Machine Learning Engineer (APPLICATIONS PROGR 3)

Risk and Safety Solutions (RSS) was founded in 2008 to provide innovative technology solutions supporting the University of California (UC), one of the world’s leading research institutions. Meeting the challenges presented by the institution’s vast breadth of Risk Management and Environmental Health and Safety (EH&S) activities related to cutting-edge research and healthcare services required a creative spirit and new ways of thinking. RSS is currently leading the development of an intelligent platform with over 40 solutions for Risk Management and EH&S in use across all 10 UC Campuses, 5 Medical Centers, and National Labs.

Since 2017, that entrepreneurial spirit has continued as RSS has expanded its clientele by offering innovative business solutions and expertise to a comprehensive range of business clients in the public and private sectors, nationally and internationally. You can learn more about RSS by visiting https://www.riskandsafety.com/

THIS POSITION IS NOT A VISA OPPORTUNITY

Under general supervision of the Associate Director of DevOps, in conjunction with the Machine Learning Architect and Senior Developers, the Machine Learning Engineer works within an agile team to develop, train, deploy, and maintain moderately complex machine learning models. This role researches the latest machine learning technologies and processes and makes recommendations for their utilization in new projects. This role works with a team of data scientists to develop, train new models and assist with complex data modeling. This role is responsible for integrating these models into existing production services, conducting performance & integration testing, and for monitoring the models to ensure they are functioning properly.

Position Information

PHYSICAL DEMANDS

• Work on a personal computer for extended periods of time.
• Work and maintain concentration in a busy office with constant interruptions and distractions, and constant traffic and noise from telephone conversations, visitors, staff, etc.
• Occasional travel to locations on and off campus. 

WORK ENVIRONMENT

• Flexible or extended hours as needed based on workload demands.
• Adhere to workplace safety practices, read information communicated about workplace safety, complete required safety training on time, and report any workplace safety issues promptly to their supervisor or the designated safety coordinator. 
• UC Davis is a smoke and tobacco free campus effective January 1, 2014. Smoking, the use of smokeless tobacco products, and the use of unregulated nicotine products (e-cigarettes) will be strictly prohibited on any UC Davis owned or leased property, indoors and outdoors, including parking lots and residential space.

MINIMUM QUALIFICATIONS

Minimum Education/Experience:

• Bachelor’s degree in computer science, Engineering, Mathematics, or Information Systems or equivalent combination of education and experience.
• 1+ year of professional experience as a machine learning engineer designing, developing, deploying, and supporting machine learning models and platforms for medium-sized projects.
• Experience with the entire Software Development Life Cycle (SDLC) of deploying machine learning models to production in one or more domains, such as classification, Natural Language Processing (NLP), computer vision, recommendation systems, and forecasting.
• Experience translating business requirements to technical solutions and developing technical specifications and documentation for use in the development and prioritization of work.
• Experience implementing machine learning algorithms in Python such as linear regression, logistic regression, decision trees, random forests, support vector machines (SVMs), Naive Bayes, neural networks, clustering, dimensionality reduction, and natural language processing (NLP).

Minimum Knowledge, Skills, and Abilities (KSA):

• Strong problem-solving skills and the ability to work independently or in a team environment.
• Oral, written and interpersonal skills to interact and communicate effectively and professionally with technical and non­technical stakeholders

PREFERRED QUALIFICATIONS

Preferred Education/Experience:   

• 2+ years of professional experience as a machine learning engineer designing, developing, deploying, and supporting machine learning models and platforms.
• Experience with industry tools and platforms used to build scalable machine learning systems, such as Elasticsearch, Kubernetes, Docker, Redis, Apache Kafka, SQL, NoSQL, Infrastructure as Code (IaC), AWS Lambda, and/or Apache Spark.
• Experience building a CI/CD pipeline with Github Actions, TravisCI, or others.
• Experience with cloud computing platforms such as AWS, Azure, or GCP.
• Experience developing web applications and/or mobile applications.

SPECIAL REQUIREMENTS

Background Check

This position is a critical position and subject to a background check. Employment is contingent upon successful completion of background investigation including criminal history and identity checks. 

Diversity, Equity, Inclusion and Belonging

At UC Davis, we’re solving life’s most urgent challenges to bring a fuller, healthier, and more resilient world within reach. We grow from every challenge we take on and we don’t just maintain - we improve.

We recognize that creating an inclusive and intellectually vibrant organization means understanding and valuing both our individual differences and our common ground. The most comprehensive solutions come from the most diverse minds, and you belong here. 

As you consider joining UC Davis, please explore our Principles of Community , our Clinical Strategic Plan and strategic vision for research and education, and our latest efforts to outgrow the expected .

The University of California is an Equal Opportunity/Affirmative Action Employer advancing inclusive excellence.  All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, protected veteran status, or other protected categories covered by the UC nondiscrimination policy.