Junior Researcher Zero Knowledge Cryptography & Machine Learning Job in Canada Recruiting by Inference Labs Inc.

Researcher Zero-Knowledge Cryptography & Machine Learning | Inference Labs - Verified IntelligenceLocation: RemoteAbout Inference Labs:Inference Labs is more than just a technology company; we're spearheading a new era in Artificial Intelligence. Advocating for decentralized, computationally verified AI systems while utilizing Web3 technology, we aim to challenge the dominance of large tech corporations with our modular, composable AI solutions. Our vision encompasses building infrastructures, protocols, and applications to make AI more accessible, democratizing AI access while promoting frictionless exchange of value and Proof of Inference.Job Description:At Inference Labs, we operate at the cutting edge of a multitude of dimensions across artificial intelligence, zero-knowledge cryptography, and decentralized networks. Central to this role is the ability to effectively communicate complex research findings in machine learning, data science, and cryptography.  You will be tasked with not only exploring deep theoretical concepts but also making them accessible to a broader audience, breaking down complex ideas and challenges in AI, cryptography, and Web3 technology into understandable segments. This role is crucial for advancing the next frontier of innovation in applying cryptographic principles to Artificial Intelligence, making it essential for candidates to possess both a profound understanding of these domains and the skill to articulate this knowledge clearly and engagingly.The work you will be doing:In your role at Inference Labs, you'll be immersed in experimentation, ideation, and collaboration with both engineers and academics. Your goal will be to push the boundaries of the field by staying abreast of cutting-edge research and the latest advancements from in our sector. We value contributions to the body of knowledge in our field, often seen in the form of research papers stemming from post graduate level internships.What you’ll bring:Experience building Machine Learning applications or other Data Science tooling with a strong interest in Machine Learning & related infrastructure; experience with time series analysis and high-frequency event data like financial markets tick data a huge plusExperience with modern cloud ML architecture. We don’t discriminate by language or ML Framework but you could have built ML projects using a combination of Python, Scala, Java, Spark; and have used frameworks like scikit-learn, Tensorflow, Torch, or KerasInterests: entrepreneurship, economics and financial markets, strong work ethic, creative thinking, systems thinking, cryptography, creative logicKey Researcher Responsibilities:Conduct research into machine learning algorithms and data science methodologies.Analyze and evaluate the performance of machine learning models within zero-knowledge circuits, adapting them to evolving research needs.Perform rigorous security assessments and statistical analyses, benchmarking machine learning systems, and identifying areas for improvement.Effectively communicate complex research findings in the domains of machine learning and data science, breaking down intricate problems for a broad audience.Qualification:We are in pursuit of individuals with a deep-seated passion and inquisitiveness in their field, demonstrated through recent research papers or projects, and who possess an eagerness to dive into challenges and pursue solutions relentlessly.  We are interested in individuals who strike a balance between academic excellence and a practical mindset.Lacking some experience in the listed responsibilities? No worries. At Inference Labs, we're on the hunt for a diverse array of individuals to join our team. If you're enthusiastic about thriving in our dynamic, remote-friendly, and start-up ambiance—and believe you have the chops for this gig despite not ticking every box—throw your hat in the ring. Let us know about the transferable skills you bring to the table in your cover letter. Our conception of the ideal candidate is strong, but we're open to being swayed. Show us what you've got!Hiring Process:Initial pre-screen with our talent acquisition providerIndividual interview with a founderTeam interviewBrief programming or research taskNote: Interview stages are subject to change.Compensation:Paid Internship, Co-op, or Full time salaried, negotiable based on skills and experience.Important to note that actual compensation can be influenced by a host of factors such as your educational background, professional training, unique credentials, the skill set you possess, your location, and your experience.