Senior Machine Learning Engineer, Data Intelligence

Prove
1d$180,000 - $190,000Remote

About The Position

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! We are looking for a Senior Machine Learning Engineer to join our team and play a critical role in bridging data science and software engineering. In this role, you will partner with data scientists to take models from prototype to production, and with software engineers to build APIs and services that are performant, reliable, and scalable. You’ll be responsible for ensuring that machine learning systems are production-ready, monitored, and continuously improved. This position is ideal for someone who thrives at the intersection of machine learning, software engineering, and MLOps.

Requirements

  • 5-7+ years of professional experience in ML engineering, software engineering, or related roles.
  • Bachelor’s Master’s in Computer Science, Engineering, or related field (required).
  • Strong programming skills in Python (and experience with libraries such as scikit-learn, TensorFlow, or PyTorch), Java, and/or Go.
  • Hands-on experience building APIs and services (e.g., FastAPI, Flask, gRPC).
  • Expertise with containerization & orchestration (Docker, Kubernetes).
  • Familiarity with CI/CD pipelines and modern MLOps tools (MLflow, Airflow, Kubeflow, SageMaker, or similar).
  • Strong understanding of cloud platforms (AWS).
  • Solid background in data pipelines, distributed systems, and performance optimization.
  • Strong collaboration skills with both data scientists and software engineers.
  • Ability to balance technical rigor with pragmatic delivery.
  • Excellent communication and problem-solving abilities.

Nice To Haves

  • Master’s in Computer Science, Engineering, or related field, or equivalent experience (preferred).

Responsibilities

  • Collaborate with data scientists to transform research models into production-ready services.
  • Design, build, and maintain APIs and microservices to serve ML models at scale.
  • Ensure smooth integration of ML solutions into core products and platforms.
  • Optimize inference performance, latency, and scalability.
  • Build monitoring, logging, and alerting systems to track model performance and data drift.
  • Implement retraining pipelines and automated workflows for continuous improvement.
  • Develop CI/CD pipelines for machine learning workflows.
  • Use modern DevOps/MLOps practices to ensure reproducibility and reliability.
  • Partner with software engineers to design robust data and compute infrastructure.
  • Work closely with cross-functional teams to align model capabilities with business needs.
  • Mentor junior engineers and contribute to best practices in ML engineering.
  • Advocate for scalable, sustainable ML deployment strategies across the organization.

Benefits

  • Competitive compensation and benefits.
  • Opportunities to shape end-to-end ML systems in production.
  • A collaborative, high-impact environment where ML solutions directly drive business outcomes.
  • Competitive salaries & Bonus Plan (for eligible roles) and Equity Plan
  • Modern Health for financial, mental, and physical wellness
  • 401(k) Retirement Plan & Match (US Offices) and Local Country Pension (International Offices)
  • Unlimited Vacation and Flexible hours
  • Comprehensive medical benefits for you and your family ❤️
  • Emotional & Physical Wellness – Access to wellness services (EAP & Prove Well-Being Reimbursement)
  • Bottomless snacks & beverages for certain office locations
  • Daily GrubHub stipend for lunch if coming into the office (US Offices)
  • A great place to work and connect with other talented Provers like yourself!
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