Machine Learning Engineer
Description For Machine Learning Engineer
MoonPay, the leading Web3 infrastructure company, is seeking a seasoned Machine Learning Engineer to join our Data team. We're a dynamic company that has built trust with over 20 million users worldwide, offering comprehensive Web3 solutions from payment systems to NFT minting software.
As our ML Engineer, you'll be instrumental in implementing machine learning systems that directly impact critical business functions. You'll work closely with data scientists and cross-functional teams including Engineering, Ops, Product, and Fraud Prevention. Your role will involve assessing and improving our ML design, developing strategies for expansion, and ensuring our ML systems operate effectively.
The ideal candidate brings substantial experience in productionizing ML systems, with expertise in Python, SQL, and cloud infrastructure. You'll work with cutting-edge technologies including Kubernetes, Kafka, and various MLOps tools. We're particularly interested in professionals who understand the full lifecycle of ML models and can bridge the gap between experimental features and production environments.
At MoonPay, we're driven by our "BLOCK Values": Be Hungry, Level Up, Own It, Crypto Curious, and Kaizen. We offer competitive benefits including equity, unlimited holidays, parental leave, and professional development opportunities. Join us in shaping the future of Web3 and digital ownership in a diverse, inclusive environment that values every voice.
Responsibilities For Machine Learning Engineer
- Consult with data scientists on training machine learning models
- Provide strategic vision for making machine learning a cornerstone to MoonPay's business
- Support and improve ML infrastructure, including data engineering and DevOps
- Design systems to meet throughput and latency requirements
- Implement NFRs for system reliability
- Participate in on-call rotation for continuous delivery of machine learning services
Requirements For Machine Learning Engineer
- Prior experience with productionising ML systems
- Experience training machine learning models
- Advanced knowledge of Python and SQL
- Knowledge of Terraform and Terragrunt for Infrastructure as Code
- Experience with real-time systems like Kafka, Kafkaconnect, Redpanda, Pub/Sub
- Experience with Kubernetes, docker, deployment types
- Experience with CI/CD systems
- Experience with Big Data technologies
- Experience with MLOps tools
- Experience with cloud providers (GCP preferred)
- Interest in FinTech, crypto, or web3
Benefits For Machine Learning Engineer
- Equity package
- Unlimited holidays
- Paid parental leave
- Annual training budget
- Home office setup allowance
- Monthly budget to spend on company products
- Freedom, autonomy and responsibility
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