ML Research Engineer

The Role

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.

Responsibilities

• 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.
• Prototype and evaluate new ML architectures, tools, and frameworks to accelerate experimentation and deployment.
• Apply strong software engineering discipline to ensure robustness, observability, and maintainability across ML codebases.

Competencies

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.

Preferred

• Experience building highly performant, distributed systems
• Demonstrated experience operationalizing novel ML research, bridging experimentation and production
• Familiarity with decentralized or heterogeneous compute environments and distributed orchestration at scale.
• Experience developing mission-critical, fault-tolerant ML infrastructure

Nice to have

• Experience working in a startup/scaleup environment
• Previous experience working with smart contracts