Senior Software Engineer (Machine Learning)

• In this role, you will build and develop ML models to solve for content understanding aspects of Ads
• These models rely on the visual, audio and textual content of ads, across multiple languages
• This includes developing computer vision and machine learning models/methods such as deep learning models, generative AI solutions, large language models (LLMs) and vision language models (VLMs)
• You will work with software engineers and other ML engineers to identify, build, train and productionize these models to improve brand safety, increase revenue opportunities and help with moderation and generation of ad creatives in general
• 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

Benefits

• Medical, wellness and financial benefits
• Free snacks and access to the company fitness center
• Unlimited paid time off policy
• Work from home opportunities- AI growth mindset
• Exceptional understanding of regression, classification, tree-based approach, neural networks, sequence-based, and NLP approaches like W2V or Bert
• Experience with SOTA technology/frameworks/Infra for Modeling
• Capacity to start off independently as the inaugural Ad Serving team hire in Cambridge
• Experience brainstorming and identifying the right KPIs and objective functions
• Experience in a tech lead role delivering large cross-functional projects
• PhD in a relevant filed (preferred)
• Worked at and contributed/led efforts at businesses where ML/Modeling is done at large scale/low latencies
• Publications at top-tier peer-reviewed conferences or journals (preferred)
• Experience developing and implementing deep learning algorithms, particularly with respect to computer vision
• Advertising or adjacent domain experience (preferred)