Senior ML Engineer - Remote

Summary
The Senior Machine Learning Engineer is responsible for delivering machine learning (ML) infrastructure solutions across Workiva with the goal of improving quality, reliability, and efficiency of ML services. The role develops tools, systems, and automation to help monitor, measure, manage, and make transparent Workiva’s machine learning models. The Senior ML Engineer analyzes issues that prevent availability or scaling and derives solutions that provide long-term stability. The role works across product lines to standardize tools and methodologies. They will also provide technical leadership to a team of Engineers to create a reliable and stable platform.

What You'll Do

• Deliver, update, maintain machine learning model training infrastructure

• Design systems to enable rapid ML development, high availability, and clear observability

• Write automated tests (unit, integration, functional, etc) with ML solutions in mind

• Develop APIs with product teams to access Workiva’s ML models

• Responsible for serving/hosting ML models to product teams including monitoring

• Debug and troubleshoot components across multiple service and application contexts

• Engage with support teams in triaging and resolving production issues

• Participate in on-call rotations which include 24x7 support of all of Workiva’s SaaS hosted environments

• Perform Code Reviews within your group’s products, components, and solutions; involve external stakeholders (Ex. Security, Architecture) where appropriate

• Communicate complex technical issues to both technical and non-technical audiences

• Forecast and plan solution development team deliverables and timelines

• Maintain the backlog, coordinates teams, and works to resolve interdependencies with other product teams when serving in the tech lead role

• Manage and resolve dependencies between teams

• Collaborate with software, data architects and product managers to design complete software products that can be leveraged to meet a broad range of customer needs and requirements

What You'll Need

• Bachelor’s degree in Computer Science, Engineering or equivalent combination of education and experience

• 4+ years of relevant experience in software engineering, infrastructure engineering, full stack development or equivalent

• Experience with the machine learning development cycle and tool sets

• Experience with Python, GO, Java, or other relevant languages preferred

• Experience with Github, VCS, or equivalent source control systems

• Experience with Docker and preferably Kubernetes

• Experience with Amazon Web Services or Google App Engine, or other cloud service providers

• Experience in an Agile/Sprint working environment

• Extensive proficiency in programming to include a solid foundation in computer science, with competencies one or more of: data structures, algorithms, object-oriented software design, and working with cloud-based distributed systems.

• Excellent communication (verbal and written) and interpersonal skills and an ability to effectively communicate with both business and technical teams

• Experience debugging complex systems or applications

• Knowledge of HTTP and web protocols

• Knowledge of one or more commercial databases

• Excellent planning and organizing skills to prioritize numerous projects and deliverables

• Knowledge of systems performance tuning and load testing

• Proven experience working product teams to integrate machine learning features into the product

• Production-level testing best practices (signals tests, load testing for ML services, etc) and optimizing models to work at scale

• Experience building model deployment pipelines and/or CI/CD pipelines and infrastructure

Working Conditions & Travel

• Reliable internet access for any period of time working remotely, if not located in a Workiva office, as we embrace flexible work arrangements.

How You’ll Be Rewarded:

• Salary range in the US: 

$102,000.00 - $173,000.00

• A discretionary bonus typically paid annually
• Restricted Stock Units granted at time of hire
• 401(k) match and comprehensive employee benefits package

The salary range represents the low and high end of the salary range for this job in the US. Minimums and maximums may vary based on location. The actual salary offer will carefully consider a wide range of factors, including your skills, qualifications, experience and other relevant factors.