Applied AI Researcher – Optimization, Domain Models

This is a fully remote position, open to applicants in United States.

📋 Description

• Create reasoning and optimization models tailored to specific problems.

• Refine vertical LLMs to accommodate industry-specific terminology, workflows, and limitations.

• Develop models for anomaly detection, forecasting, and quality inspection.

• Modify foundational models to adhere to domain-specific rules, policies, and regulations.

• Manage evaluation processes (offline, online, and human-in-the-loop).

• Establish guardrails for controlling hallucinations, mitigating bias, and ensuring policy compliance.

• Deploy safety tools for robust enterprise-grade AI applications.

• Set success metrics aligned with business and operational goals.

• Transform research prototypes into scalable, deployable micro-industry models.

• Collaborate with engineers to embed models into agents and SaaS workflows.

• Record model behavior, underlying assumptions, and potential failure scenarios.

• Develop standardized playbooks for model adaptation.

• Contribute to the development of proprietary model architectures and training methodologies.

• Author internal whitepapers and external points of view where suitable.

• Assist in go-to-market narratives with substantial technical insight.

⛳️ Requirements

• Preferred PhD in AI, ML, Applied Mathematics, Operations Research, or a related discipline.

• Solid foundation in optimization, probabilistic modeling, or deep learning.

• Proven experience in fine-tuning LLMs or training models specific to certain domains.

• Practical experience with Python, PyTorch, TensorFlow, or JAX.

🏝️ Benefits

• Competitive salary

• Flexible working hours

• Professional development budget

• Home office setup allowance

• Global team events