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Machine Learning Engineering Manager- Ads Engagement Modeling
Rol remoto de Ads Engineering con fit claro de ubicación del candidato.
PublicadoAgregado recientemente
Países elegibles1 país aceptado
Señal de seniorityLead
Modelo de trabajoRemoto
Ubicaciones aceptadas para candidatos
Estados Unidos
Resumen del rol
Machine Learning Engineering Manager- Ads Engagement Modeling
Requisitos y responsabilidades
Contenido del rol extraído en secciones para revisar más rápido.
Details
- Set Technical Vision and Strategy: Define and execute a roadmap for engagement modeling, balancing innovative modeling approaches with business objectives.
- Drive Technical Execution: Oversee the model development lifecycle from ideation to deployment, ensuring high standards of ML performance and robustness.
- Lead and Mentor a High-Performing Team: Recruit, mentor, and retain top ML talent, fostering a culture of growth, collaboration, and technical excellence.
- Collaborate Cross-Functionally: Partner with PMs, data scientists, and other engineering teams to align on engagement strategies, data requirements, and model KPIs.
- Innovate in ML Architecture: Implement and optimize model architectures tailored to engagement prediction, leveraging deep learning and advanced ML techniques.
- People Management Experience: Prior experience managing engineering teams with a strong emphasis on technical mentorship and team growth.
- Set Technical Vision and Strategy: Ability to plan and execute a long-term technical strategy aligned with business objectives. Define and execute a roadmap for conversion modeling, balancing innovative modeling approaches with business objectives.
- Drive Technical Execution: Oversee the model development lifecycle from ideation to deployment, ensuring high standards of ML performance and robustness.
- Lead and Mentor a High-Performing Team: Recruit, mentor, and retain top ML talent, fostering a culture of growth, collaboration, and technical excellence.
- Collaborate Cross-Functionally: Partner with PMs, data scientists, and other engineering teams to align on engagement strategies, data requirements, and model KPIs.
- Innovate in ML Architecture: Implement and optimize model architectures tailored to conversion prediction, leveraging deep learning and advanced ML techniques.
- At least 2+ of experience building and managing high-performing machine learning teams, ideally in the Ads domain. Will consider tech lead experience as well
- Deep ML Expertise: Deep hands-on experience working with machine learning models and deploying them in large-scale production systems. Proven ability in training, evaluating, and deploying large-scale models.
- End-to-End ML Lifecycle Experience: Proven ability in training, evaluating, and deploying large-scale models.
- 4+ years of hands-on experience with TensorFlow or PyTorch.
- Strategic Thinking: Ability to develop and communicate a clear, compelling technical strategy that supports broader company objectives and addresses the needs of internal customers.
- Impact-Driven Mindset: Passion for developing scalable, well-designed, and responsible AI solutions that drive business value.
- Exceptional Communication & Collaboration: Strong interpersonal skills and a collaborative mindset, with the ability to effectively communicate complex technical topics to diverse audiences and build strong relationships with cross-functional partners
- Experience with Ads or Engagement Modeling is a plus.
- 100% remote opportunity (we have 4 office locations for hybrid/onsite work preference in NY, SF, LA and Chicago)
- Competitive salary and equity options
- Comprehensive health benefits (medical, dental, vision) & workplace perks (home office set up stipend etc)
- Generous 401k matching
- Flexible vacation policy
- Paid parental leave (4+ months)
- Family planning support
- Paid volunteer time off
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Flujo de contratación
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