Senior Manager – ML Applied Science

10 hours ago

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Workiva

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SaaS • Finance • Compliance

Workiva is a cloud-based, AI-powered platform that unifies financial reporting, risk and compliance management, and sustainability reporting. It enables teams to connect data across systems, collaborate in real time, automate reporting (including XBRL tagging), and maintain auditability and traceability for regulated disclosures and assurance processes. Workiva serves large enterprises and finance, legal, audit, and sustainability teams to accelerate reporting, improve accuracy, and reduce risk.

1001 - 5000 employees

Founded 2008

☁️ SaaS

💸 Finance

📋 Compliance

📋 Description

• Collaborate closely with product teams to lead and develop applied scientists in owning advanced solutions including RAG, Agent based workflows, and model tuning and seamlessly integrating Generative AI and machine learning features into products • Work closely with cross-functional stakeholders, including Product and other engineering teams, to align goals and deliverables • Support technical leadership, coach and guide ML engineers and scientists aligned with the technical leaders of the team • Manage and lead AI/ML teams balancing diverse skill sets consisting of ML scientists, ML engineers, and full stack software engineers • 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 • Manage the team within an agile development environment, ensuring timely and high-quality delivery of SaaS products • Help shape the AI & ML vision at Workiva, focusing on integrating traditional ML and Data Science principles with Generative AI to augment our current product offerings • Be accountable for the team's on-call rotations, providing 24x7 support for all of Workiva’s SaaS hosted environments • Address customer requests and feedback, continuously improving the user experience across multiple solutions and problem spaces

🎯 Requirements

• Bachelor’s degree in Computer Science, Engineering, or a related quantitative field (e.g., Statistics, Mathematics, Physics) or equivalent combination of education and experience. • Masters degree in Computer Science or related fields (Preferred). • 7+ years in ML engineering, applied science, or related software engineering experience • 4+ years of experience in a people management role • Proficiency in ML development cycles and toolsets • Expertise with LLMs and related technologies (Preferred). • Experience leading teams of 5+ people, preferably with diverse skill sets and specializations • Proven experience leading teams in Agile and Sprint-based environments • Proven experience working with product teams to integrate machine learning features into the product • Solid experience in delivering SaaS products, specifically hosted in AWS, Azure, or GCP • In-depth knowledge of Generative AI, traditional Machine Learning, and Data Science principles • Excellent problem-solving skills, with the ability to address customer needs and improve product experiences.

🏖️ Benefits

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