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| Job Position | Company | Posted | Location | Salary | Tags |
|---|---|---|---|---|---|
MoonPay | United Kingdom | $96k - $108k | |||
Bitso | Latin America | $126k - $131k | |||
Tether | Dubai, United Arab Emirates | $122k - $144k | |||
Tether | Warsaw, Poland | $122k - $144k | |||
| Learn job-ready web3 skills on your schedule with 1-on-1 support & get a job, or your money back. | | by Metana Bootcamp Info | |||
Tether | Amsterdam, Netherlands | $122k - $144k | |||
Tether | London, United Kingdom | $122k - $144k | |||
Tether | Islamabad, Pakistan | $122k - $144k | |||
Tether | Madrid, Spain | $122k - $144k | |||
Tether | Bangalore, India | $122k - $144k | |||
Tether | Dublin, Ireland | $122k - $144k | |||
Tether | Stockholm, Sweden | $122k - $144k | |||
Tether | Seoul, South Korea | $122k - $144k | |||
Genies | Remote | $90k - $118k | |||
OpenSea | New York, NY, United States | $125k - $215k | |||
Inmobi | Remote |
|
Senior Machine Learning Data Engineer
South Africa - Hybrid / United Kingdom - Hybrid / Spain - Hybrid / Romania - Remote / Poland - Remote / Portugal - Remote
Engineering â Software Engineering /
Full Time /
Hybrid
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đ About the Opportunity
Our engineering discipline builds the technology that enables MoonPay to learn quickly and scale easily. We organize in small cross-functional squads of 4-6 engineers and an embedded Product Manager and Product Data Analyst. We currently have squads across Crypto / NFT / Payments / FinCrime / KYC / Core Product and others. For this role, the initial focus will be on working on our FinCrime products, while mastering other product areas to then spearhead ML and AI adoption in the company.
đ What you will do
- Build and integrate data pipelines for ingesting data, processing and serving features in real-time in a high throughput/low latency environment
- Support multiple data models that serve critical data for FinCrime products (ML models, risk engine, etc.)
- Own our Feature Store development, expanding our feature engineering capabilities for stateless and stateful data for both offline and online serving
- Enhance our monitoring capabilities, adding new data alerts for drift, anomalies, latency, etc
- Analyze large datasets using SQL, Apache Beam and Polars to surface features
- Help build AI-powered automation tools or pipelines and propose improvements across the company
- Maintain and improve our existing codebase, expanding our internal Feature Store and ML libraries and pipelines
đ» What you will be working with/on
- Apache Beam
- Dataflow
- BigTable
- Redis
- BigQuery
- Python, Polars, Pandas and Numpy
- ML feature engineering for fraud prevention
- FastAPI, Docker, Kubernetes
- Kubeflow and Airflow
- Vertex AI
- Pydantic
- DataDog
- Github
đ§âđ About You
- Experienced in Data Engineering at leading Fintech startups or fast growing tech companies
- Curious about Machine Learning and with strong fundamentals about data modelling for feature generation
- Experienced with some of our tech stack, or are confident you can cross train and up skill quickly
- Understand data structures, pipelines and big data processing for real-time consumption
- Real world experience working with feature stores (in-house or vendor based e.g. Tecton)
- Experienced with Cloud Native applications such as Google Cloud or similar e.g. AWS, Azure
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What an AI Developer does?
An AI developer is someone who creates and builds artificial intelligence systems
Their responsibilities may include designing and implementing algorithms, creating and training machine learning models, and deploying AI systems to solve practical problems
Additionally, they may be responsible for maintaining and improving existing AI systems, as well as collaborating with other teams or individuals to integrate AI technology into larger systems.