About the position
VERSES is a cognitive computing company building next-generation intelligent software systems modeled after the Wisdom and Genius of Nature. We are a distributed, diverse, and inclusive workforce that aspires to do our best work on important problems with exceptional people. We’re looking for trailblazers and problem solvers passionate about tackling important global-scale challenges so if that sounds appealing, let’s imagine a smarter world together. At VERSES, we're shaping the future of computing with our natural computing platform, Genius. We're looking for a Staff Software Engineer (ML focused) to our product team and make a direct impact on the development of our agentic enterprise solution.
Responsibilities
- Migrate research concepts and ideologies (ie Active Inference) into production software
- Contribute to the design and development of robust, scalable, ML infrastructure with emphasis on Bayesian inference and uncertainty quantification
- Implement active inference agents and models to support adaptive, goal-directed behavior in dynamic environments
- Optimize end-to-end ML pipelines from data ingestion and preprocessing to deployment and monitoring
- Ensure observability, reproducibility, and reliability of models throughout the development lifecycle
- Rapidly prototype systems for live demonstration, applying cutting-edge technologies to connect the physical and digital worlds
- Collaborate with cross-functional teams, including data scientists, researchers, designers, and other engineers, to define software requirements and integrate probabilistic models into production systems
- Actively participate in technical discussions, offer mentorship, and ensure adherence to coding standards and best practices through active participation in code reviews
- Work in a small and tight-knit agile innovation unit running ahead of the main product team
- Develop technical documentation and participate in knowledge sharing sessions
Requirements
- At least 10 years of experience in software engineering, including 3+ years in ML-focused roles
- Strong expertise in probabilistic modeling and Bayesian inference, including a solid understanding of variational inference
- Experience designing ML pipelines using tools like Airflow, Kubeflow, or MLflow
- Fluency in Python and experience with deep learning frameworks (e.g. PyTorch, TensorFlow, JAX)
- Experience with agile software development methodologies
- Bachelor's degree in Computer Science or a related field or equivalent years of work experience
- Experience with reinforcement learning or control theory frameworks
- Experience with core machine learning and AI concepts, including generative models (like GPTs), and an awareness of emerging paradigms such as active inference
- Track record of deploying ML models in high-availability systems (real-time inference, edge computing)
- Experience with probabilistic programming frameworks to solve real world inference and decision making problems
Nice-to-haves
- Excellent problem-solving and analytical skills
- Strong written and verbal communication skills
- A passion and spirit of innovation
Benefits
- Global virtual work environment (although some positions may need to operate within specific time zones)
- Responsible paid time off policy (RTO), and company-recognized Holidays
- Generous total rewards package
