Machine Learning Engineer, Sequence Models (project Sequoia)

What you'll do

• Build and scale infrastructure for data processing, distributed training, and model serving; optimize GPU use, throughput, latency, and infrastructure costs.
• Own training data pipelines, including ingestion, schema evolution, backfills, and data-quality checks.
• Establish repeatable training, validation, and deployment processes, and maintain operational excellence for production systems.

What they ask for

• 3+ years of non-internship professional software development experience.
• 1+ years designing and developing large-scale software applications, tools, systems, or services using C#, C++, Java, or Perl.
• Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, or a related field.
• Experience with ML and LLM fundamentals and deploying LLMs in production on GPUs, Neuron, TPU, or other AI acceleration hardware.

Nice to have

• 3+ years of full software development life cycle experience.
• Experience debugging and profiling large-scale systems and applying software engineering best practices.

Pay

158,100.00 - 213,800.00 USD annually (base salary)

Tools

C#, C++, Java, Perl, GPUs, Neuron, TPU

AI focus

Build infrastructure and production systems for sequence models, including Generative AI and LLMs; support model training, inference, optimization, and deployment.