Applied ML Research Engineer

Summary

Join VERSES, a cognitive computing company, as an Applied ML Research Engineer and contribute to building next-generation intelligent software systems. Based primarily in the Applied Research group, you will also contribute to the Foundations of ML group. Your focus will be on using Bayesian statistics inspired by the free energy principle and active inference to create scalable and practical solutions. You will contribute to development and innovation, apply Bayesian techniques to real-world problems, contribute to ML theory and publish papers, and present your work to company leaders. This role requires a Master's degree or PhD in a quantitative field with experience in relevant areas. VERSES offers a global virtual work environment, mental health wellness programs, a responsible paid time off policy, and a generous total rewards package.

Requirements

• Have Master's degree or a PhD in a quantitative field, with experience in computer science, data science, statistics and operations research
• Demonstrated track record in applying Bayesian techniques and engaging in ML research
• Understanding of cutting edge of machine learning research
• Ability to work within a team of both ML research scientists and engineers

Responsibilities

• Contribute to specific lines of development and innovation work, to help others who are accountable for product development to implement and operationalize research results
• Apply Bayesian techniques to real-world problems
• Contribute to developing ML theory, and publish papers
• Review, comment, analyze and re-use Company source materials including research, patents, white papers, presentations, illustrations, and reference examples
• Distill and present your work to company leaders on a regular basis

Preferred Qualifications

• Experience with active inference and the free energy principle are a plus
• You will have a background from academia, industry experience or a combination of both
• Have knowledge of implementing AI systems at scale
• Knowledge of deploying ML services on the cloud, working with big data

Benefits

• Global virtual work environment (although some positions may need to operate within specific time zones)
• Mental Health wellness programs
• Responsible paid time off policy (RTO), and company-recognized Holidays
• Generous total rewards package