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This job is closed
We are hiring for one of our ecosystem projects. The company is shifting the future of value extraction.
They are the next generation automated smart contract auditing system focusing on Zero-Day Exploits. They are a blockchain security startup, composed of industry security researchers and scholars, providing top-notch security solutions through our technology precipitation and innovative research.
Their security solutions rely on computation intensive with automation rather than labor intensive, significantly reducing the cost of auditing. They see value extraction on smart contracts as a 2-step black box optimization process. They facilitate the search by algorithmic parsing, efficient stateful computation techniques, and innovative feedback mechanisms.
The Role
We are seeking a skilled optimisation researcher with expertise. You will work closely with the research driven CEO and extend the technicality of the company'sautomation and optimization process.
You will be responsible for developing algorithms for general value extraction on smart contracts, which can be treated as different sophisticated forms of test functions. Web3 experience is not necessary. The ideal candidate will possess a deep understanding of black-box optimization and fuzzing techniques coupled with proficiency in researching and developing Machine Learning (ML) methods for discrete and continuous optimization. Moreover, experience in High-Frequency Trading (HFT) is highly desirable.
In this role, you will:
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Conduct cutting-edge research in optimization and fuzzing techniques and apply in Web3 domain, focusing on vulnerability detection, protocol analysis, and security enhancements.
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Develop innovative methods for discrete optimization for test suite generations through a deep understanding of the nature of different runtime and smart contracts.
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Develop innovative algorithms for optimizing the searching processes with comprehensive coverage for different types of value extractions.
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Apply ML-based approaches to enhance the effectiveness and efficiency of the searching frameworks in identifying vulnerabilities and defects.
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Develop a benchmark to evaluate the efficacy of different algorithms independently.
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Collaborate internally with engineers and advise externally with cross-functional teams, including scholars and security researchers, to integrate ML optimization techniques into existing Mamori architecture.
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Utilize HFT expertise to explore potential applications and adaptations of optimization techniques in financial systems and blockchain-based trading platforms.
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Stay updated with the latest advancements in fuzzing and ML optimization, proposing novel approaches for continuous improvement.
You might thrive in this role if you have:
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Strong background in optimization and fuzzing techniques, including experience in web application fuzzing and solving test functions for optimization problems.
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Proficiency in researching and developing ML or optimization methods for continuous optimization problems, ideally with a focus on improving searching processes.
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Proficiency in researching and developing test suite generation in computer systems, ideally with understanding of different blockchain runtime environments and nature of smart contracts.
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Solid understanding of vulnerabilities, computation and security challenges in web applications and blockchain ecosystems.
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Experience in High-Frequency Trading (HFT) with a deep understanding of trading platforms, algorithmic strategies, and market dynamics is highly desirable.
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Excellent programming skills in languages such as Python, C/C++, or Rust.
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Strong problem-solving and analytical abilities, with an intellectual curiosity in exploring new techniques and driving innovation.
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Effective communication skills to collaborate with diverse teams and present research findings and recommendations
Why work with us
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You’ll work on extremely challenging and unseen problems to overturn the industry
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You’ll shape the culture as an early employee and make impactful contributions from now
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You’ll be part of an adaptive, flat, result-driven organization
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You and your work will create a legacy and set an industry standard in automation on value extraction.
#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.