Machine Learning Engineer
1 semana atrás
Who we are:
We are a leader in fraud prevention and AML compliance. Our platform uses device intelligence, behavior biometrics, machine learning, and AI to stop fraud before it happens. Today, over 300 banks, retailers, and fintechs worldwide use Sardine to stop identity fraud, payment fraud, account takeovers, and social engineering scams. We have raised $145M from world-class investors, including Andreessen Horowitz, Activant, Visa, Experian, FIS, and Google Ventures.
Our culture:
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We have hubs in the Bay Area, NYC, Austin, and Toronto. However, we maintain a remote-first work culture. #WorkFromAnywhere
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We hire talented, self-motivated individuals with extreme ownership and high growth orientation.
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We value performance and not hours worked. We believe you shouldn't have to miss your family dinner, your kid's school play, friends get-together, or doctor's appointments for the sake of adhering to an arbitrary work schedule.
Location: Remote - Brazil
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To be considered for this position, you must reside in one of the following cities:
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São Paulo: São Paulo, Campinas, São José dos Campos
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Rio de Janeiro: Rio de Janeiro
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Minas Gerais: Belo Horizonte
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Paraná: Curitiba
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Santa Catarina: Florianópolis
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About the Role:
We're on the lookout for a Machine Learning Engineer to spearhead the evolution of our device intelligence and fingerprinting systems. This isn't just a role; it's a chance to lead groundbreaking projects that directly combat fraud and enhance security for millions.
What You'll Do:
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Design and refine backend services using Golang to process and analyze device data, ensuring robustness and scalability.
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Collaborate closely with software engineers, product managers, and other stakeholders to integrate machine learning capabilities seamlessly into our products.
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Develop sophisticated algorithms leveraging high-entropy signals and probabilistic matching to revolutionize device identification.
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Dive into vast datasets to uncover insights, boosting the accuracy and reliability of our systems.
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Apply advanced machine learning models to enhance device recognition and effectively manage uncertainties.
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Maintain the highest standards of privacy and security, aligned with industry best practices and regulations.
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Foster a culture of continuous learning, and document processes clearly to ensure consistency across the team.
What We're Looking For:
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5+ years of experience in software engineering, with a focus on backend development; proficiency in Go or a similar language is essential.
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Bachelor's or Master's in Computer Science, Engineering, or a related discipline.
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Hands-on experience with applied machine learning and data-informed optimization, working with large-scale datasets using tools like PyTorch and Scikit-learn.
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Proficient in SQL for querying and analyzing large datasets.
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Comfortable working with both relational and non-relational databases.
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Proficient in English - from casual chats to formal reports.
Extra Points For:
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A strong understanding of cybersecurity principles, especially in device identification and fraud prevention.
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Experience managing cloud infrastructure (AWS, Google Cloud, or Azure).
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Knowledge of containerization tools (Docker, Kubernetes) and CI/CD pipelines.
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Understanding of modern browser APIs and high-entropy data collection techniques.
Compensation: Base pay range of $R330,000 - $R440,000 + Series C equity with tremendous upside potential + Attractive benefits
The compensation offered for this role will depend on various factors, including the candidate's location, qualifications, work history, and interview performance, and may differ from the stated range.
Benefits we offer:
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Generous compensation in cash and equity
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Early exercise for all options, including pre-vested
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Work from anywhere: Remote-first Culture
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Flexible paid time off, Year-end break, Self care days off
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Health insurance, dental, and vision coverage for employees and dependents - US and Canada specific
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4% matching in 401k / RRSP - US and Canada specific
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MacBook Pro delivered to your door
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One-time stipend to set up a home office — desk, chair, screen, etc.
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Monthly meal stipend
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Monthly social meet-up stipend
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Annual health and wellness stipend
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Annual Learning stipend
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Unlimited access to an expert financial advisory
Join a fast-growing company with world-class professionals from around the world. If you are seeking a meaningful career, you found the right place, and we would love to hear from you.
To learn more about how we process your personal information and your rights in regards to your personal information as an applicant and Sardine employee, please visit our Applicant and Worker Privacy Notice.
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