MoonPay15.02.26
AI SCORE 8.5

Senior Machine Learning Engineer - Remote Opportunity

$140K–$200K/year

About the Role

Join MoonPay as a Senior Machine Learning Engineer and help us onboard the world to the decentralized economy. As a Senior Machine Learning Engineer remote, you will play a crucial role in building and integrating machine learning solutions that evaluate transactions and customer behavior in real-time and offline environments.

What You'll Do

  • Develop and integrate machine learning solutions for fraud prevention across multiple crypto products.
  • Experiment with various modeling techniques on customer data, bringing your solutions to production by collaborating with product, data, operations, and engineering teams.
  • Analyze large datasets using SQL, Python, and Apache Beam to extract valuable features.
  • Build AI-powered automation tools or pipelines and propose improvements across our operations.
  • Own the full lifecycle of machine learning solutions from data ingestion and processing to feature engineering, model development, deployment, and iteration.
  • Maintain and enhance our existing codebase, expanding our internal ML libraries and pipelines.

Requirements

  • Proven experience in machine learning at leading fintech startups or fast-growing tech companies.
  • Confidence in developing, releasing, and maintaining ML models in a fast-paced, iterative environment.
  • Familiarity with our tech stack, including Python, gradient boosting algorithms (e.g., XGBoost/CatBoost), PyTorch, and cloud platforms like Google Cloud or AWS.
  • Real-world experience working with time series data for classification and adversarial models.
  • Understanding of data structures, pipelines, and big data processing for real-time consumption.

Nice to Have

  • Experience with Cloud Native applications such as AWS or Azure.
  • Knowledge of Docker, Kubernetes, and CI/CD practices.
  • Familiarity with tools like FastAPI, Kubeflow, and Airflow.

What We Offer

  • Competitive salary package and equity opportunities.
  • Unlimited holidays for a healthy work-life balance.
  • Hybrid working schedule: work fully remotely or from your nearest Moonbase.
  • Private healthcare benefits for you and your loved ones.
  • Annual training budget to support your professional development.
  • Home office setup allowance to create your ideal workspace.
  • Regular remote company offsites for team bonding and collaboration.

At MoonPay, we believe in financial freedom for everyone. If you are passionate about building a fairer, more open financial system, we want you to join us as a Senior Machine Learning Engineer remote. Together, let's make financial autonomy the new normal!

Why This Job8.5 of 10

This Senior Machine Learning Engineer role at MoonPay offers a unique opportunity to work remotely while contributing to the decentralized economy. With a competitive salary and equity options, it's an attractive position for experienced ML professionals.

Salary Range
Required
0/1
Optional
0/1
Bonus
0/1

Who Will Succeed Here

Proficient in Python and experienced with machine learning libraries such as PyTorch and XGBoost, enabling the candidate to develop robust models for transaction evaluation and fraud prevention.

Strong understanding of cloud infrastructure, specifically Google Cloud, and containerization technologies like Docker and Kubernetes, to efficiently deploy and manage machine learning solutions in a remote environment.

A proactive problem-solver with a deep analytical mindset, capable of quickly adapting to new algorithms and technologies, and experienced in handling SQL databases for data manipulation and analysis.

Learning Resources

Python for Data Science Handbookguide

Career Path

Senior Machine Learning Engineer(Now)Lead Machine Learning Engineer(1-2 years)Machine Learning Architect(3-5 years)

Market Overview

Market Size 2024
$20.1B
Annual Growth
22.4%
AI Adoption
57%
Investment
+135%
Labour Demand
+30%
Avg Salary
$150K

Skills & Requirements

Required
PythonMachine LearningSQL
Growing in Demand
TensorFlowNatural Language Processing (NLP)Data Engineering
Declining
R (for Machine Learning)Apache Mahout

Domain Trends

Increased Adoption of MLOps
Organizations are increasingly adopting MLOps practices, with 60% of enterprises implementing MLOps frameworks to streamline ML operations and deployments.
Rise of Edge AI
The Edge AI market is projected to grow by 25% annually, as more companies deploy machine learning models at the edge for real-time processing.
Focus on Ethical AI
Around 70% of tech companies are prioritizing ethical AI practices, with investments in bias detection and transparency tools increasing by 40%.

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