Machine Learning Engineer II

Company Overview:

At AppLovin, we’re at the forefront of the advertising technology industry. Our cutting-edge platform connects businesses with their potential customers using advanced machine learning technologies. With state-of-the-art ML infrastructure and models, our system rivals those of industry giants. We take pride in providing top-of-the-line compensation packages in the industry and are actively seeking extraordinary machine learning engineers to join our exceptional team.

Position Overview:

We are looking for a Machine Learning Engineer with a specialization in ML infrastructure and deep learning architecture. In this role, you will play a pivotal part in developing cutting-edge deep learning architectures and advancing our ML infrastructure. If you’re passionate about pushing the boundaries of machine learning technology, building multi-billion dollar businesses with advanced algorithms, and are excited to work in a dynamic, innovative environment, this is the opportunity you’ve been waiting for.

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.

Qualifications:

• Master’s or Ph.D. in Computer Science, Machine Learning, or a related field.
• Experience 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.

What We Offer:

• Competitive compensation package, including top-tier salaries in the industry
• Free medical, dental, and vision insurance
• 401k matching and employee stock purchase plan
• A dynamic and inclusive work environment that encourages creativity and innovation.
• Opportunities for career growth and professional development.
• Access to cutting-edge technology and resources.
• A chance to make a significant impact on the advertising technology landscape.

Join us in pushing the boundaries of machine learning technology and be a part of our mission to connect businesses with their potential customers through advanced ML solutions. If you’re an extraordinary ML engineer looking to contribute to a dynamic, high-impact team, we want to hear from you.

The expected base pay range for this CA based position is $134,000 - $207,000. Total compensation at AppLovin is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Depending on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical and other benefits.

We use Covey as part of our hiring and / or promotional process for jobs in NYC and certain features may qualify it as an AEDT. As part of the evaluation process we provide Covey with job requirements and candidate submitted applications. We began using Covey Scout for Inbound on March 12, 2024.

Please see the independent bias audit report covering our use of Covey here.