Karkidi
Principal Machine Learning Engineer
Karkidi, Ames, Iowa, us, 50011
The Principal Machine Learning Engineer at Workiva spearheads the strategic vision for advancing Machine Learning (ML) solutions, ensuring inclusivity, and fostering innovation. This role champions MLOps excellence, crafting cloud infrastructure solutions to expedite ML development cycles. As a technical leader, the Principal ML Engineer guides a team in creating Workiva’s Generative AI platform, empowering product teams to pioneer transformative solutions. They offer expertise and mentorship within the Machine Learning domain, driving progress through collaboration and technical acumen.What You’ll Do
Shape the strategic engineering roadmap for ML advancementExplore cutting-edge technologies for strategic ML endeavorsArchitect systems to facilitate agile ML development with robust observabilityAdvise Workiva leadership and stakeholders on ML strategiesLead the team in adopting new ML technologies and methodologies to align with Workiva's goalsMentor junior ML engineers and scientists while establishing team standards and processesCollaborate with product teams to integrate ML solutions via APIsMaintain and evolve machine learning infrastructureForecast and coordinate development timelines, ensuring timely deliverablesManage backlog and resolve interdependencies with other product teamsHost ML models for product teams, ensuring monitoring and performanceDevelop automated tests tailored for ML solutionsTroubleshoot and debug components across diverse service and application contextsAssist support teams in resolving production issues and participate in on-call rotationsConduct code reviews and engage external stakeholders in ensuring solution qualityCommunicate complex technical issues effectively to diverse audiencesCollaborate with software architects, data experts, and product managers to design comprehensive software products meeting varied customer needsWhat You’ll Need
Required Qualifications
Bachelor’s degree in Computer Science, Engineering, or equivalent experienceMinimum 8 years of ML engineering experiencePreferred Qualifications
Technical leadership experience within an ML teamProficiency in architecting highly-available MLOps and ML solutionsExpertise in the ML development cycle and associated tool setsDemonstrated ability to identify and apply ML solutions effectivelyExperience with Generative AI and integrating Gen AI modelsStrong organizational skills with the ability to manage multiple projectsProven track record of problem-solving and decision-making in ambiguous situationsProficiency in Python, GO, Java, or similar languagesFamiliarity with Git or equivalent version control systemsExperience with Docker, preferably Kubernetes, and cloud platforms like AWSAgile/Sprint working environment experienceSolid foundation in computer science principles and cloud-based distributed systemsExcellent communication skills, both verbal and written, for effective collaborationProficiency in debugging complex systems and knowledge of web protocolsUnderstanding of commercial databases and systems performance tuningExperience in production-level testing and optimizing models for scalabilityWorking Conditions
Minimal ( Reliable internet access for remote working opportunitiesHow You’ll Be Rewarded
Salary range in the US: $167,000.00 - $284,000.00A discretionary bonus typically paid annuallyRestricted Stock Units granted at time of hire401(k) match and comprehensive employee benefits packageThe 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.
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Shape the strategic engineering roadmap for ML advancementExplore cutting-edge technologies for strategic ML endeavorsArchitect systems to facilitate agile ML development with robust observabilityAdvise Workiva leadership and stakeholders on ML strategiesLead the team in adopting new ML technologies and methodologies to align with Workiva's goalsMentor junior ML engineers and scientists while establishing team standards and processesCollaborate with product teams to integrate ML solutions via APIsMaintain and evolve machine learning infrastructureForecast and coordinate development timelines, ensuring timely deliverablesManage backlog and resolve interdependencies with other product teamsHost ML models for product teams, ensuring monitoring and performanceDevelop automated tests tailored for ML solutionsTroubleshoot and debug components across diverse service and application contextsAssist support teams in resolving production issues and participate in on-call rotationsConduct code reviews and engage external stakeholders in ensuring solution qualityCommunicate complex technical issues effectively to diverse audiencesCollaborate with software architects, data experts, and product managers to design comprehensive software products meeting varied customer needsWhat You’ll Need
Required Qualifications
Bachelor’s degree in Computer Science, Engineering, or equivalent experienceMinimum 8 years of ML engineering experiencePreferred Qualifications
Technical leadership experience within an ML teamProficiency in architecting highly-available MLOps and ML solutionsExpertise in the ML development cycle and associated tool setsDemonstrated ability to identify and apply ML solutions effectivelyExperience with Generative AI and integrating Gen AI modelsStrong organizational skills with the ability to manage multiple projectsProven track record of problem-solving and decision-making in ambiguous situationsProficiency in Python, GO, Java, or similar languagesFamiliarity with Git or equivalent version control systemsExperience with Docker, preferably Kubernetes, and cloud platforms like AWSAgile/Sprint working environment experienceSolid foundation in computer science principles and cloud-based distributed systemsExcellent communication skills, both verbal and written, for effective collaborationProficiency in debugging complex systems and knowledge of web protocolsUnderstanding of commercial databases and systems performance tuningExperience in production-level testing and optimizing models for scalabilityWorking Conditions
Minimal ( Reliable internet access for remote working opportunitiesHow You’ll Be Rewarded
Salary range in the US: $167,000.00 - $284,000.00A discretionary bonus typically paid annuallyRestricted Stock Units granted at time of hire401(k) match and comprehensive employee benefits packageThe 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.
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