Machine Learning Manager - Ads Engagement Modeling

Posted 14 days agoViewed

💎 Seniority level: Manager, 2+ years of management experience, 6+ years working with machine learning models at scale, 4+ years hands-on experience with TensorFlow or PyTorch

📍 Location: United States, Canada

💸 Salary: 230000.0 - 322000.0 USD per year

🔍 Industry: Social Media, Technology

⏳ Experience: 2+ years of management experience, 6+ years working with machine learning models at scale, 4+ years hands-on experience with TensorFlow or PyTorch

🪄 Skills: LeadershipData AnalysisMachine LearningPyTorchTensorflow

Requirements:

2+ years of management experience leading ML-focused teams.
6+ years of experience working with machine learning models at scale.
4+ years of hands-on experience with TensorFlow or PyTorch.
Proven ability in training, evaluating, and deploying large-scale models.
Experience with Ads or Engagement Modeling is a plus.

Responsibilities:

Define and execute a roadmap for engagement modeling.
Oversee the model development lifecycle from ideation to deployment.
Recruit, mentor, and retain top ML talent.
Collaborate with PMs, data scientists, and engineering teams.
Implement and optimize model architectures using advanced ML techniques.

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🔥 Machine Learning Manager - Ads Engagement Modeling

Posted 28 days ago

📍 United States, Canada

🧭 Full-Time

🔍 Technology, Machine Learning, Advertising

🏢 Company: Reddit👥 1001-5000💰 $410,000,000 Series F over 3 years ago🫂 Last layoff over 1 year agoNews Content Social Network Social Media

🔧 Requirements

2+ years of management experience leading ML-focused teams.
6+ years of experience working with machine learning models at scale.
4+ years of hands-on experience with TensorFlow or PyTorch.
Proven ability in training, evaluating, and deploying large-scale models.
Experience with Ads or Engagement Modeling is a plus, with a focus on media interactions.

💡 Responsibilities

Define and execute a roadmap for engagement modeling, balancing innovative modeling approaches with business objectives.
Oversee the model development lifecycle from ideation to deployment, ensuring high standards of ML performance and robustness.
Recruit, mentor, and retain top ML talent, fostering a culture of growth, collaboration, and technical excellence.
Partner with PMs, data scientists, and other engineering teams to align on engagement strategies, data requirements, and model KPIs.
Implement and optimize model architectures tailored to engagement prediction, leveraging deep learning and advanced ML techniques.

Machine LearningPyTorchData scienceTensorflow

Posted 28 days ago

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