Machine Learning Jobs in Web3

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Job Position Company Posted Location Salary Tags

Braintrust

San Francisco, CA, United States

Zama

Remote

Worldcoin

remote

$81k - $110k

Ripple

New York, NY, United States

$61k - $80k

ZORA

Remote

$98k - $156k

TipTop

Remote

$165k - $260k

Waivlength

Remote

$140k - $180k

Next Big Thing AG

Berlin, Germany

Foundry

New York, NY, United States

$61k - $80k

Next Big Thing AG

Berlin, Germany

Ripple

San Francisco, CA, United States

$45k - $100k

Next Big Thing AG

Berlin, Germany

Next Big Thing AG

Berlin, Germany

Next Big Thing AG

Berlin, Germany

Next Big Thing AG

Berlin, Germany

Machine Learning Engineer Python Scala Hadoop Hive [REMOTE]

Braintrust

This job is closed

  • JOB TYPE: Freelance, Contract Position (no agencies/C2C - see notes below)
  • LOCATION: United States only - Remote (TimeZone: PST/CIST| Partial overlap)
  • HOURLY RANGE: Our client is looking to pay $110 – $145/hr
  • ESTIMATED DURATION: 40hr/week - Long-term

THE OPPORTUNITY

Requirements

• Python, Scala
• Kafka, Structured Streaming, Kinesis
• Spark, Hadoop and Hive
• Industrial Software Engineering Experience – CI/CD, Unit Testing, Working on projects with multiple team members.

Top Skills

AI (Artificial Intelligence)
AWS
Python

What you’ll be working on

This is a W2/salaried contract. The pay rate reflects the fact it's a W2 engagement.

Responsibilities
• Ability to write robust code in one or more of Python, Java and Scala
• Familiarity with machine learning frameworks (like Keras or PyTorch) and libraries (like scikit-learn)
• Experience using Amazon Web Services (EC2, S3 etc) with data at scale
• Proficient in core technologies like Spark, Hadoop and Hive.
• Excellent communication skills
• Ability to work in a team
• Design, develop, debug, and modify components of machine learning and deep learning systems and applications, including data pipelines.
• Develop and tune model training and inference systems.
• Complete documentation and procedures for installation and maintenance.
• Actively participate in group technology reviews to critique work of self and others.
• Work collaboratively with all members of technical staff. Collaborate with data scientists, program managers, and product managers in the development of assigned components.
• Participate in and provide input to requirements definition.
• Run machine learning tests and experiments
• Implement appropriate ML algorithms
• Study and transform data science prototypes
• Research and implement appropriate ML algorithms and tools
• Select appropriate datasets and data representation methods
• Train and retrain systems when necessary
• Extend existing ML libraries and frameworks Qualifications
• Proven experience as a Machine Learning Engineer or similar role: 4-5 years of experience in software development.
• Understanding of data structures, data modeling and software architecture
• Knowledge of math, probability, statistics and algorithms
• Knowledge of streaming platforms like Kafka and Kinesis.
• Basic knowledge of various ML model platforms.
• Experience standing up model inferencing API endpoints.
• Exposure to No SQL databases like MongoDB.
• Experienced in using SQL for querying data from relational tables.
• Excellent analytical and problem solving skills with an aptitude for troubleshooting issues.
• Degree with strong technical focus (Computer Science, Engineering).

Apply Now!

#PL-BT

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.