Machine Learning Jobs in Web3
207 jobs found
| Job Position | Company | Posted | Location | Salary | Tags |
|---|---|---|---|---|---|
FalconX | Remote | $105k - $108k | |||
Magic Eden | San Francisco, CA, United States | $180k - $220k | |||
Hologram Labs | New York, NY, United States | $122k - $156k | |||
Kraken Digital Asset Exchange | Remote | $63k - $75k | |||
| Learn job-ready web3 skills on your schedule with 1-on-1 support & get a job, or your money back. | | by Metana Bootcamp Info | |||
Heretic | San Francisco, CA, United States | $87k - $120k | |||
Heretic | San Francisco, CA, United States | $87k - $120k | |||
Heretic | San Francisco, CA, United States | $96k - $120k | |||
Heretic | San Francisco, CA, United States | $84k - $120k | |||
ZAUBAR | remote | $63k - $75k | |||
Ripple | Toronto, Canada | $54k - $60k | |||
Genies, Inc. | remote | $175k - $260k | |||
DApp360 Workforce | United States | $105k - $108k | |||
ChainGPT | Remote | $60k - $120k | |||
Aave Companies | London, United Kingdom | $90k - $110k | |||
Binance | Asia |
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This job is closed
Impact :
At FalconX, you’ll help create a more open financial system. In building trading, credit and custody infrastructure, we are enabling thousands more institutions to enter the market and support a more open and accessible financial system. The world’s largest financial institutions from Wall Street to Silicon Valley will turn to you for products that provide unparalleled seamless, efficient and secure access to the cryptocurrency sector.
FalconX is hiring a Machine Learning Engineer focused on our core platform stack to help introduce a new, in-demand product line for the company that integrates seamlessly with our proprietary, best-in-class Prime Brokerage platform. We are looking for an experienced Software Engineer with a background in building scalable, distributed systems as well as a strong understanding of blockchain, wallets, and platforms to build upon our vision of an open financial system.
Responsibilities:
- Hands-on Model Development and Optimisation: Actively participate in designing, developing, and optimizing the Large Language Model (LLM) to work efficiently for financial use cases, with a hands-on approach to fine-tuning the model for domain-specific terminology and context.
- Prompt Engineering: Leverage prompt engineering techniques to guide the LLM to produce desired responses. This includes crafting effective prompts and iteratively refining them based on the model's performance.
- Stay Up-to-date with Industry Trends: Keep up-to-date with the latest trends and advancements in AI, machine learning, and prompt engineering, particularly in relation to the financial industry, to ensure the product remains competitive and cutting-edge.
- Collaborative Engineering: Work closely with product managers and other relevant teams in a hands-on capacity to understand product requirements and customer needs, incorporating this feedback directly into model development and prompt engineering.
Qualifications:
- Bachelors or Masters degree in computer science
- Minimum 3 years of work experience
- Strong pedigree
- Experience in LLM or Natural Language Processing
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.