Artificial Intelligence Programmer Specializing in Machine Learning
Immunefi, the foremost Bug Bounty Marketplace in the crypto/Web3 space, is on the hunt for a skilled and autonomous Machine Learning Engineer. With a focus on preventing catastrophic hacks in decentralized finance, Immunefi operates in a dynamically evolving market and aims for excellence, building a world-class team of highly skilled professionals.
Role and Responsibilities
As a Machine Learning Engineer at Immunefi, you will be handling, transforming, and processing data, designing machine learning structures, and developing AI agents. A significant part of your role will involve designing, developing, and optimizing machine learning models to detect security vulnerabilities, anomalies, or threats in smart contracts and blockchain systems. You will collaborate with security experts to integrate ML insights into Immunefi’s security platform and conduct experiments, analyzing model performance, and iterating on model improvements.
Key Requirements
Strong programming skills, especially in Python, are essential for this role. A solid background in machine learning, AI, model training, and experimentation is a must. Experience with frameworks such as PyTorch or TensorFlow is typically expected. Familiarity with blockchain or Web3 security might be relevant given Immunefi’s specialization in smart contract security, though explicit ML relevance is not confirmed. Experience or interest in applying ML techniques to security analytics, vulnerability detection, or anomaly detection in blockchain environments could be essential.
Essential Skills
Proficiency in Python programming and ML libraries such as PyTorch, Hugging Face, or TensorFlow is essential. Strong analytical and problem-solving skills are necessary to interpret complex data and security issues. Understanding of blockchain technologies, smart contracts, and related vulnerabilities is crucial to tailor ML solutions effectively. The ability to communicate technical findings clearly to both technical and non-technical stakeholders is also important.
Work Environment
Immunefi offers a 100% remote-first work environment, flexible schedule, autonomous work environment, opportunity to build an early-stage company, opportunity to build one's own path, a global market, and the chance to make an impact and participate in building and securing the ecosystem for smart contracts and the future of money. The team is fully remote and geographically dispersed, requiring autonomous and self-driven work across global timezones. The work environment at Immunefi is highly collaborative, cross-functional, and requires rapid immersion.
Since Immunefi focuses on Web3 and smart contract security, the role may uniquely combine machine learning expertise with deep blockchain knowledge to enhance security solutions. If you seek the exact official job description, Immunefi’s career page or job boards may have up-to-date and detailed postings. The above reflects an inferred profile from related data points in the search results.
- As a Machine Learning Engineer at Immunefi, you will be utilizing your skills in data-and-cloud-computing, such as handling, transforming, and processing data, designing machine learning structures, and developing AI agents, while also focusing on artificial-intelligence, specifically designing, developing, and optimizing machine learning models to detect security vulnerabilities in the world of blockchain and smart contracts.
- With a key requirement of strong programming skills in Python and expertise in machine learning, AI, model training, and experimentation, the ideal candidate for this 100% remote-first role at Immunefi will possess essential skills in Python programming and ML libraries such as PyTorch, Hugging Face, or TensorFlow, combine these skills with an understanding of blockchain technologies, smart contracts, and related vulnerabilities, and have the ability to clearly communicate technical findings to both technical and non-technical stakeholders within a highly collaborative, cross-functional, and globally dispersed work environment.
