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AI Applied Scientist

Verily
Waterloo, ON

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Détails du poste

Temps plein

Compétences

TensorFlow
Génie logiciel
Droit
Informatique
PyTorch
Apprentissage profond
Traitement du langage naturel
Analytique des données
Développement logiciel
Science des données
Intelligence artificielle
Collaboration interfonctionnelle
Communication interfonctionnelle

Description complète du poste

Who We Are

Verily Health is a data platform and technology company purpose-built to power AI-enabled precision health solutions that accelerate research and improve care for individuals and communities. Uniquely positioned at the intersection of technology, data science, and healthcare, Verily transforms multimodal health data into insights, models, and actions that make healthcare more personalized, predictive, and precise.

Description

As an AI and Data Scientist at Verily, you will be supporting our core mission to build advanced data and AI capabilities for Verily's portfolio of products. You will help drive innovation in data-driven healthcare applications by developing and deploying sophisticated models. Your work will involve utilizing cutting-edge techniques to analyze complex datasets, uncover patterns, and build robust, data-driven solutions that address healthcare challenges. You will collaborate with a diverse cross-functional team to build reusable and scalable tools that unlock information from structured and unstructured clinical data.

Responsibilities

Dive into complex data science projects, identifying opportunities to leverage data for groundbreaking healthcare solutions.
Collaborate with a diverse team of experts to conceptualize, develop, and implement AI solutions tailored to a variety of healthcare applications.
Apply cutting-edge machine learning algorithms, including Large Language Models (LLMs) and Natural Language Processing (NLP), to unlock insights from large, unstructured medical datasets and inform strategic decisions.
Build robust, data-driven solutions that translate complex analysis into practical applications, tackling significant healthcare challenges head-on.
Design and build scalable data pipelines that ensure data quality and accessibility, contributing to Verily's core data infrastructure.

Qualifications

Minimum Qualifications

Advanced degree in a quantitative discipline (e.g., computer science, statistics, applied mathematics, biomedical informatics, biomedical engineering) or equivalent practical experience.
2+ years of experience applying advanced machine learning and AI techniques (e.g., supervised and unsupervised methods, LLMs, NLP) to clinical data.
Direct experience working with Large Language Models (LLMs) and familiarity with prompt optimization technologies.
Strong proficiency in Python.

Preferred Qualifications

Experience with LLM models, including prompting, fine-tuning, and retrieval-augmented generation (RAG).
Familiarity with software engineering principles and experience deploying algorithms in production environments.
Experience developing transformer-based deep learning algorithms using TensorFlow or PyTorch.
Experience working with clinical subject matter experts and cross-functional teams.
Ability to work cross-functionally and lead projects, with a tolerance for ambiguity.

This role is eligible for Verily-sponsored immigration support.

Compensation Information

The Canada base salary range for this full-time position is CAD 139,000 - 156,500 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training.

Verily is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status. For our EEO Policy Statement, please click here.

If you have a need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

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