Genius

Benefits:

• Global virtual work environment

• Responsible paid time off policy (RTO)

• Company-recognized Holidays

• Generous total rewards package

Education Requirements:

• Master’s degree or higher in Computer Science, Engineering, AI, or related fields.

Experience Requirements:

• A minimum of 2-3 years of experience developing and deploying machine learning models

• Proven proficiency in multi-agent reinforcement learning, decentralized AI, and smart city infrastructure modeling.

Other Requirements:

• Familiarity with probabilistic programming, Active inference bonus

• Familiarity with CityLearn framework or similar AI-driven sustainability tools.

• Strong software engineering skills, including experience with Python, ML deployment, and scalable systems.

• VERSES is unable to offer visa sponsorship or assistance with work authorization for this position. Only candidates authorized to work in the United States and Canada without the need for sponsorship will be considered.

• VERSES currently does not accept agency resumes. Please do not forward resumes to our careers email or to VERSES employees. VERSES is not responsible for any fees or overhead related to unsolicited resumes. No agencies, please.

Responsibilities:

• Develop, deploy, and scale multi-agent reinforcement learning models within decentralized AI systems for sustainable urban solutions (EcoNet).

• Integrate CityLearn framework and other smart city modeling tools to enhance adaptive, resilient urban infrastructure systems.

• Collaborate closely with research and product teams to transition research models into production-ready systems.

• Continuously refine system dynamics and decentralized AI system capabilities.

Benefits:

• Global virtual work environment

• Responsible paid time off policy (RTO)

• Company-recognized Holidays

• Generous total rewards package

Education Requirements:

• Bachelor's degree in Computer Science or a related field or equivalent years of work experience

Experience Requirements:

• At least 10 years of experience in software engineering, with a focus on developing solutions for, and supporting, enterprise-scale applications.

• Proficiency in at least one “server-side” programming language, such as Python, Rust, or Node.js

• Experience with cloud technologies (AWS, Azure, GCP), containerization (Docker, Kubernetes), and databases (MySQL, PostgreSQL, MongoDB) Experience with pub sub technologies such as RabbitMQ, Kafka, and Reddis.

• Strong understanding of web technologies and standards, such as REST/CRUD, HTTP, DNS and web security

• Experience with DevOps and security practices

Other Requirements:

• Experience with API design and development

• Experience working with IoT and edge computing technologies

• Experience with agile software development methodologies

• Understanding of core machine learning and AI concepts, including generative models (like GPTs), and an awareness of emerging paradigms such as active inference

• VERSES is unable to offer visa sponsorship or assistance with work authorization for this position. Only candidates authorized to work in the United States without the need for sponsorship will be considered.

• VERSES currently does not accept agency resumes. Please do not forward resumes to our careers email or to VERSES employees. VERSES is not responsible for any fees or overhead related to unsolicited resumes. No agencies, please.

Responsibilities:

• Migrating research concepts and ideologies (ie Active Inference) into production software

• Evolve our agentic platform promoting scalability and maintainability furthering the state of the art

• Rapidly prototype systems for live demonstration, applying cutting-edge technologies to connect the physical and digital worlds

• Work closely with partners to develop and implement solutions as they onboard to the Genius Platform, ensuring a seamless integration and adoption process.

• Collaborate with cross-functional teams, including researchers, designers, and other engineers, to define software requirements and guarantee successful implementation.