Machine Learning Jobs in Web3

277 jobs found

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Job Position Company Posted Location Salary Tags

NOYA Network

Remote

Gauntlet

United States

$150k - $180k

Ionicpartners

United States

$81k - $100k

OpenZeppelin

United States

$63k - $90k

Storm2

San Francisco, CA, United States

$150k - $200k

Gauntlet

New York, NY, United States

TRM Labs

Remote

$98k - $156k

Yakoa

San Jose, CA, United States

$98k - $156k

Gauntlet

New York, NY, United States

$60k - $90k

Supermind

Bengaluru, India

$50k - $86k

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

Web3 Machine Learning Engineer Quantitative Strategist

NOYA Network

This job is closed

NOYA is hiring a Web3 Machine Learning Engineer - Quantitative Strategist 

NOYA is a native Omnichain yield aggregator that non-custodially allows users to farm protocols Omnichain efficiently.

We seek quantitative researchers and machine learning engineers interested in solving diverse and complex business problems. You will leverage your experience and communication skills to work across business teams to build and develop innovative quantitative models and algorithms.

·Develop core algorithms and models leading directly to better risk, trading, and lending

·Be able to distill complex models and analysis into compelling insights for our users

·Ensure data quality throughout all stages of acquisition and processing

·Stay up-to-date with data science tools and methodologies 

·Knowledge of probability and statistics, including time series, predictive modeling, optimization, and causal inference. Experience in design and deployment of real-world, large-scale, user-facing systems

Qualifications:

·Expertise in quantitative research, portfolio management, risk management, and/or trading

·Experience as a quantitative analyst/developer/trader. Must have some experience in quantitative modeling/trading.

·2+ years of experience deploying statistical, time series, and/or machine learning models in production

·Passion for DeFi and crypto, including a deep understanding of AMMs (Uniswap V3 Optimizations) while proactively engaging in new developments 

·2+ years of experience in integrating quantitative models into applications

·Skilled in programming languages like Python, Java/C++/C#, and SQL

·Sound knowledge in dealing with large data sets for analytical approaches and quantitative methods

·Ability to analyze a wide variety of data: structured and unstructured, observational and experimental, to drive system designs and product implementations

·Experience with one or more big data tools and technologies like Snowflake, Databricks, S3, Hadoop, Spark

·Strong technical and business communication

Compensation and Benefits:

Compensation: We understand that top talent deserves top pay, which is why we offer a competitive compensation package consisting of both crypto remuneration and an equity/token pckage in NOYA.

Flexible schedule: We believe that our team members work best when they're happy and fulfilled, which is why we offer a flexible work schedule that allows you to work from anywhere in the world and manage your own time.

Intellectual freedom: We believe that the best ideas come from individuals who are free to explore and innovate. That's why we offer our team members the intellectual freedom to develop novel models and frameworks for innovative financial products and turn ideas, theories, and research into real-impact implementations.

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.