Position Type: Full-Time, Permanent

Department: Toronto AI Lab

Work Location: Toronto, ON

Work Arrangement: Hybrid: 3 Days per Week On-Site

POSITION SUMMARY:

Toronto's AI Lab is seeking an Agentic AI Researcher to help shape the next generation of LG Electronics' products by advancing research in agentic AI systems and applying those capabilities across LG's global product portfolio.

In this role, you will contribute to the development of self-learning, autonomous, and personalized AI agents that are embedded directly into LG products, including smart home platforms, connected appliances, and future intelligent devices. Your research will help enable products that can reason, adapt, remember, and proactively assist users over long periods of time.

Working closely with senior and lead researchers, engineers, and product teams, you will apply agentic AI concepts-such as lifelong learning, hierarchical memory, and personalized inference-to real-world use cases at scale. Research outcomes will be transitioned into prototypes and, over time, into production systems deployed across millions of consumer and enterprise products worldwide.

This role offers a unique opportunity to bridge cutting-edge AI research with tangible product impact, helping define how autonomous and agent-based AI becomes a core intelligence layer across LG's future smart home ecosystem and beyond.

PRINCIPAL RESPONSIBILITIES:

• Conduct research on continual learning agents, including skill libraries/tools and curriculum or goal discovery, under the guidance of senior researchers.
• Contribute in a fast-paced, technically challenging environment by proposing and testing innovative ideas and solutions.
• Design and experiment with self-learning agent systems for lifelong skill acquisition and evolution, including reward functions for task completion quality and long-horizon consistency.
• Research and implement techniques for personalized inference control, such as activation steering or persona vectors, with attention to user alignment and enterprise safety.
• Contribute to Agent-User-Memory frameworks, including memory agents, user modeling, and orchestration layers for personalization.
• Collaborate with academic and internal research partners; support paper writing and experimentation for top-tier conferences.
• Translate research ideas into working prototypes and proof-of-concepts.
• Implement and evaluate research baselines and metrics for long-context reasoning, planning, memory utility, and skill retention.
• Tune and optimize large multimodal models and assist in building evaluations to measure agent and model performance.

KNOWLEDGE, SKILLS, AND ABILITIES:

• Education & Experience
• PhD in Machine Learning, Artificial Intelligence, or related field (no post-graduate research experience required), OR
• Master's Degree in ML/AI with 3+ years of relevant post-graduate experience
• Technical Skills
• Strong foundational knowledge in machine learning, reinforcement learning, LLMs, memory-augmented models, or agentic AI systems
• Hands-on experience with PyTorch and/or JAX; familiarity with large-scale training or distributed systems is a plus
• Experience or coursework involving RL reward design, agent evaluation, or long-horizon reasoning tasks
• Ability to design experiments, analyze results, and iterate on models and agents
• Research & Collaboration
• Research experience demonstrated through academic projects, industry work, publications, or open-source contributions
• Interest in contributing to academic publications and collaborative research
• Strong written and verbal communication skills
• Eagerness to learn from senior researchers and grow toward technical leadership
• Personal Attributes
• Curious, self-motivated, and capable of working effectively in a collaborative research environment
• Demonstrated ability to apply creative problem-solving to real-world challenges

Note: This posting is for an existing vacancy. The expected base salary range for this position is $130k - $160k. Actual total compensation may include variable incentive pay. The determination of an applicant's base salary is based on the applicant's skills, competencies, location, and unique qualifications.

Artificial intelligence will be used in sourcing, reviewing and communicating with candidates for this position.

This job description is not intended to be all-inclusive. Employee may perform other related duties as negotiated to meet the ongoing needs of the organization.

The organization offers an attractive compensation package that encompasses a competitive salary and excellent benefits.

Conditions of Employment:

It is the candidate's sole responsibility to obtain any work permits/visas or other authorizations which may be required to legally work in Canada prior to commencing employment.