Data Science is at the core of TRM's mission to build a safer financial system for billions of people. To achieve such goal, the Data Science team relies on a diverse set of structured and unstructured data to design, build, and support machine learning models to detect and prevent fraud and financial crime in cryptocurrencies and digital assets. As our platform grows, the Data Science team will be building a scalable foundation to propel our impact and product forward.As a Machine Learning Engineer at TRM Labs, you will collaborate with an experienced team of engineers, data scientists, and product managers to build scalable systems to detect, prevent, and mitigate cryptocurrency fraud and financial crime. You will be deeply involved in the technical details of building highly available and real-time risk detection services to understand the ever evolving attack vectors in crypto and to build a safer financial system for billions of people.Your Responsibilities* Build machine learning system to detect high-risk activities like money laundering, terrorist financing, human trafficking, account takeovers, and credit card fraud. This will consist of feature engineering / storage, deep learning training pipelines, offline evaluation systems, and online serving infrastructure.* Push the boundary of natural language processing (NLP) technologies and combine artificial and human intelligence to extract illicit activity on the DarkWeb, Social Media Platforms, and other forums.* Working cross-functionally with engineering and data science teams to define and expand labels for model training, productionize real-time machine learning models, and conduct independent research projects to drive our innovation forward* Developing your skills through exceptional training as well as frequent coaching and mentoring from colleaguesSome of the Traits we value* Advanced graduate degree in quantitative field* 3+ years industry experience developing production machine learning systems at scale from inception to business impact. Proven ability to tailor your solutions to business problems in a cross-functional team.* Basic understanding of modern machine learning techniques and their mathematical underpinning, such as classification, clustering, optimization, deep neural network and natural language processing.* Engineering skills. This is a hybrid research/engineering role. You'll be responsible for productionizing your pipelines/models and integrating against our back-end services.* Experience in one or more of the following languages: Python (preferred), Scala (preferred), Java, C++, or other equivalent languages.* Experience with large scale data processing is a plus (Hive, Spark preferred)* Adaptable. Goals can change fast. You anticipate and react quickly.* Autonomous. You own what you work on. You move fast and get things done.* Excellent communication. You will need communicate complex ideas effectively to both technical and non-technical audiences, and both verbally and in writing* Collaborative. You must work collaboratively in a cross-functional team and with people at all levels in an organization* Relevant experience in crypto/blockchain is a plusBenefits* Stock* $2,000 yearly coupon for books, conferences, and professional coaching* Competitive salary* Paid time off* Volunteer time off* Parental leave* Medical, dental, & vision insurance* Life & disability coverage* 401K* Apple equipment* Daily lunch and dinnerWhy usWe work with the best. TRM is YC-backed and funded by Blockchain Capital, the leading blockchain VC firm. Our customers include the world's top digital asset companies.Strong engineering and product culture. Collectively, we've researched machine learning at Harvard and Stanford, led strategy teams at McKinsey, built data pipelines at Facebook and shipped distributed apps at Amazon and OpenDoor.Our culture is creative, collaborative, and hypothesis-driven. We focus on creating the best products possible with low ego and high productivity.TRM Labs is an equal opportunity employer.
Associated topics: .net, application, back end, develop, devops, python, sdet, software developer, software development engineer, software engineer