Senior ML Engineer

Role overview Lead the engineering of machine learning systems and pipelines for an AI-enabled project management product. This senior role spans model development, production deployment and the infrastructure needed to operate models reliably at scale. It also includes technical leadership, mentoring and translating product needs into practical ML solutions.

Responsibilities - Design and build machine learning systems, pipelines and scalable workflows. - Develop, deploy and maintain production-grade models. - Research and apply current machine learning methods to product needs. - Improve model performance, latency and resource use, including through distributed training and optimization. - Establish practices for model versioning, monitoring and MLOps. - Mentor machine learning engineers and data scientists, and work with product teams to shape solutions.

Requirements - At least seven years of machine learning engineering experience. - A master’s or doctoral degree in computer science, machine learning or a related field. - Expert knowledge of PyTorch or TensorFlow and strong Python and software engineering skills. - Significant experience with NLP, transformers and large language models. - Evidence of deploying machine learning models to production at scale. - Expertise in MLOps, model monitoring and versioning; experience with distributed training and model optimization.

Benefits and work setup - Remote work options and a competitive senior-level salary and equity package. - Health insurance, wellness benefits and a professional development budget. - Leadership and growth opportunities, access to advanced AI infrastructure, and support for conference speaking and publications.