Machine Learning Engineer

Must have

Strong background in applied machine learning and/or reinforcement learning, with hands-on experience training, evaluating, and optimizing models.

Proven experience building or scaling ML systems (pre-training, post-training, inference)

Comfortable working in an experimental environment, with extremely high autonomy and unpredictable timelines

Impeccable analytical and problem-solving skills

Strong software engineering fundamentals: data structures, algorithms, and system architecture.

Fully remote work

- we currently hire between the West Coast (PT) and Central Europe (CET) time zones

Machine Learning Engineers at Gensyn design and build advanced ML systems that bridge cutting-edge research and real-world deployment.

This role spans proof-of-concept research, high-performance ML optimization, peer-to-peer reinforcement learning, and the development of high-scale fault-tolerant distributed training pipelines. You’ll collaborate closely with researchers, systems engineers, fullstack software engineers, and product teams to take ideas from prototype to production.

Build scalable, distributed ML compute systems that operate efficiently over uniquely decentralised and heterogeneous infrastructure

Develop and optimize reinforcement learning and applied ML pipelines, improving performance, reliability, and reproducibility.

Collaborate with both researchers and production engineers to design and run novel experiments, taking research from theory to production.

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