Senior Machine Learning Engineer

Overview

Senior Machine Learning Engineer on Roku's Ad Engineering team, building ML models for content understanding of ads across visual, audio and textual content in multiple languages.

What you'll do

• Develop scalable and effective machine-learning models and optimization strategies to solve business problems related to Ads
• Run regular A/B experiments, gather data, and perform statistical analysis
• Work closely with software engineers and other ML engineers to deliver end-to-end solutions into production
• Improve the scalability, efficiency and automation of ML driven ad serving systems, model training, deployment and serving
• Partner with senior stakeholders to plan and drive the ML strategy for Ad Serving
• Build and develop ML models to solve for content understanding aspects of Ads, using deep learning, generative AI, large language models (LLMs) and vision language models (VLMs) to support brand safety, revenue opportunities, and moderation and generation of ad creatives

What you'll need

• 6+ years of building models for business application experience
• Master's degree (or higher) and 4+ years of CS, CE, ML or related field experience
• Strong CS fundamentals; should be able to write an algorithm with ease
• Experience developing and implementing deep learning algorithms, particularly with respect to computer vision algorithms
• Good understanding of data science and machine learning fundamentals like regression, classification, tree-based approach, neural networks, sequence-based, and NLP approaches like W2V or Bert
• Can brainstorm and identify the right KPIs and objective functions
• Knowledge of programming languages such as C/C++, Python, Java or Perl
• AI growth mindset / AI Literacy

Nice to have

• Knowledge of programming languages such as C/C++, Python, Java or Perl
• Publications at top-tier peer-reviewed conferences or journals

Details

• Location: Bengaluru, India (Ad Serving team based in Bangalore)
• Hybrid working: teams generally work in the office Monday through Thursday; Fridays are generally flexible for remote work, except for roles or office locations requiring five days a week attendance