About Prove 

As the world moves to a mobile-first economy, businesses need to modernize how they acquire, engage with and enable consumers. Prove’s phone-centric identity tokenization and passive cryptographic authentication solutions reduce friction, enhance security and privacy across all digital channels, and accelerate revenues while reducing operating expenses and fraud losses. Over 1,000 enterprise customers use Prove’s platform to process 20 billion customer requests annually across industries, including banking, lending, healthcare, gaming, crypto, e-commerce, marketplaces, and payments. For the latest updates from Prove, follow us on LinkedIn.

Prove is driving the future of digital identity. We are looking for Provers who know how to make an impact. We’re talking self-starting professionals who thrive in a fast-paced environment, process information quickly, and make intelligent decisions. The work is challenging and requires not only smart but natural curiosity and tenacity. Teamwork is also important to us – we work together and play together.   

Prove has big plans, and we’re excited about the future. If this sounds like the place for you – come join our team! 

Title: Senior Machine Learning Engineer

Department: EPD - Engineering and Data

Reports To: Senior Manager, Data Science 

FLSA Status: Exempt

Location: US Remote

 

Job Summary

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.

 

Key Responsibilities:

• 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.

Qualifications and Experience:

Required

• 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

 

Preferred

• Experience in high growth /pre-IPO Technology companies
• Experience with model risk management

 

This position description should not be considered the final description of the position. The position description is not intended to be an all-inclusive list of duties and standards of the positions. It should be assumed that we would, to some extent, structure responsibilities in accordance with the successful candidate’s capabilities a