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Senior Machine Learning Engineer
Skills
Artificial IntelligenceCreativeData ArchitectsData ScienceDatabasesDebuggingMachine Learning
What the job involves
The main requirements, responsibilities and hiring steps.
Requirements
- 2+ years of relevant experience with a Bachelor's Degree or equivalent experience
- 4+ years of ML engineering or related experience preferred
- Proficiency in ML development cycle and toolsets
- Experience with model deployment, data pipelines, CI/CD, and infrastructure
- Familiarity with Generative AI and development patterns
- Proficient in Python, GO, Java, with source control systems
- Experience with Docker, Kubernetes preferred, and cloud services like AWS
- Strong programming foundation
- Experience in Agile/Sprint environments
- Knowledge of HTTP/web protocols, databases, performance tuning, production-level testing
- Excellent communication and organizational skills
Nice to have
- Creative problem-solving skills
- Strong mentoring abilities
- Excellent communication skills
- Organizational skills for managing multiple projects
Day to day
- Delivering innovative machine learning solutions across Workiva using MLOps and software engineering best practices
- Developing tools, systems, infrastructure, and automation for managing Workiva’s machine learning solutions
- Analyzing issues to ensure high availability and scalability, and deriving long-term stability solutions
- Collaborating with product teams to create APIs and access ML solutions
- Leading the ML team, mentoring, defining best practices, and performing code reviews
- Debugging and troubleshooting components across services and applications
- Collaborating with software/data architects and product managers to create software products addressing customer needs
Hiring process
- Willingness to travel up to 15% for team and corporate meetings Reliable internet access for remote work