Tykhe Inc · 6 hours ago
Artificial Intelligence Researcher
Tykhe Inc is a leading provider of Revenue Cycle Management for the healthcare industry, and they are seeking an AI Research Scientist to join their team. The role involves designing and analyzing machine learning experiments, collaborating with cross-functional teams, and contributing to academic publications.
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Responsibilities
Design, execute, and analyze machine learning experiments, establishing strong baselines and selecting appropriate evaluation metrics
Stay up to date with the latest AI research; identify, adapt, and validate novel techniques for company-specific use cases
Define rigorous evaluation protocols, including offline metrics, user studies, and adversarial (red team) testing to ensure statistical soundness
Specify data and annotation requirements; develop annotation guidelines and oversee quality control processes
Collaborate closely with domain experts, product managers, and engineering teams to refine problem statements and operational constraints
Develop reusable research assets such as datasets, modular code components, evaluation suites, and comprehensive documentation
Work alongside ML Engineers to optimize training and inference pipelines, ensuring seamless integration into production systems
Contribute to academic publications and represent the company in research communities, as needed
Qualification
Required
Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related field is strongly preferred
Candidates with a master's degree and exceptional research or industry experience will also be considered
3–5 years of experience in AI/ML research roles, ideally in applied or product-focused environments
Demonstrated success in delivering research-driven solutions that have been deployed in production
Experience collaborating in cross-functional teams across research, engineering, and product
Strong foundational knowledge in machine learning and deep learning algorithms
Hands-on experience with PEFT/LoRA, adapters, fine-tuning techniques, and RLHF/RLAIF (e.g., PPO, DPO, GRPO)
Ability to read, implement, and adapt state-of-the-art research papers to real-world use cases
Proficiency in hypothesis-driven experimentation, ablation studies, and statistically sound evaluations
Advanced programming skills in Python (preferred), C++, or Java
Experience with deep learning frameworks such as PyTorch, Hugging Face, NumPy, etc
Strong mathematical foundations in probability, linear algebra, and calculus
Domain expertise in one or more areas: natural language processing (NLP), symbolic reasoning, speech processing, etc
Ability to translate research insights into roadmaps, technical specifications, and product improvements
Preferred
Publications in top-tier AI/ML conferences (e.g., NeurIPS, ICML, ACL, CVPR) are a plus