Research Scientist (Multimodal AI)

Location: On-site in Toronto GTA, New York, or San Francisco

Salary: $185,000–$210,000 per year, plus equity. Compensation is region-specific and may vary by hiring location.

Company

hirify.global builds data infrastructure for robotics and embodied AI, including data capture, data labeling, and hardware-enabled workflows for AI labs and robotics companies.

What you will do

• Research, develop, and improve vision-language models and multimodal foundation-model architectures.
• Design post-training strategies including supervised fine-tuning, preference optimization, and reinforcement learning.
• Improve model reasoning, generalization, reliability, and training efficiency.
• Develop data curation, filtering, and synthetic data generation strategies.
• Design evaluation frameworks and benchmarks to identify failure modes and guide research priorities.
• Run large-scale experiments using distributed training infrastructure and large datasets.

Requirements

• Hands-on experience researching, training, fine-tuning, or post-training large-scale foundation models, especially vision-language or multimodal models.
• Strong knowledge of deep learning architectures, optimization, and modern model training methods.
• Practical experience with supervised fine-tuning, preference optimization, or reinforcement learning approaches such as DPO, GRPO, PPO, or RLHF.
• Strong proficiency in Python and PyTorch, JAX, or comparable deep learning frameworks.
• Experience with large-scale machine learning experiments, distributed training systems, and GPU-based model development.
• Research publications, open-source contributions, or experience at leading AI research organizations.

Nice to have

• Experience with large-scale post-training and reinforcement learning for reasoning or alignment.
• Familiarity with multimodal data pipelines involving images, video, or other sensory inputs.
• Experience with reward modeling, synthetic data generation, or advanced model evaluation.
• Experience improving model capabilities through training, data, or model architecture innovations.

Culture & Benefits

• Inclusive and supportive candidate experience.
• Accommodation is available during the interview process upon request.
• Equal employment opportunity and a workplace free from discrimination, harassment, and retaliation.
• Equity and health and wellness benefits may be included in total rewards.

Hiring process

• AI tools may support administrative activities such as drafting interview questions, note-taking, recordings, sourcing, and scheduling.
• Candidate evaluations, interviews, and hiring decisions are made by members of the Mecka team.