Applied Researcher (AI)

Location: Palo Alto, California, United States

Base pay: $200,000–$420,000 USD per year, plus equity.

Company

hirify.global is building personal AI through personal hardware for local inference, bespoke training infrastructure, next-generation user interfaces, and frontier deep learning research.

What you will do

• Partner with customers across industries to understand workflows, identify high-value modeling problems, and define success criteria.
• Build data preparation and curation pipelines, training datasets, and representative evaluations from domain-specific data and expert feedback.
• Design and run continued pre-training, supervised fine-tuning, reinforcement learning, and parameter-efficient fine-tuning experiments.
• Build evaluation suites, analyze model failures, and iterate on data and training methods to improve quality, reliability, and performance.
• Work with customer engineers and the infrastructure team to scale training, resolve bottlenecks, and support deployment and ongoing model improvement.
• Turn customer engagement insights into reusable training recipes, evaluation tools, and platform improvements.

Requirements

• BS, MS, or Ph.D. in Computer Science, Machine Learning, Mathematics, or equivalent practical industry experience.
• Strong understanding of modern deep learning architectures and practical experience training, fine-tuning, and evaluating language or multimodal models.
• Extensive hands-on experience with PyTorch or JAX, including clean, scalable code for model training and experimentation.
• Ability to turn open-ended problems and imperfect real-world data into working models through rigorous experimentation and evaluation.
• Strong communication and collaboration skills, including direct customer engagement, learning new domains, and explaining technical tradeoffs to technical and non-technical audiences.
• Collaborative mindset, ownership of outcomes, and bias for action in a fast-paced environment.

Nice to have

• Experience delivering models for customer or industry use cases with measurable improvements in model performance or business outcomes.
• Expertise in reinforcement learning, preference optimization, synthetic data generation, or adapting models to specialized domains.
• Experience with distributed training, experiment management, or deploying and monitoring models in production.
• Experience partnering with domain experts and handling proprietary or sensitive datasets under customer privacy and security requirements.

Culture & Benefits

• Work alongside scientists, engineers, and builders from leading technology companies and AI labs.
• Comprehensive health, dental, and vision insurance.
• Unlimited paid time off.
• Relocation assistance as needed.
• Visa sponsorship is available for the right candidate.