Abbott Principal Algorithm Engineer in Santa Clara, California
At Abbott, we're committed to helping people live their best possible life through the power of health. For more than 125 years, we've brought new products and technologies to the world -- in nutrition, diagnostics, medical devices and branded generic pharmaceuticals -- that create more possibilities for more people at all stages of life. Today, 99,000 of us are working to help people live not just longer, but better, in the more than 150 countries we serve.
Our brand-new hematology offering, the Alinity h-series, integrates hematology workflow, from high-throughput Complete Blood Count (CBC) analysis to automated slide making and staining. With a bi-directional, internal conveyor and a throughput of 250 CBCs per hour, it delivers high performance in one of the most compact footprints available.
The Alinity hq analyzer delivers a CBC with an expanded 6-part White Blood Cell (WBC) differential that includes routine and several advanced parameters using Advanced MAPSS (Multi Angle Polarized Scatter Separation) technology. With the Alinity hs slide maker stainer and the integrated robotic sample management, the Alinity h-series of systems delivers unprecedented uniformity, flexibility, operational productivity and confidence to our customers.
We are looking for a Principal Algorithm Engineer to develop the algorithms on the Alinity hematology analyzer to deliver best in industry results. The Principal Algorithm engineer will define areas of the algorithm that can be improved by better methods and techniques. She/he will prototype those new methods and demonstrate improved results. After feasibility is confirmed, she/he will implement the new algorithm into the product code. The Principal Algorithm Engineer will define future products by representing algorithms on the core teams. She/he will supervise and mentor junior members of the group.
Job Responsibilities :
Analyze data from the Alinity instrument and compare results to ground truth
Design and develop data analysis tools to automate the results comparison
Develop new algorithms for blood cell classification using machine learning techniques and clustering
Define upcoming product features as part of the core team
The ideal candidate should have at least 5 years of experience with classification algorithms
Experience with SVMs, neural networks, k-means clustering, EM models
Good knowledge of statistics, hypothesis testing as well as probability
Familiar with linear regression, correlation, outliers
Good programming skills are required; capable of implementing algorithms in C++ Algorithm prototyping in R, Matlab or Python is expected
Ph.D. desired, or 5+ years of experience in algorithm development
Interest in medicine/biology of blood
An Equal Opportunity Employer
Abbot welcomes and encourages diversity in our workforce.
We provide reasonable accommodation to qualified individuals with disabilities.
To request accommodation, please call 224-667-4913 or email email@example.com