Senior Applied Scientist (Remote, US)

About the Role

The AI Innovation Lab is an early-stage team within a growth-stage company, providing the opportunity for real ownership over hard problems and the room to shape how they are solved. This is not a research role; you will be building models that go to production on messy, high-stakes data, requiring a high comfort level working with complex, unstructured data.

Sayari's technology is trusted by U.S. Customs and Border Protection, HM Revenue & Customs, and Fortune 500 enterprises, and is used by thousands of professionals across 35+ countries to secure supply chains and dismantle illicit networks. As a Senior Applied Scientist, you will be contributing to the development of cutting-edge technology that has a real impact on global commerce.

What You Will Do

• Design and execute fine-tuning strategies (LoRA, full fine-tuning) and own the experimentation cycle from hypothesis through production deployment
• Build and refine data collection and labeling strategies for complex, messy domains, including designing auto-labeling pipelines
• Evaluate and select base models (proprietary and open-source) for domain-specific tasks, focusing on small language models (SLMs)
• Deploy fine-tuned models to production using cloud ML platforms (Vertex AI, SageMaker, or equivalent)
• Develop rigorous evaluation frameworks that measure real-world performance on agentic workflows, not just benchmarks
• Work closely with the Technical Lead on architecture and strategy decisions
• Collaborate with a small team of AI/ML engineers who ship together
• Develop and maintain expertise in the latest advancements in machine learning and data science
• Stay up-to-date with industry trends and emerging technologies

What We Are Looking For

• 5+ years of experience in applied ML with a focus on model training and fine-tuning in a commercial setting
• 2+ years of hands-on experience with LoRA and full fine-tuning
• Track record of deploying fine-tuned models to production on cloud ML platforms
• High comfort level working with messy, unstructured data and designing labeling strategies from scratch
• Proficiency with HuggingFace, PyTorch, and at least one cloud ML platform
• Strong opinions about base model selection, held loosely
• Ability to articulate tradeoffs between architectures
• Experience working with complex data and designing auto-labeling pipelines
• Strong understanding of machine learning and data science concepts

Nice to Have

• Experience working with small language models (SLMs)
• Knowledge of cloud ML platforms (Vertex AI, SageMaker, or equivalent)
• Familiarity with agentic workflows and evaluation frameworks
• Experience working in a fast-paced, growth-stage company

Benefits and Perks

• 100% fully paid medical, vision, and dental for employees and their dependents
• Generous time off, including 18 PTO days and 10 sick days
• Outstanding compensation package, with a target base salary of
  85,000-$200,000 plus company bonus and equity
• Eligibility to participate in additional benefits, such as 401k match up to 5% and 100% paid life insurance (up to
  00,000 coverage)
• A collaborative and positive culture, with a strong commitment to diversity, equity, and inclusion
• The opportunity to work with a talented team of professionals who are passionate about AI and machine learning
• The chance to contribute to the development of cutting-edge technology that has a real impact on global commerce

• Be prepared to discuss your experience with model training and fine-tuning, and how you have deployed models to production in the past.
• Make sure you have a strong understanding of machine learning and data science concepts, and be prepared to articulate tradeoffs between different architectures.
• Highlight your ability to work with complex, unstructured data and design labeling strategies from scratch.
• Be prepared to talk about your experience working with cloud ML platforms, such as Vertex AI or SageMaker.
• Show enthusiasm for the company's mission and technology, and be prepared to discuss how you can contribute to the development of cutting-edge AI models.
• Don't be afraid to ask questions about the company culture and values, and how they impact the way the team works.
• Be prepared to provide examples of your experience working in a fast-paced, growth-stage company, and how you have adapted to changing priorities and requirements.