Senior Manager, Machine Learning

About this job

Arkose Labs focuses on protecting consumers from online spam and abuse by building a proactive fraud deterrence platform named Arkose Titan. The company helps secure major global organizations such as Microsoft, Meta, and Roblox. As a Senior Manager of Machine Learning based in Pune, you will lead the machine learning team and guide the technical direction for fraud detection and risk-scoring products. This position functions as a builder-manager role where you will mentor and grow a compact, high-impact team while simultaneously remaining involved in hands-on model design, architecture choices, and code reviews. Your daily work involves connecting business and fraud outcomes like detection accuracy and false positive rates to the machine learning systems that power them, while collaborating closely with detection engineering to turn emerging fraud patterns into reliable features and models.

Responsibilities

• Define and drive data science and machine learning roadmaps across Arkose Titan.
• Lead the creation of machine learning models for real-time fraud and risk decisioning.
• Establish modern MLOps practices covering model governance and end-to-end lifecycle management.
• Drive applied research in graph machine learning, behavioral analytics, and fraud detection.
• Manage, mentor, and expand a team of machine learning researchers.
• Contribute directly to model design, feature engineering, architecture reviews, and code reviews.
• Translate fraud and business metrics into measurable machine learning objectives.

Requirements

• 10+ years of experience building and deploying machine learning models in production.
• 2+ years of direct experience managing machine learning engineers or data scientists.
• Track record of shipping machine learning systems that impacted business metrics in adversarial domains.
• Strong technical depth in evaluation modeling and architecture choices like classification or anomaly detection.
• Experience across the complete machine learning lifecycle from data pipelines to monitoring.
• Demonstrated people-management skills in hiring, coaching, and developing individual contributors.
• Excellent cross-functional communication abilities for technical and non-technical stakeholders.

Good to have

• Experience with bot detection, device fingerprinting, behavioral biometrics, or real-time risk scoring.
• Experience working with low-latency and high-throughput machine learning serving infrastructure.
• Familiarity with current machine learning research relevant to fraud and security.
• Experience scaling researcher productivity using Agentic AI.

Who should apply

This role suits experienced technical leaders with a strong background in production machine learning, adversarial domains, and people management. Candidates should have extensive experience building scalable models and coaching research teams. Freshers cannot apply as the position requires significant senior-level industry experience.

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