Review and optimize code for AI applications deployed on Google Cloud Platform
Provide architectural and technical guidance for enterprise-scale AI solutions
Design and implement strategies for scaling LLMs in production environments
Apply prompt engineering, reinforcement learning from human feedback (RLHF), and retrieval-augmented generation (RAG) to enhance model performance
Work with multi-modal AI models (text, image, video, and audio synthesis)
Collaborate on open-source AI projects or contribute to AI research publications
Implement A/B testing, user feedback loops, and AI-driven personalization strategies
Fine-tune and deploy LLMs and transformer-based architectures using frameworks such as Hugging Face, OpenAI, TensorFlow, and PyTorch

Proven experience with Google Cloud Platform and its AI/ML services
Strong background in enterprise AI applications and production-level scaling of LLMs
Hands-on experience with prompt engineering, RLHF, and RAG techniques
Familiarity with multi-modal AI models and generative AI technologies
Contributions to open-source AI projects or published research in AI
Expertise in A/B testing, personalization, and feedback-driven optimization
Proficiency in fine-tuning and deploying LLMs using modern AI frameworks

Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days, depending on grade
Company paid holidays
Personal Days
Sick Leave
Medical, dental, and vision coverage (or provincial healthcare coordination in Canada)
Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada)
Life and disability insurance
Employee assistance programs
Other benefits as provided by local policy and eligibility

Lead Data Scientist

Key skills