Machine Learning Jobs in Web3

283 jobs found

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Job Position Company Posted Location Salary Tags

MoonPay

United Kingdom

$96k - $108k

Bitso

Latin America

$126k - $131k

Genies

Remote

$90k - $118k

Zscaler

Remote

$122k - $150k

Tether

Medellin, Colombia

$115k - $120k

Tether

Dublin, Ireland

$115k - $120k

Tether

TI Lugano CH

$115k - $120k

Tether

Stockholm, Sweden

$115k - $120k

Tether

Cairo, Egypt

$115k - $120k

Tether

Bangalore, India

$115k - $120k

Tether

Lisboa, Portugal

$115k - $120k

Tether

Dubai, United Arab Emirates

$115k - $120k

Tether

Rio De Janeiro, Brazil

$115k - $120k

Tether

Amsterdam, Netherlands

$115k - $120k

Tether

Buenos Aires, Argentina

$115k - $120k

MoonPay
$96k - $108k estimated
United Kingdom - Hybrid
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Senior Machine Learning Data Engineer

South Africa - Hybrid / United Kingdom - Hybrid / Spain - Hybrid / Romania - Remote / Poland - Remote / Portugal - Remote
Engineering – Software Engineering /
Full Time /
Hybrid

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🌔 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.

🚀 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

đź’» 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

🧑‍🚀 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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Is machine learning a good career?

Yes, machine learning is a rapidly growing field and can be a very promising career option for those interested in it

As businesses and industries increasingly rely on data to drive decision-making, there is a growing need for skilled professionals who can analyze and make sense of this data

Machine learning, which involves developing algorithms that can learn from and make predictions on large datasets, is a crucial part of this process

Machine learning careers can range from data analysts, machine learning engineers, data scientists, and more

These professionals work in a variety of industries, including finance, healthcare, e-commerce, and technology

The demand for machine learning experts is high, and the salaries in this field are also generally quite competitive

However, it's important to note that machine learning can be a complex field that requires a strong background in mathematics, statistics, and computer science

It also requires ongoing learning and staying up-to-date with the latest developments and tools in the field

If you enjoy working with data, have a strong interest in programming, and are willing to put in the effort to stay current with developments, a career in machine learning can be very rewarding.