Machine Learning Engineer (Close date: March 22nd) at Zelus Analytics

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We are seeking Machine Learning Engineers with a passion for sports to implement, automate, and optimize the quantitative models that power our world-class sports intelligence platforms in baseball, basketball, cricket, eSports, football (American), golf, hockey, soccer, and tennis. Through your work, you can support the professional teams in our exclusive partner network in their efforts to compete and win championships.

Zelus Analytics is a fully remote company working directly with teams across the NBA, MLB, NFL, IPL and NHL, in addition to a number of soccer teams around the globe. Zelus unites a fast-growing startup environment with a research-focused culture that embraces our core values of integrity, innovation, and inclusion. We pride ourselves on providing meaningful mentorship that offers our team the opportunity to develop and expand their skill sets while also engaging with the broader analytics community. In doing so, we hope to create a new path for a more diverse group of highly talented people to push the cutting edge of sports analytics.

We believe that a diverse team is vital to building the world’s best sports intelligence platform. Thus, we strongly encourage you to apply if you identify with any marginalized community across race, ethnicity, gender, sexual orientation, veteran status, or disability. At Zelus, we are committed to creating an inclusive environment where all of our employees are enabled and empowered to succeed and thrive.

As Zelus employees advance in experience and level, they are expected to build on their competencies and expertise and demonstrate increasing impact, independence, and leadership within their roles.

More specifically, as a Zelus Machine Learning Engineer, you will be expected to:

Optimize, automate, and validate quantitative models built using statistics, machine learning, optimization, and simulation
Develop, schedule, monitor, and maintain model training and prediction workflows
Coordinate with broader engineering team to plan and implement changes to core infrastructure to support one or more sports
Collaborate with data scientists to define and manage model productionalization and platform release plans
Deploy REST APIs on top of fitted models using distributed computation to support real-time, client-facing integration
Collaborate and communicate effectively in a distributed work environment
Fulfill other related duties and responsibilities, including rotating platform support

Additionally, a Machine Learning Engineer II will be expected to:

Develop and maintain abstractions for model deployment that allow our workflows to run efficiently and be easily adapted to future use cases
Assess, provision, monitor, and maintain the appropriate infrastructure and tooling to execute model training and prediction workflows
Create visualizations with dashboard or application development frameworks to deliver data insights to our clients

Additionally, a Senior Machine Learning Engineer will be expected to:

Research, design, and test improvements to model deployment and guide organizational adoption
Collaborate with product and data science leads to define and manage implementation, validation, deployment, and release plans/logistics for our sports intelligence platforms
Lead team-wide implementation of machine learning engineering standards
Effectively communicate complex technical concepts to both internal and external audiences
Provide guidance and technical mentorship for junior engineers
Assist with recruiting and outreach for the engineering team, including building a diverse network of future candidates

Additionally, a Senior Machine Learning Engineer II will be expected to:

Identify and implement generalizable strategies for infrastructure maintenance and computational cost savings
Break down complex machine learning engineering projects into actionable work plans including proposed task assignments with clear design specifications
Assist in defining machine learning engineering standards for the organization

A qualified Machine Learning Engineer will be able to demonstrate several of the following and will be excited to learn the rest through the mentorship provided at Zelus:

Academic and/or industry experience in software design and development
Academic, industry, and/or research experience with applied mathematical and predictive modeling (statistics, machine learning, optimization, and/or simulation)
Experience with cloud infrastructure and distributed computing
Experience with (i) back-end development, including fluency with Python (preferred), R, or other data-oriented and statistical programming languages, or (ii) front-end development, including fluency with application development languages (Javascript, Typescript) and UI frameworks (React, RShiny, Vue)
Experience with relational databases and SQL development
Familiarity working with Linux servers in a virtualized/distributed environment
Strong software-engineering and problem-solving skills

A qualified Senior Machine Learning Engineer will be able to demonstrate all of the above at a higher level of competency plus the following:

Expertise designing, developing, and optimizing the cloud infrastructure for large-scale, cloud-based analytics systems
Experience with task orchestration and workflow automation tools
Experience adapting, retraining, and retooling in a rapidly changing technology environment
Desire and ability to successfully mentor junior engineers

Starting salaries range from*:

$87,000 to $102,000 for Machine Learning Engineer
$102,000 to $118,000 for Machine Learning Engineer II
$118,000 to $136,000 for Senior Machine Learning Engineer
$136,000 to $160,000 for Senior Machine Learning Engineer II

*Compensation paid in non-US currency will be in a comparable range adjusted by differences in total cost of employment.

Zelus has a fully distributed workforce, spanning multiple states and countries, with a formal process for establishing compensation equity across its global staff. In addition to competitive salaries, our full-time compensation packages include equity grants and comprehensive benefits, such as an annual incentive bonus plan, supplemental health, vision, and dental insurance, and flexible PTO, all of which allow us to attract and retain a world-class team.

As an equal opportunity employer, Zelus does not discriminate on the basis of race, ethnicity, color, religion, creed, gender, gender expression or identification, sexual orientation, marital status, age, national origin, disability, genetic information, military status, or any other characteristic protected by law. It is our policy to provide reasonable accommodations for applicants and employees with disabilities. Please let us know if reasonable accommodation is needed to participate in the job application or interview process.

In most jurisdictions, Zelus is an at-will employer; employment at Zelus is for an indefinite period of time and is subject to termination by the employer or the employee at any time, with or without cause or notice.

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