Applied AI Researcher for Real-World Customer Models

River AI; Palo Alto (CA); On-site; USD 200,000 - 420,000; Full time

Benefits offered by this job

Health, dental, and vision insurance

Unlimited PTO

Relocation assistance

Visa sponsorship

Job summary

River AI in Palo Alto is seeking exceptional applied researchers to work directly with customers across industries to train and improve their own models. Your goal is to translate real-world problems, domain expertise, and customer data into models that deliver measurable value in their workflows.

You will own the applied research lifecycle, from defining the problem and preparing data to designing experiments, training models, and evaluating results.

Qualifications

• 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, with a track record of writing clean, scalable code for model training and experimentation.
• Proven ability to turn open-ended problems and imperfect real-world data into working models, using rigorous experiments and evaluation to guide decisions.
• Strong communication and collaboration skills, with the ability to work directly with customers, learn new domains, and explain technical tradeoffs to technical and non-technical audiences.
• A highly collaborative mindset, ownership of outcomes, and a bias for action in a fast-paced environment.

Responsibilities

• Partner directly with customers across industries to understand their workflows, identify high-value modeling problems, and define success criteria.
• Develop data preparation and curation pipelines with customer teams, turning domain-specific data and expert feedback into training datasets and representative evaluations.
• Design and run training experiments using techniques such as continued pre-training, supervised fine-tuning, reinforcement learning, and parameter-efficient fine-tuning (PEFT), selecting approaches that fit each customer's goals, data, and compute budget.
• Build evaluation suites, analyze model failures, and iterate on data and training methods to improve quality, reliability, and performance on real customer tasks.
• Work with customer engineers and River's infrastructure team to scale training runs, resolve bottlenecks, and support deployment and ongoing model improvement.
• Turn lessons from customer engagements into reusable training recipes, evaluation tools, and improvements to River's platform.

Skills

Deeper understanding of deep learning

PyTorch

JAX

Experiment design & evaluation

Customer engagement & communication

Collaboration in fast-paced teams

Education

BS/MS/PhD in CS/ML/Math or equivalent

Tools

PyTorch

JAX

Job description

River AI in Palo Alto is seeking exceptional applied researchers to work directly with customers across industries to train and improve their own models. Your goal is to translate real-world problems, domain expertise, and customer data into models that deliver measurable value in their workflows.

You will own the applied research lifecycle, from defining the problem and preparing data to designing experiments, training models, and evaluating results.