Senior Machine Learning Engineer
Updated on 4/13/2024
AppLovin

501-1,000 employees

AI-powered software for customer connection and business growth
Company Overview
AppLovin is a leading company in the tech industry, offering comprehensive software and AI solutions that enable businesses to effectively reach and expand their global audiences. The company's competitive edge lies in its advanced AI models, which continually train against billions of data points, ensuring their technology remains at the forefront of the industry. With a culture that emphasizes growth and connection, AppLovin offers a dynamic work environment, fostering both professional development and global impact.
Data & Analytics
AI & Machine Learning

Company Stage

N/A

Total Funding

$1.9B

Founded

2012

Headquarters

Palo Alto, California

Growth & Insights
Headcount

6 month growth

7%

1 year growth

8%

2 year growth

7%
Locations
Palo Alto, CA, USA
Experience Level
Entry
Junior
Mid
Senior
Expert
Desired Skills
Python
Tensorflow
Data Structures & Algorithms
Pytorch
CategoriesNew
AI & Machine Learning
Applied Machine Learning
Deep Learning
Requirements
  • Master’s or Ph.D. in Computer Science, Machine Learning, or a related field.
  • Proven experience in ML infrastructure design, optimization, and scalability.
  • Expertise in deep learning architectures and frameworks (e.g., PyTorch, TensorFlow).
  • Strong programming skills in Python and proficiency in relevant ML libraries.
  • Solid understanding of distributed computing, cloud platforms, and big data technologies.
  • Excellent problem-solving abilities and a track record of delivering innovative solutions.
  • Strong communication skills and the ability to work collaboratively in a team environment.
Responsibilities
  • Deep Learning Architectures: Design, develop, and implement deep learning architectures that drive innovation and improve the performance of our advertising technology. Stay up-to-date with the latest advancements in deep learning research and apply them to real-world applications.
  • Advance ML Infrastructure: Lead efforts to enhance and scale our ML infrastructure, ensuring its reliability, efficiency, and scalability. Collaborate with cross-functional teams to optimize data pipelines, model deployment, and monitoring systems.
  • Collaboration: Work closely with our talented team of machine learning engineers, data scientists, and software engineers to integrate your solutions into our platform seamlessly.
  • Performance Optimization: Continuously optimize machine learning models and algorithms to improve ad targeting, recommendation systems, and customer insights.
  • Research and Development: Stay at the forefront of machine learning research and apply innovative techniques to solve complex challenges in the advertising technology space.