Machine Learning Engineer

1 week ago

Vancouver, British Columbia, Canada T-Net British Columbia Full time
About the Role

We are seeking a highly skilled Machine Learning Engineer to join our team at T-Net British Columbia. As a Machine Learning Engineer, you will be responsible for designing, developing, and deploying innovative machine learning algorithms and models to solve complex problems in robotics and AI.

Key Responsibilities
  • Collaborate with cross-functional teams to identify opportunities for applying machine learning techniques to solve complex problems in robotics and AI.
  • Design, develop, and deploy machine learning models and algorithms to address specific business needs and challenges in robotics and AI.
  • Implement scalable and efficient software solutions to integrate machine learning models into production systems.
  • Optimize and fine-tune machine learning algorithms for improved performance and accuracy.
  • Conduct thorough testing and validation of machine learning models to ensure robustness and reliability.
  • Stay updated on the latest developments and advancements in machine learning and communicate promising research directions to the team.
  • Provide technical guidance and mentorship to junior team members.
Requirements
  • Master's degree or Ph.D. in Computer Science, Engineering, Mathematics, or a related field.
  • 3+ years of demonstrated experience in a wide variety of ML methods with a focus on a specialization such as dexterous manipulation with reinforcement learning or imitation learning, computer vision for robotics, or natural language processing.
  • 4+ years of experience in software engineering, with a focus on developing and deploying production-grade applications.
  • Working experience with ROS2.
  • Development experience with parallel computing such as CUDA, OpenMP, SSE, etc.
  • Experience with Atlassian tools; Jira, GitLab, Confluence.
  • Experience taking ML models to production.
  • Hands-on experience with popular machine learning frameworks and libraries such as TensorFlow, PyTorch, scikit-learn, etc.
  • Experience with cloud platforms (e.g. AWS, Azure, GCP) and distributed computing frameworks (e.g., Spark) is a plus.
  • Familiarity with robotics principles and technologies is highly desirable.
  • Publications in leading AI, ML or robotics conferences.
Preferred Skills
  • Strong proficiency in programming languages such as Python or C++.
  • Extensive knowledge of machine learning techniques and algorithms, including but not limited to supervised and unsupervised learning, deep learning, reinforcement learning, and natural language processing.
  • Working knowledge of PyTorch and/or TensorFlow.
  • Excellent problem-solving skills and the ability to work effectively in a fast-paced, collaborative environment.
  • Strong communication skills and the ability to convey complex technical concepts to non-technical stakeholders.
  • Above all else, a consistently positive attitude and a willingness to do whatever it takes to create robust solutions to complex problems.
  • Optimistic listening and conflict resolution capabilities.
  • Demonstrated ability to influence others without authority.
  • Eager to take on new challenges with tenacity and positivity.
  • Patience, persistence, and attention to detail when resolving performance issues.
  • Obsession with bringing human-like intelligence to machines.
About T-Net British Columbia

T-Net British Columbia is an equal opportunity employer; employment with T-Net British Columbia is governed based on skills, competence, and qualifications and will not be influenced in any way by race, color, religion, gender, national origin/ethnicity, veteran status, disability status, age, sexual orientation, gender identity, marital status, mental or physical disability, or any other legally protected status.

Full-time (non co-op) employees enjoy medical/dental/vision coverage, life insurance, wellness programs, stock options, paid time off (3 weeks vacation accrued annually, paid statutory holidays, paid statutory sick leave, and statutory parental leave), scheduling and worksite flexibility by role, and more.

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