Machine Learning / AI Engineer

San Diego, CA, United States

What if the work you did every day could impact the lives of people you know? Or all of humanity?

At Illumina, we are expanding access to genomic technology to realize health equity for billions of people around the world. Our efforts enable life-changing discoveries that are transforming human health through the early detection and diagnosis of diseases and new treatment options for patients.

Working at Illumina means being part of something bigger than yourself. Every person, in every role, has the opportunity to make a difference. Surrounded by extraordinary people, inspiring leaders, and world changing projects, you will do more and become more than you ever thought possible.

The Machine Learning/AI Engineer will be part of a team responsible to develop the infrastructure, system and predictive modeling and tools to enable Illumina Proactive, a predictive maintenance and system troubleshooting product that delivers enhanced customer experience and supports Illumina’s Service and Support organization. To accomplish this Machine Learning/AI Engineer will work cross-functionally with software development teams and product engineering to develop complex algorithms and machine learning models. The position will provide technical leadership to other engineers, analysts and programmers from design to deployment of models and other analytical projects. The position may also provide analytics support to other parts of the organization including Product Development, Manufacturing, Sales and Marketing and/or Finance.

Responsibilities

Apply data mining, predictive modeling, machine learning techniques to complex data structures and systems

Apply statistical analyses and modeling to draw insights from diverse array of commercial data

Develop algorithms and models capable of monitoring and predicting the performance of Illumina products

Collaborate with cloud software teams to deploy algorithms into Illumina’s remote diagnostics/proactive service product

Work with Data Scientists and Machine Leaning Engineers across Illumina to collaborative solve complex analytical and model building problem within and out side of the Commercial organization

Develop and defend business justifications and monitor impact of predictive modeling projects

Keep current with outside advancements in data science techniques and inject developments as appropriate

Qualifications

Deep understanding of machine learning techniques (supervised and unsupervised), predictive analytics and classification algorithms

Solid understanding of statistical analyses and statistical modeling

Hands-on experience in designing, developing and deploying machine learning and predictive models in production environment

Experience creating and presenting model output and performance of data to stakeholders using software such as Powerpoint, Tableau, PowerBI, Periscope, or other similar

Minimum of 5 years of functional programming and statistical analysis experience in MatLab, Python, R, SaS, or similar

Minimum of 2 years of experience with relational databases and SQL

Strong interpersonal and communication skills (both written and oral) including the ability to communicate complex technical/statistical concepts to a non-technical audience.

Preferred Qualifications

Systems engineering, reliability engineering or technical product support experience

Experience with collaborative model development and data science using version control tools (e.g. Git repositories)

Experience working agile SW development environments and familiar with software development best practices

Experience integrating and analyzing data from multiple business applications (SAP, SFDC, IBM Cognos)

Ability to work in a global collaborative team environment

Education

Master’s degree or Ph.D. preferred in a relevant technical discipline (Mathematics, Engineering, Computer Science, BioStatistics or a similar field). A Bachelor’s degree with highly relevant experience in acceptable

1+ years of relevant industry experience

The estimated base salary range for the Machine Learning / AI Engineer role based in the United States of America is: $86,500 - $129,700. Should the level or location of the role change during the hiring process, the applicable base pay range may be updated accordingly. Compensation decisions are dependent on several factors including, but not limited to, an individual’s qualifications, location where the role is to be performed, internal equity, and alignment with market data. Additionally, all employees are eligible for one of our variable cash programs (bonus or commission) and eligible roles may receive equity as part of the compensation package. We offer a wide range of benefits as innovative as our work, including access to genomics sequencing, family planning, health/dental/vision, retirement benefits, and paid time off.

At Illumina, we strive to foster a diverse and inclusive workplace by cultivating an environment in which everyone contributes to our mission. Built on a strong foundation, Illumina has always been rooted in openness, collaboration, and seeking alternative views and perspectives to propel innovation in genomics. We are proud to confirm a zero-net gap in pay, regardless of gender, ethnicity, or race. We also have several Employee Resource Groups (ERG) that deliver career development experiences, increase cultural awareness, and demonstrate our collective commitment to diversity and inclusion in the communities we live and work. We are proud to be an equal opportunity employer committed to providing employment opportunity regardless of sex, race, creed, color, gender, religion, marital status, domestic partner status, age, national origin or ancestry, physical or mental disability, medical condition, sexual orientation, pregnancy, military or veteran status, citizenship status, and genetic information. If you require accommodation to complete the application or interview process, please contact [email protected]. To learn more, visit: https://www.dol.gov/ofccp/regs/compliance/posters/pdf/eeopost.pdf

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