Senior Machine Learning Engineer, Prove

• 5+ years of professional experience as a Machine Learning Engineer or in a similar role
• Bachelor’s degree in Computer Science, or a related field
• Experience with public cloud infrastructure (AWS, GCP, Azure)
• Demonstrated experience with MLOps, including CI/CD pipelines, model versioning, and monitoring in a production environment
• Strong software development principles and a track record of building scalable, reliable systems
• Expert proficiency in Python and experience with machine learning frameworks (e.g., PyTorch, TensorFlow, Scikit-learn)
• Proficient in machine learning and/or signal processing techniques
• Promote, maintain and enhance our cultural values of humility, passion, inclusion, and leadership
• Strong passion for learning about our products and markets through in-house and external training
• Experience in high-growth /pre-IPO Technology companies

Desirable

• Reports To: Senior Manager, Data Science
• As a member of the Data Science team, you will work closely with our product, cloud backend, engineering, and customer-facing teams to define what it means to have an effective solution, propose and implement models and algorithms for the solution, and build systems that automatically ensure the intelligence behind our products is operating as efficiently and effectively as possible
• You will be responsible for understanding how the whole system works and helping to drive improvements
• This is a critical hands-on role with a high degree of influence. We embrace our startup roots and are willing to wear whatever hat is necessary to make our team and products successful
• Design, build, and deploy end-to-end machine learning systems and data pipelines in a production environment
• Lead the research and development of new models and algorithms that drive the core intelligence of Prove's products
• Collaborate across teams (product, cloud backend, platform, data engineering) to define requirements and deliver solutions that improve system performance and efficiency
• Serve as a technical leader, providing guidance on architectural design, best practices, and code quality across the team
• Drive continuous improvement by owning the full lifecycle of models, from data ingestion and training to monitoring and maintenance
• Exercise creative thinking and imagination to find solutions to hard problems
• Mentor other engineers and data scientists, fostering a culture of technical excellence and innovation
• Strong passion for learning about our products and markets through in-house and external training