Machine Operator jobs

These models power our ad ranking and recommendation systems, helping advertisers reach the right users at the right time by accurately estimating engagement and conversion likelihood. By leveraging large-scale behavioral data, creative features, and contextual signals, we continuously improve the relevance and accuracy of our predictions. This drives key outcomes such as higher user engagement, stronger conversion performance, and better return on ad spend — enabling advertisers to achieve their goals while delivering a better experience for users.

• Design, implement, and maintain high-performance fraud detection models to identify and block fraudulent activities at the publisher, game, and user levels.
• Build and refine systems to analyze user behavior, transaction patterns, and contextual signals, enabling accurate and timely detection of suspicious or malicious activity.
• Ensure model quality and reliability by continuously monitoring performance, calibrating predictions, and addressing data drift or delayed feedback.
• Actively participate and work with other leads to set the long term direction for the team, plan and oversee engineering designs and project execution.
• Effectively communicate complex technical concepts to non-engineering stakeholders.

• Advanced degree (MS or Ph.D.) in Computer Science, Machine Learning, Statistics, related field, or equivalent practical experience.
• 5+ years of hands-on experience building and operating large-scale systems for detection, monitoring, or risk management in ads, payments, or related domains.
• 3+ years of experience designing and deploying fraud detection or anomaly detection models, user behavior modeling, or risk scoring systems.
• Significant experience in one or more general-purpose programming languages like Python, Go, Scala, C++ or similar.
• Knowledge of metric design, experimentation methodologies, and large-scale data analysis.

• Experience designing and productionizing optimization algorithms in an ad serving platform and/or other marketplaces.
• Experience with state-of-the-art control systems, reinforcement learning algorithms.

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

This position requires the incumbent to have a sufficient knowledge of English to have professional verbal and written exchanges in this language since the performance of the duties related to this position requires frequent and regular communication with colleagues and partners located worldwide and whose common language is English.

• Design, implement, and maintain high-performance CTR and CVR prediction models that power ad ranking and recommendation systems.
• Build and refine systems for creative understanding and user behavior modeling, enabling more accurate and context-aware engagement predictions.
• Ensure model quality and reliability by continuously monitoring performance, calibrating predictions, and addressing data drift or delayed feedback.
• Actively participate and work with other leads to set the long term direction for the team, plan and oversee engineering designs and project execution.
• Effectively communicate complex technical concepts to non-engineering stakeholders.

• Advanced degree (MS or Ph.D.) in Computer Science, Machine Learning, Statistics, related field, or equivalent practical experience.
• 5+ years of hands-on experience building and operating large-scale Ads delivery and optimization systems.
• 3+ years of experience building CTR/CVR systems, content understanding, or behavior modeling systems.
• Significant experience in one or more general-purpose programming languages like Python, Go, Scala, C++ or similar.
• Knowledge of metric design, experimentation methodologies, and large-scale data analysis.

• Experience designing and productionizing optimization algorithms in an ad serving platform and/or other marketplaces.
• Experience with state-of-the-art control systems, reinforcement learning algorithms.

• International relocation support is not available for this position.

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

This position requires the incumbent to have a sufficient knowledge of English to have professional verbal and written exchanges in this language since the performance of the duties related to this position requires frequent and regular communication with colleagues and partners located worldwide and whose common language is English.

• Design, implement, and scale AI agents that assist in generating game code and executing goal-directed behaviors.
• Define orchestration logic for single- and multi-agent systems
• Develop reusable agentic frameworks - planning modules, memory systems, or policy adaptation layers - for creator extensibility.
• Lead high-impact initiatives, including hierarchical reinforcement learning for scalable behaviors, AI planning and goal inference frameworks for NPCs and simulations, and agent memory and world modeling systems for persistent, believable behavior.
• Collaborate across internal and external teams to unlock innovative use cases in gaming, simulation, and interactive storytelling.
• Contribute to the long-term vision and roadmap for Unity’s agentic AI offerings, ensuring modularity, usability, and performance across platforms.
• Establish and champion best practices for model quality, simulation-based evaluation, and ML/AI safety within real-time systems.

• Advanced degree (MS or Ph.D.) in Computer Science, Machine Learning, or a related field.
• 5+ years of hands-on experience developing ML systems in production, ideally within real-time or interactive environments.
• Experience with multi-agent systems, orchestration, or AI tool integration.
• Strong background in one or more of the following: LLM, reinforcement learning, decision-making under uncertainty, AI planning, or multi-agent systems.
• Proficiency in at least one general-purpose programming language (e.g., Python, C++, Go, Java) and familiarity with ML frameworks (e.g., PyTorch, TensorFlow).
• Strong system design skills and the ability to architect performant, scalable ML systems.
• Excellent communication and collaboration skills; ability to work effectively with cross-functional teams including engine developers, designers, and product managers.

• Familiarity with game development workflows.
• Publications or open-source contributions in reinforcement learning, agent-based modeling, or related areas.
• Experience with behavior trees, utility AI, or hierarchical task planning.
• Passion for the gaming industry and AI applications in games.

• Relocation support is not available for this position.

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

This position requires the incumbent to have a sufficient knowledge of English to have professional verbal and written exchanges in this language since the performance of the duties related to this position requires frequent and regular communication with colleagues and partners located worldwide and whose common language is English.