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Software Engineer-Machine Learning

Washington Park, Washington Thermo Fisher Scientific

Job ID :


Location :

US – Washington – Bothell


Job Description

Job Title: Machine Learning Software Engineer
When you’re part of the team at Thermo Fisher Scientific, you’ll do important work, like helping customers in finding cures for cancer, protecting the environment or making sure our food is safe. Your work will have real-world impact, and you’ll be supported in achieving your career goals.

Division and Location
The Biosciences Division (BID) is a $2.5 billion business with more than 4,000 employees across the globe. Grounded in Science we offer reagents, instruments, and consumables to over 480,000 customers from pharmaceutical, biotech, healthcare, academic, government and industrial markets. We’re proud of our portfolio which offers more than 4,000 patents, over 770,000 scientific citations and 70,000 products.

We’re looking for a passionate Machine Learning Software Engineer for this newly created, key role which is located in Bothell, WA.

How will you make an impact?
The work that you’ll do here will truly make in impact on Human Health. You’ll be working with new technologies and meaningful applications that make a difference. You’ll advance all phases of software development including design, implementation, testing, integration and maintenance for our company’s cell analysis software.

What will you do?
– Drive the development and support of:
– Image processing algorithms to perform image enhancement, object detection, and image analysis.
– Algorithms that address classification, regression, and optimization problems, utilizing statistical analysis, pattern recognition, machine learning, and other Artificial Intelligence techniques.
– Graphical User Interface and analysis algorithms in both standalone and distributed applications.
– Collaborate with biologists to translate their scientific research needs into analysis solutions, by defining user stories and software requirements.
– Design novel image and data analysis approaches to make the application’s workflow simpler and more robust.
How will you get there?

– Bachelor’s degree in Computer Science, Engineering, or related field. Master’s or Ph.D. preferred.
– 7+ years of experience developing commercially released applications.
– Unit testing experience
– Experience with Visual Studio and .NET
– Preferred experience in applying image and data analysis algorithms on applications related to cellular-biology.
– Amazon Web Services experience is preferred. Knowledge, Skills, Abilities
– Passion to keep pace with latest advances in analysis and software development technology and applying modern technology to solve real customer’s problems.
– Strong working knowledge of AI (Artificial Intelligence) techniques, including statistical analysis, supervised and unsupervised machine learning, and optimization algorithms.
– Strong working knowledge of image processing algorithms.
– Strong working knowledge of C# and C++ programming languages.
– Expert software development skills, including real-time multi-threaded software.
– Knowledge and application of design patterns, object-oriented programming, and micro-services.
– Knowledge of Matlab, R, and other prototyping tools is a preferred.
– Python, Java and other programming languages preferred.
– Knowledgeable in microscopy and biology preferred.
– Familiarity with Linux preferred.
– Must enjoy collaborating and be a strong team player with the ability to communicate effectively.Exceptional relocation assistance available for qualified candidates!

At Thermo Fisher Scientific, each one of our 70,000 extraordinary minds has a unique story to tell. Join us and contribute to our singular missionenabling our customers to make the world healthier, cleaner and safer.

Thermo Fisher Scientific is an EEO/Affirmative Action Employer and does not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability or any other legally protected status.

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