Senior Machine Learning Engineer, Digital Intelligence

What you'll do

• Research and prototype next-generation architectures for structured and unstructured data.
• Develop novel pre-training objectives tailored to financial event sequences and heterogeneous profile data.
• Implement research ideas into production-quality code.
• Optimize training throughput for large data sources using distributed training frameworks.
• Mentor engineers on ML best practices and translate research advances into deployable systems.
• Monitor models in production to reduce agent effort and shorten resolution times.
• Design and implement solutions for specific product use cases in collaboration with other teams.

What we're looking for

• PhD with or Master’s degree with in Computer Science with training and work experience in Machine Learning, LLM/NLP, or similar fields.
• Deep LLM and Transformer expertise including attention mechanisms, positional encodings like RoPE, and multi-modal data inputs.
• PyTorch proficiency at scale with hands-on experience in distributed training frameworks like FSDP and DeepSpeed.
• Proven experience in foundation model pre-training from scratch and designing tokens/vocabularies for complex, heterogeneous data sources.
• Strong software engineering skills to build robust, production-quality systems that perform reliably at scale.
• Prior experience with financial data and recommendation systems.
• Publication record at top AI/ML venues (preferred).
• Experience optimizing serving infrastructure, post-training LLMs, network optimization, interpretability, or steering techniques (preferred).