Machine Learning Engineer

Coframe•Burlingame, CA

1d•Onsite

About The Position

As a Machine Learning Engineer at Coframe, you’ll build the models that power performance optimization. You’ll train foundation models and customer-specific models to predict and improve user engagement, clicks, and conversions, and own each model’s lifecycle from research and training through deployment infrastructure. You’ll develop and scale machine learning infrastructure for training, serving, and monitoring models in production. The role includes building evaluation systems that connect model performance to customer outcomes, creating feedback loops from real-world experiment results, and collaborating with technical and non-technical teams to turn customer goals into models, metrics, and product improvements. Coframe is a rapidly growing, well-funded company based primarily in San Francisco. Its small team includes AI researchers and former founders, and the company works with OpenAI to co-train a model for its use case. Coframe is an Equal Opportunity Employer.

Requirements

Experience fine-tuning vision-language models (VLMs) or large language models (LLMs).
Experience training ranking, click-through rate (CTR), conversion, or engagement models.
Strong machine learning infrastructure experience, including training pipelines, data systems, and model serving.
Ability to own models end to end, from research and experimentation to production deployment.
Strong software engineering fundamentals and experience shipping reliable production systems.
Ability to translate business metrics into modeling objectives and rigorous evaluations.
Curiosity, pragmatism, and excitement about working on problems with no established playbook.
A track record of exceptional achievement in industry, research, or academics.

Nice To Haves

Experience building agent loops.
Experience with edge or low-latency model serving.
Experience working with e-commerce, growth, or experimentation teams.

Responsibilities

Build foundation models and customer-specific models for performance optimization.
Fine-tune vision-language models and large language models to understand and improve digital experiences.
Train ranking, click-through rate, conversion, and engagement models that guide what Coframe generates and ships.
Own the full model lifecycle, from idea and research through training, evaluation, and deployment.
Build and scale machine learning infrastructure for training, serving, and monitoring models in production.
Develop online and offline evaluation systems that connect model performance to real customer outcomes.
Build feedback loops so models can improve continuously using real-world experiment results.
Work with technical and non-technical teams to translate customer goals into models, metrics, and product improvements.