Machine Learning Researcher - Probabilistic Programming

Machine Learning Researcher

100% Remote - US & Canada

About Us

VERSES is a cognitive computing company building next-generation intelligent software systems. Our flagship product, Genius™ is 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 and we value: AUDACITY, ASSERTIVENESS, ALIGNMENT, ACCOUNTABILITY, ABUNDANCE & AWESOMENESS.

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!

Make An Impact

VERSES AI seeks to engage a machine learning researcher with strong knowledge of probabilistic programming frameworks (e.g. NumPyro), SVI, and variational inference algorithms.

Specifically, we are looking for a researcher who will be responsible for developing and implementing machine learning algorithms and solutions based upon variational Bayesian methods, with broad applications including physics discovery, reinforcement learning, and structured knowledge representation. We seek a candidate with a track record of innovative research, able to develop and test probabilistic programming frameworks, and with a strong knowledge of neural network frameworks such as TensorFlow, Keras, and PyTorch, and Jax.

This unique position combines the benefits of working within an academic research driven environment, and you will be encouraged to collaborate widely and publish, with the benefits of the commercial sector including compute resources, appropriate remuneration and the ability to pursue the commercial impact of scientific innovations. You will join a team of talented researchers & engineers who work collaboratively with developers, system engineers, quality engineers, product managers, and usability experts to make our products easier to use.

Essential Functions- a/k/a/ Your Mission

• Pursuing cutting edge ML research both independently and as part of a team
• Developing ML theory and algorithms at scale and publishing academic papers
• Research focus on: develop and test probabilistic programming frameworks, ML benchmarking, ML scaling, structure learning, graph neural networks, message passing on factor graphs
• Distilling and presenting your work to our company leaders on a regular basis
• This individual may work with others in the scientific or research community to assist them in their research.This role contributes to specific lines of development and innovation work, to help others who are accountable for product development to implement and operationalize research results

Requirements

• Strong background in Computer Science, Machine Learning, Bayesian Methods, Reinforcement Learning, and Dynamical Systems analysis and simulation
• Proficient in programming in Python
• Experience with pattern recognition and time series analysis
• Knowledge of Variational inference algorithms, SVI, and probabilistic programming frameworks
• Knowledge of neural network frameworks such as TensorFlow, Keras, and PyTorch
• Mastery of model evaluation and optimization techniques
• Strong analytical and problem-solving skills
• Excellent written and verbal communication skills
• Ability to work independently and in a team environment
• Ph.D. in Computer Science, Physics, Mathematics, Statistics or related field

Great to Haves

• Experience with active inference and the free energy principle
• Experience in distributed ML
• Extensive knowledge of Bayesian approaches in machine learning
• Demonstrated track record at publishing in top echelon ML venues such as NeuIPS, ICML, ICLR, CVPR, etc on topics such Deep Learning, Reinforcement Learning, ML Theory & Foundations Unsupervised Learning & Generative Models

Benefits

• In addition to fostering a culture of highly engaged, emotionally intelligent, and energetic people we offer:
• Global virtual work environment (although some positions may need to operate within specific time zones)
• 100% Company paid medical, dental & vision benefits
• Financial and Mental Health wellness programs
• Responsible paid time off policy (RTO), sick time complying with all State and Federal guidelines, and of course... Company recognized Holidays!!
• Vested interest in the success of individuals
• Generous total rewards package which includes equitable base pay, potential for bonuses, stock options

Job Type

Regular, Full-time

Remote Position: US or Canada

Commitment to Diversity, Equity, Inclusion, and Belonging:

At VERSES, we value diverse creative practices and forms of knowledge. We encourage applications from everyone, including members of all equity-seeking communities, such as (but certainly not limited to) women, racialized and Indigenous persons, persons with disabilities, persons of all sexual orientations, gender identities, and expressions.

We will ensure that qualified individuals with disabilities are provided reasonable accommodations to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment, as appropriate. Please contact us at [email protected] to request accommodation.

We are an equal opportunity employer. We do not discriminate on the basis of race (including hairstyle and texture), religion (including religious grooming and dress practices), gender, gender identity, gender expression, color, national origin, pregnancy, ancestry, domestic partner status, disability, sexual orientation, age, genetic predisposition, medical condition, marital status, citizenship status, military or veteran status, or any other basis covered by applicable laws. VERSES will not tolerate discrimination or harassment based on any of these characteristics or any other unlawful behavior, conduct, or purpose.

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.