Senior Machine Learning Researcher

About this job

As a Senior Machine Learning Researcher at Arkose Labs in Pune, India, you will play a crucial role in developing innovative machine learning solutions to protect online consumers from spam, abuse, and fraud. Arkose Labs provides a proactive fraud deterrence platform called Arkose Titan, which neutralizes modern attacks powered by Agentic AI and LLMs to safeguard global giants like Microsoft, Meta, and Roblox. In this role, your daily work involves building and implementing deep learning models, creating product features using statistical and machine learning algorithms to spot bot and fraud traffic, and conducting exploratory data analysis. You will stay updated on the latest research in ML and cybersecurity, publish your findings, and work closely with cross-functional teams, security analysts, and software engineers to integrate your ML solutions directly into security products while communicating complex technical ideas clearly.

Responsibilities

• Develop and implement ML and deep learning models to detect and mitigate security threats.
• Build new product features using statistical and machine learning algorithms to identify bot and fraud traffic.
• Conduct data cleaning, preprocessing, exploratory data analysis, and apply statistical methods.
• Stay updated with latest research in ML and cybersecurity, and publish findings in journals and conferences.
• Collaborate with cross-functional teams, security analysts, and software engineers to integrate ML solutions.
• Communicate complex technical concepts to both technical and non-technical stakeholders effectively.

Requirements

• 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 such as TensorFlow, PyTorch, and scikit-learn.
• Strong coding skills in Python, R, and familiarity with languages like C++, Java, or Scala.
• Strong understanding of statistical methods, data cleaning, preprocessing, and exploratory data analysis.
• Familiarity with cybersecurity concepts, threat models, attack vectors, and security tools.
• Strong analytical and problem-solving skills with an understanding of network, bot, and application security.

Good 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 and security like adversarial ML or graph learning.
• Experience scaling researcher productivity using Agentic AI.

Who should apply

This role suits experienced machine learning and cybersecurity professionals who possess a strong background in developing deep learning models, statistical analysis, and threat detection. Candidates should have a relevant degree in computer science or AI, along with strong coding skills in Python and experience with major ML frameworks. Because the posting does not mention freshers, experienced professionals with a solid understanding of cybersecurity concepts and security tools are best suited to tackle these technical challenges.

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