Arkose Labs is on a mission to create an online environment where all consumers are protected from spam and abuse. As a Fast Company 2025 Best Workplace for Innovators, we provide a proactive fraud deterrence platform, Arkose Titan, designed to neutralize modern attacks powered by Agentic AI and LLMs. By combining proprietary intelligence with dynamic friction, we undermine attacker ROI to protect global giants like Microsoft, Meta, and Roblox. Headquartered in San Mateo, CA, we maintain a global presence across APAC, Central and South America, and EMEA.

Position Overview:

As a Sr. Machine Learning Researcher specializing in security, you will apply your expertise in machine learning and cybersecurity to develop innovative solutions to detect, prevent, and respond to security threats and fraud. You will conduct independent research, collaborate with cross-functional teams, and stay abreast of the latest advancements in the field.

Key Responsibilities:

Develop and implement ML and deep learning models to detect and mitigate security threats.
Developing new product features using statistical/machine learning-based algorithms to identify bot and fraud traffic
Conduct data cleaning, preprocessing, and exploratory data analysis. Apply statistical methods to analyze security-related data.
Stay updated with the latest research and advancements in ML and cybersecurity. Publish research findings in reputable journals and conferences.
Collaborate with cross-functional teams to understand project requirements and contribute to the development of solutions.
Collaborate with security analysts, software engineers, and other stakeholders to integrate ML solutions into security products.
Communicate complex technical concepts to both technical and non-technical stakeholders effectively.

Must Have:

Bachelor's, Master's, or PhD in Computer Science, Machine Learning, Artificial Intelligence, or a related field.
Proficiency in ML algorithms, neural networks, and model development.
Experience with ML frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn).
Strong coding skills in Python, R, and familiarity with languages such as C++, Java, or Scala.
Ability to perform data cleaning, preprocessing, and exploratory data analysis.
Strong understanding of statistical methods and their applications.
Familiarity with cybersecurity concepts, threat models, and common attack vectors.
Experience with security tools and technologies (e.g., intrusion detection systems, firewalls, malware analysis tools).
Strong analytical and problem-solving skills to identify and mitigate security threats using ML techniques.
Understanding of network security, bot security, application security, and incident response.

Nice to Have

Experience with bot detection, device fingerprinting, behavioral biometrics, or real-time risk scoring.
Experience with low-latency, high-throughput ML serving infrastructure.
Familiarity with current ML research relevant to fraud/security (e.g., following or contributing to arXiv publications in adversarial ML, anomaly detection, or graph learning).
Experience scaling researcher productivity using Agentic AI.

Why Arkose Labs?

At Arkose Labs, our technology-driven approach enables us to make a substantial impact in the industry, supported by a robust customer base consisting of global enterprise giants such as Microsoft, Roblox, and more. We’re not just a company; we’re a collaborative ecosystem where you will actively partner with these influential brands, tackling the most demanding technical challenges to safeguard hundreds of millions of users across the globe.

Why do top tech professionals choose Arkose Labs?

Cutting-Edge Technology: Our high-efficacy solutions, backed by solid warranties, attract leading, global enterprise clients. Innovation and Excellence: We foster a culture that emphasizes technological innovation and the pursuit of excellence, ensuring a balanced and thriving work environment. Experienced Leadership: Guided by seasoned executives with deep tech expertise and a history of successful growth and equity events. Ideal Size: We’re structured to be agile and adaptable, large enough to provide stability, yet small enough to value your voice and ideas.

Join us in shaping the future of technology. At Arkose Labs, you’re not just an employee; you’re part of a visionary team driving global change

The most recognizable brands in the world select Arkose Labs, including Roblox, Microsoft, Adobe, Expedia, Snap and Meta.

We value your unique contributions, perspectives, and experiences. Be part of a diverse and high-performing environment that prioritizes collaboration, excellence, and inclusion. We hire the best, focus on their professional development, and offer support for continuing education.

We value:

People: first and foremost they are our most valuable resource. Our people are independent thinkers who make data driven decisions and take ownership and accountability in all the things they do.
Team Work. We demonstrate respect, trust, integrity, and communicate openly with a positive can do attitude and constructively challenge one another
Customer Focus . We empathize with our customers and obsess about solving their problems
Execution with precision, professionalism and urgency
Security . It’s the lens through which we implement our processes, procedures, and programs

Benefits:

Competitive salary + Equity
Beautiful office space with many perks
Robust benefits package
Provident Fund
Accident Insurance
Hybrid office model with flexible working hours and work from home days to support personal well-being and mental health

Arkose Labs is an Equal Opportunity Employer that makes employment decisions without regard to race, color, religious creed, national origin, ancestry, sex, pregnancy, sexual orientation, gender, gender identity, gender expression, age, mental or physical disability, medical condition, military or veteran status, citizenship, marital status, genetic information, or any other characteristic protected by applicable law. In addition, Arkose Labs will provide reasonable accommodations for qualified individuals with disabilities.

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Senior Machine Learning Researcher

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