Staff Machine Learning Engineer

Workiva

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profile Job Location:

Ames, IA - USA

profile Monthly Salary: $ 148000 - 237000
Posted on: 2 days ago
Vacancies: 1 Vacancy

Job Summary

Join our team at Workiva as a Staff Machine Learning Engineer! As a pivotal member of our Machine Learning (ML) team youll spearhead the architecture and delivery of groundbreaking machine learning solutions across our platform. Your expertise will be instrumental in leading projects that demand innovative problem-solving including the integration of cutting-edge Generative AI into our products.

In this role youll have the chance to develop robust tools systems and infrastructure to bolster the development monitoring and management of our machine learning solutions. Leveraging your engineering prowess youll tackle challenges related to availability and scaling ensuring the long-term stability of our systems.

If youre passionate about pioneering the possibilities of Generative AI and want to be part of a team driving innovation at Workiva we invite you to join us! Learn more about Workivas Generative AI and be part of shaping the future of ML with us.

What Youll Do

Architect and Develop Solutions

  • Architect and deliver cutting-edge ML solutions using MLOps and best practices fostering creativity in project execution

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

  • Develop tools systems and automation to support ML solutions ensuring efficiency scalability and rapid development

Collaborate and Lead

  • Collaborate closely with product teams to develop APIs maintain ML infrastructure and integrate machine learning features into products

  • Provide technical leadership mentor less experienced ML engineers and scientists and define team best practices and processes

  • Lead in the ML space by introducing new technologies and techniques and applying them to Workivas strategic initiatives

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

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

Ensure Reliability and Support

  • Deliver update and maintain machine learning infrastructure to meet evolving needs

  • Host ML models to product teams monitor performance and provide necessary support

  • Write automated tests (unit integration functional etc.) with ML solutions in mind to ensure robustness and reliability

  • Debug and troubleshoot components across multiple service and application contexts engaging with support teams to triage and resolve production issues

  • Participate in on-call rotations providing 24x7 support for all of Workivas SaaS hosted environments

  • Perform Code Reviews within your groups products components and solutions involving external stakeholders (e.g. Security Architecture)

What Youll Need

Required Qualifications

  • Bachelors degree in Computer Science Engineering or equivalent combination of education and experience

  • Minimum of 4 years in ML engineering or related software engineering experience

  • Proficiency in ML development cycles and toolsets

Preferred Qualifications

  • Familiarity with Generative AI

  • Strong technical leadership skills in an Agile/Sprint working environment

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

  • Proficiency in Python GO Java or relevant languages with experience in Github Docker Kubernetes and cloud services

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

  • Experience with commercial databases and HTTP/web protocols

  • Knowledge of systems performance tuning and load testing and production-level testing best practices

  • Experience with Github or equivalent source control systems

  • Experience with Amazon Web Services (AWS) or other cloud service providers

  • Ability to prioritize projects effectively and optimize system performance

Working Conditions

  • Less than 10% travel

  • Reliable internet access for remote working opportunities

How Youll Be Rewarded

Salary range in the US: $148000.00 - $237000.00

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.

Employment decisions are made without regard to age race creed color religion sex national origin ancestry disability status veteran status sexual orientation gender identity or expression genetic information marital status citizenship status or any other protected characteristic.

Workiva is committed to working with and providing reasonable accommodations to applicants with disabilities. To request assistance with the application process please email .

Workiva employees are required to undergo comprehensive security and privacy training tailored to their roles ensuring adherence to company policies and regulatory standards.

Workiva supports employees in working where they work best - either from an office or remotely from any location within their country of employment.

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Required Experience:

Staff IC

Join our team at Workiva as a Staff Machine Learning Engineer! As a pivotal member of our Machine Learning (ML) team youll spearhead the architecture and delivery of groundbreaking machine learning solutions across our platform. Your expertise will be instrumental in leading projects that demand inn...
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Key Skills

  • Computer Science
  • Docker
  • Kubernetes
  • Python
  • VMware
  • C/C++
  • Go
  • System Architecture
  • gRPC
  • OS Kernels
  • Perl
  • Distributed Systems

About Company

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Workiva's cloud-based software transforms work with assured, integrated reporting solutions for finance, ESG, audit & risk—connecting people, data & processes.

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