Machine Learning Jobs in Web3

207 jobs found

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Job Position Company Posted Location Salary Tags

Chainalysis

New York, NY, United States

$54k - $90k

Zash

Remote

$50k - $70k

Braintrust

San Francisco, CA, United States

$32k - $72k

Gemini

United States

$45k - $100k

Steel Perlot

Los Angeles, CA, United States

$81k - $100k

Anima

New York, NY, United States

$0k

Blockchain.com

San Francisco, CA, United States

$39k - $70k

Realto Group

Bengaluru, India

$115k - $14k

Realto Group

Bengaluru, India

$115k - $14k

Tech Mahindra

Guadalajara, Mexico

$27k - $90k

Braintrust

San Francisco, CA, United States

Zama

Remote

Worldcoin

remote

$81k - $110k

Ripple

New York, NY, United States

$61k - $80k

ZORA

Remote

$98k - $156k

Senior Machine Learning Engineer

Chainalysis
$54k - $90k estimated

This job is closed

The global financial ecosystem is changing. Revolutionary blockchain technology has unlocked the potential for people around the world to have more equal access to wealth and information. This transformation has begun with the mass global adoption of cryptocurrencies but like all new financial systems, it needs greater trust to realize its full potential and remain safe from bad actors. That’s where we come in. The Chainalysis blockchain data platform enables businesses, governments, and banks to solve the world’s most high-profile criminal cases, paving the way for an economy built on blockchains.

ML Engineers are embedded in our blockchain analytics teams within Engineering. This team partners with research and investigation teams, helping mastermind the algorithms and models that solve cases ranging from Twitter hacks to bringing down one of the largest child abuse networks in the world. ML Engineers in the Data Intelligence group have a deep understanding of various protocols, are experts at identifying transaction patterns, develop new techniques to analyze blockchain data and participate in complex investigations if needed. We measure success by the insights we can surface to our customers about the activity on a given blockchain and the accuracy of those insights.

In one year you’ll know you were successful if…

  • You have earned the ins and outs of our blockchain analysis techniques
  • Developed new techniques and algorithms that are used in production
  • Conducted complex investigations that resulted in success for our customers
  • Have become an expert in analyzing one or more blockchains
  • Contributed to the effectiveness and velocity of team deliverables

A background like this helps:

  • A solid understanding of graph models, algorithms, analysis, and frameworks
  • Proven experience with running batch and streaming based analytical models in production
  • Understanding of efficient data structures, algorithms and computational complexity
  • Planned, built, and owned production systems
  • Experience with Python, Pandas, and SQL
  • The versatility and willingness to learn new technologies on the job
  • The ability to clearly communicate complex results to technical and non-technical audiences
  • Bias for action

The following would differentiate you:

  • Deep understanding of one or more blockchains from both a protocol and data perspective
  • Experience with statistical analysis on real world datasets
  • Experience with big data technologies like Hadoop or Spark
  • Build and deployed production models using frameworks like Keras, TensorFlow, and/or PyTorch
  • Experience with graph traversal and computation
  • Data Visualization experience using matplotlib, ggplot, bokeh, d3.js etc
  • Experience with Java and/or Scala

#LI-BD1 #LI-Remote

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.