Senior Machine Learning Ops Engineer


 140k - 180k
 United States  (New York)
Prove logo

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! 

Data Scientists at Prove work on Proof of Concepts (POCs) with Sales, Customer Success (CS) related projects with Customer Support Team and Research & Development (R&D) with Product and Engineering. This position of MLOps Engineer can be viewed as a person responsible for expanding and optimizing our data and machine learning pipeline architecture.  Full-scale data science products need to be deployed and this role demands a person who has experience with software/DevOps/Data Engineering. 

Primarily this position involves using engineering skills to build a production grade self-service analytics framework that provides Data Science more autonomy and control.  Data Scientists can then use the framework for all prototyping work or to deploy models into production in swift fashion with a low overall cycle time. This position requires the ability to create a platform that can score a single transaction in real time, while working within production constraints & considerations.

The incumbent develops best practices, policies, procedures and governance of ML models in production, model lifecycle management, and associated data engineering processes designed to deploy ML and AI models efficiently and reliably in production in cloud-based and on-premises environments. Other responsibilities include increasing the maturity of existing ML pipelines by standardizing the data science development lifecycle, identifying and enforcing standards for model experimentation, model validation and testing. Duties will include evaluation of new ML cloud tools and data science methods available on AWS/GCP, and their selection and introduction to the wider organization, education and onboarding of Data Science teams to new technologies. Finally this position will help with any automation needed to refine the Data Science analytics pipeline. 

Key Responsibilities:

  • Build and Support a self-service framework using tools like Tensorflow or Pytorch or other relevant ones
  • Ensure the framework is production grade with low latency, and has 24/7 monitoring, observability, logging, error handling, scalability, etc. 
  • Help Data Scientists with deploying models or algorithms that power Prove’s products
  • Optimize the secured cloud platform for our global data analytic needs
  • Implementing ML models and algorithms in production-quality code
  • Supporting cross-functional efforts to analyze, automate, and optimize system performance
  • Hands-on coding, systems analysis, code reviews, design, and delivery of projects
  • Helping in automation of existing Data Science process pipelines 
  • Integrate with External Vendors API which are being test by Data Scientists for possible lift
  • Writing well designed, testable, efficient code that meets coding standards
  • Delivering new features, executing on the roadmap and planning for the future
  • Providing thought leadership on industry best practices around ML model development, design, testing, security, and software development
  • Exercising creative thinking and imagination to find solutions to hard problems

Qualifications and Experience:

  • 5-8 years of DevOps experience, preferably in a fast-paced environment
  • 3+ years of experience building/maintaining Docker/Kubernetes infrastructure
  • Strong programming skills in Python/Go/Java
  • Preferably 2-3 years of ML or ML Ops experience in a production environment or equivalent Master’s degree in related field
  • Knowledge of Tensorflow or Pytorch or similar library tools
  • Background in machine learning theory and/or signal processing techniques is a plus 
  • Experience building tools for ML scientists or experience building auto-scaling ML systems
  • 3+ years of experience with cloud: AWS or Google Cloud Platform (GCP) or Azure
  • Strong software development principles, including scalable software and architectural design patterns
  • Experience with database (SQL and NoSQL) systems such as BigQuery, Postgres, MongoDB
  • 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

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 and changing business conditions. Incumbents will follow any other instructions, and perform any other related duties, as assigned by their supervisor.

The salary range for this role is $140,000- $180,000 plus company bonus. Offered salary will be determined by the applicant’s education, experience, knowledge, skills, and abilities, as well as internal equity and alignment with market data.

Benefits & Perks for FTE Provers:

  • Competitive salaries & Bonus Plan (for eligible roles) and Equity Plan
  • 401(k) Retirement Plan & Match
  • Comprehensive medical benefits for you and your family ❤️
  • Emotional & Physical Wellness – Access to wellness services (EAP, Gympass, Prove Well-Being Reimbursement)
  • Unlimited Vacation and Flexible hours
  • Professional Development Coaching via Bravely
  • Healthy lunches catered and bottomless snacks & beverages for all office locations
  • 12 paid holidays for all global employees 📅
  • A great place to work and connect with other talented Provers like yourself!
Don’t meet every single requirement? Studies have shown that women and people of color are less likely to apply to jobs unless they meet every single qualification. At Prove we are dedicated to building a diverse, inclusive and authentic workplace, so if you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles.
This position description should not be considered the final description of the position. It should be assumed that we would, to some extent, structure responsibilities in accordance with the successful candidate’s capabilities and changing business conditions.
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