Senior Machine Learning Engineer, Prove

Data Intelligence

$180-190k

+ Bonus + Equity

AWS

Docker

Kubernetes

Python

Java

Airflow

Tensorflow

Scikit-Learn

Flask

Kubeflow

PyTorch

Sagemaker

FastAPI

Senior and Expert level

Remote from US

Identity verification platform

Open for applications

Identity verification platform

201-500 employees

B2BSecuritySaaSMobileCyber SecurityIdentity

Open for applications

$180-190k

+ Bonus + Equity

AWS

Docker

Kubernetes

Python

Java

Airflow

Tensorflow

Scikit-Learn

Flask

Kubeflow

PyTorch

Sagemaker

FastAPI

Senior and Expert level

Remote from US

201-500 employees

B2BSecuritySaaSMobileCyber SecurityIdentity

Company mission

To enable a digital world where every consumer and company can transact with trust.

Job

Company

Role

Who you are

This position is ideal for someone who thrives at the intersection of machine learning, software engineering, and MLOps
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)
Master’s in Computer Science, Engineering, or related field, or equivalent experience (preferred)
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

What the job involves

Reports To: Senior Manager, Data Intelligence
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
Model Deployment & Integration
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
Performance & Reliability
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
Engineering & MLOps
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
Collaboration & Leadership
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

Our take

Prove's identity-proving solutions allow businesses to enable their customers to prove their identities with just a phone. It is used by more than 1,000 global enterprises and 500 financial institutions, across multiple industries.

With more and more activity taking place online and via mobile devices, Prove offers companies speed and security while processing transactions. The identity verification space is buoyant, with many other companies providing services. But despite this competition, Prove has grown to be a leading and award-winning platform.

Prove's phone-centric tokenization and passive cryptographic solutions have had tremendous corporate momentum. The company has been named to Deloitte’s prestigious Technology Fast 500 list several times, and is well set to further its hold on the market.

Freddie

Company Specialist at Welcome to the Jungle

Insights

Top investors

17% employee growth in 12 months

Glassdoor (3.5)

Company

Funding (last 2 of 9 rounds)

Oct 2023

$40m

LATE VC

Jun 2020

$100m

LATE VC

Total funding: $252.1m

Company benefits

401k Match
Parental Leave Policy
Stock Options
Health benefits
Wellbeing reimbursement
Work From Home Opportunities
Bonus Scheme
Generous Vacation Time

Company HQ

NoMad, New York, NY

Leadership

Rodger Desai

(CEO)

Studied at Harvard Business School after working as an Engineer for Exxon Mobil, General Electric, and Accenture, as well as co-founding several venture-backed startups.

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