Research Engineer
At a glance
Mid-level AI Research role at Nace AI. Palo Alto · full-time · no salary stated · we estimate $135,000–$232,000 across the United States.
Nace AI has not published a salary for this role. The figure below is our estimate, not theirs.
aimlroles summary, based on the employer's posting.
What you'll do
- Set research questions around adapting language models, meta-learning and hypernetworks, then evaluate ideas with rigorous experiments
- Move successful research approaches from testing into production systems with engineering teammates
- Publish findings or make them available as open-source work when appropriate
- Shape methods used to build customized intelligence on the company’s named platforms
What you bring
- At least three years across machine-learning research and engineering, including hands-on language-model work
- A strong research foundation in language modeling, NLP or a related discipline, plus work with LLMs or VLMs
- Use quantitative methods to address language understanding, generation or multimodal AI challenges
- Write Python and use a deep-learning framework such as PyTorch, JAX or TensorFlow, with distributed model training and optimization experience
Who this fits
This suits a hands-on researcher who wants to lead problems from initial framing through experiments and work with engineers to put effective methods into production. The position is onsite in Palo Alto.
From the employer
About Us:
At Nace AI, we are redefining how professional services operate by delivering Sovereign Specialized Intelligence. As an applied research and product company, we equip enterprises with a comprehensive AI stack to build customized, secure intelligence tailored to their unique business needs.
Driven by advanced Small Language Models and our dynamic metamodel framework, our flagship platforms - Nace Data Intelligence and the Nace SLM Cloud - enable true end-to-end business process automation. The result is transformative ROI: professional services firms using Nace AI are currently recovering 1,000 hours per client engagement, drastically reducing overhead and accelerating delivery.
The work we are doing has a meaningful impact across industries, and every hire at Nace AI plays a critical role in shaping the company’s trajectory. This is a unique opportunity to join a high conviction AI company at an early stage and directly influence its growth.
If building a world-class AI team from the ground up excites you, we’d love to talk.
About the Role
We're looking for a Research Scientist to advance the core methods behind Nace AI's Small Language Models and metamodel framework. You'll work at the intersection of research and production, designing novel approaches to LLM adaptation, meta-learning, and hypernetworks, then carrying them from experimentation into systems that power Nace Data Intelligence and the Nace SLM Cloud.
This is a hands-on role on a small, high-caliber team. You'll own research problems end to end: framing the question, running rigorous experiments, publishing or open-sourcing where it makes sense, and partnering closely with engineering to ship what works. Your work will directly shape how enterprises build customized, secure intelligence on our stack.
Minimum Qualifications
3+ years of combined research and engineering experience in machine learning, including hands-on work with language models.Direct experience working with Large Language Models (LLMs) or Vision-Language Models (VLMs) in research or production settings
Strong research background in Natural Language Processing, Machine Learning, or related disciplines with focus on language modeling
Proven track record in solving complex problems in language understanding, generation, or multimodal AI using rigorous quantitative methodologies
Demonstrated ability to clearly communicate research findings to diverse technical audiences
Proficient programming skills in Python and deep learning frameworks (PyTorch, JAX, or TensorFlow), with experience in distributed training and model optimization
Preferred Qualifications
5+ years of experience conducting applied ML research, with a sustained record of taking novel methods from experimentation to working systems.
PhD in Computer Science, Computational Linguistics, or closely related field with focus on language models and adaptive learning systems
Proven research and engineering experience with LLMs/VLMs, particularly in meta-learning or parameter-efficient adaptation, as evidenced by grants, fellowships, patents, internships, or contributions to open-source projects
First authored publications on language models, meta-learning, hypernetworks, or adaptive AI in recognized peer-reviewed conferences (ACL, EMNLP, NeurIPS, ICML, ICLR) or journals
Kaggle experience is a plus.
Preferred Technical Experience
Research expertise in LLM reasoning, hypernetworks, multi-task learning, meta-learning, designing novel LLM adaptation methods, Online Continual Learning