative solutions
• Maintain rigorous quality control standards
• Maintain meticulous records and work closely with other scientists to coordinate complex experiments
• Adherence to SOPs, GLPs and regulatory requirements

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

• Bachelors Degree in any science, computation, or engineering field or related degree

Preferred Education and Experience

• Masters in any science, computation, or engineering field or related degree
• Experience in Machine Learning and image analysis
• 1+ years hands-on experience in Python
• Hands on experience either from internships or undergraduate research in developing and debugging deep learning models
• Experience with traditional Machine Learning techniques (e.g., SVM, Random Forest, etc.) and deep learning frameworks (e.g., TensorFlow or PyTorch)
• Programming proficiency in languages such as Python, with experience in data manipulation libraries (e.g., NumPy, Pandas) and Machine Learning libraries
• Experience with developing or contributing to open-source tools/packages
• Experience utilizing software engineering practices such as version management, build management and testing, and basic knowledge of version control using github
• Experience working in a multi-disciplinary environment in academic or industrial settings
• Excellent interpersonal skills
• Ability to work both independently and in a collaborative, multi-disciplinary environment
• Careful attention to detail

Work Environment

• May enter laboratory environment, including potential exposure to lasers, biohazards

Physical Demands

• Fine motor movements in fingers/hands to operate computers and other office equipment; repetitive motion with lab equipment

Position Type/Expected Hours of Work

• This role is currently able to work in a hybrid work environment. We are a Washington State employer, and any remote work must be performed in Washington State.

Annualized Salary Range

• $77,250 - $108,150 *

• Final salary depends on the required education for the role, experience, level of skills relevant to the role, and work location, where applicable.

Benefits

Employees (and their families) are eligible to enroll in benefits per eligibility rules outline in the Allen Institute’s Benefits Guide. These benefits include medical, dental, vision, and basic life insurance. Employees are also eligible to enroll in the Allen Institute’s 401k plan. Paid time off is also available as outlined in the Allen Institutes Benefits Guide. Details on the Allen Institute’s benefits offering are located at the following link to the Benefits Guide: https://alleninstitute.org/careers/benefits.

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.