Machine Learning Scientist developing innovative machine learning solutions, mentoring junior team members at Amii in Edmonton. Leading applied ML projects and supporting clients in AI adoption.
Responsibilities
Work with Amii clients to advance their ML projects and capabilities
Serve as a subject matter expert to guide and support organizational initiatives
Support the advancement of ML research and development in both industry and academia
Mentor junior team members to help them achieve their goals and advance their professional growth
Leads regular client meetings to understand their machine learning objectives and provides tailored technical guidance to support project development
Bridges the gap between fundamental ML techniques and business applications, providing scientific insight into technical projects and leading the technical and scientific direction
Supports the implementation of exploratory data analysis and machine learning modelling techniques
Conducts client discovery sessions to understand and evaluate potential projects and to determine specific needs and requirements
Coaches clients to efficiently extract insights and make informed decisions
Writes and reviews technical reports and code
Develops and nurtures strong relationships with clients through effective communication and scientific excellence
Incorporates client feedback to enhance delivery and ensure client success
Establishes themselves firmly as a trusted subject matter expert in reinforcement learning as well as potential other domains
Coaches junior staff through the model-building process, providing expertise and support
Mentors junior team members on career development and progression, drawing lessons for coaching opportunities
Encourages a collaborative work environment by facilitating teamwork and the exchange of ideas among team members
Identifies and addresses knowledge gaps, providing solutions or resources to bridge them
Ensures the Principled AI Framework is integrated into all projects, promoting ethical AI development and usage
Translates academic research into practical applications, applied research and industry solutions
Conducts research in leading-edge methods in various AI domains, such as reinforcement learning (RL), computer vision (CV), natural language processing (NLP) and large language models (LLMs)
Transfers knowledge across domains and industries, building a strong technical repertoire to bring to new problems
Prepares manuscripts for publication in peer-reviewed journals
Supports fundamental research in AI through applied research projects and the development of research topics
Provides supervision to junior team members by overseeing and refining their work, and managing approval processes
Mentors direct reports on career development and progression, drawing lessons for coaching opportunities
Fosters a collaborative work environment by facilitating teamwork and the exchange of ideas among team members
Encourages and maintains a problem-solving approach to work while acting as a coach and collaborator
Identifies and addresses knowledge gaps, providing solutions or resources to bridge them
Functions as a point of escalation for addressing challenges and facilitating the resolution of problems
Requirements
Masters or PhD in Computer Science with a specialization in Machine Learning or related scientific field with relevant applied experience in Machine Learning
2+ years experience developing, training, and evaluating machine learning models in an industrial setting
Experience and expertise with Reinforcement Learning as demonstrated with academic projects and/or industrial application
1+ years experience in a leadership capacity in industry or academic setting (nice to have)
Proficient in Python, experience in other programming languages i.e. Java or SQL (nice to have)
Proficient with machine learning tools and frameworks such as Scikit-learn, Pytorch/Tensorflow, Pandas, Optuna, Wandb, lightgbm/XGBoost, and SciPy
Publication record in peer-reviewed academic conferences or relevant journals
Ability to explain complex technical concepts clearly to non-technical audiences
Thorough understanding of the strengths and weaknesses of a range of ML techniques across supervised learning, unsupervised learning, and reinforcement learning
Experience leveraging cloud based tools for ML model building and deployment
Benefits
Competitive compensation, including paid time off and flexible health benefits
Participate in professional development activities
Gain access to the Amii community and events
A professional yet casual work environment that encourages the growth and development of your skills
A chance to learn from amazing teammates who support one another to succeed
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