Member of Technical Staff, Research Engineer / Research Scientist (Post-Training)

About the Role

As a Member of Technical Staff, Research Engineer on our Model Training team, you will be at the heart of our efforts to elevate model performance through innovative post training strategies. Your work will focus on optimizing our models after initial training by developing and implementing advanced fine-tuning methodologies. This role is critical to ensuring that our AI systems not only meet but exceed the demands of enterprise-scale applications.

This is a good role for you if you:

• Have extensive experience in training large-scale language models and designing sophisticated post training pipelines.
• Are proficient with modern deep learning frameworks—especially PyTorch—and possess a deep understanding of transformer architectures.
• Have a strong track record in fine-tuning strategies, including techniques such as RLHF, DPO, or other reinforcement learning-based methods.
• Thrive on solving high-stakes challenges by developing innovative approaches that directly impact model robustness, alignment, and operational reliability.
• Are passionate about pushing the boundaries of AI and eager to collaborate across multidisciplinary teams to drive enterprise success.

Responsibilities include:

• Designing and implementing scalable post training pipelines that integrate advanced fine-tuning techniques to optimize model performance.
• Developing and iterating on novel methodologies—including reinforcement learning approaches—to enhance model alignment, robustness, and safety.
• Collaborating with cross-functional teams to translate research breakthroughs into production-ready systems for enterprise applications.
• Continuously evaluating and refining training processes using rigorous experimentation and performance metrics to ensure our models remain at the cutting edge.
• Serving as a key technical leader, driving innovation in model training that directly shapes the future of enterprise AI.

Employee Pay Disclosures

At Inflection AI, we aim to attract and retain the best employees and compensate them in a way that appropriately and fairly values their individual contributions to the company. For this role, Inflection AI estimates a starting annual base salary will fall in the range of approximately $175,000 - $350,000 depending on experience. This estimate can vary based on the factors described above, so the actual starting annual base salary may be above or below this range.

Interview Process

Apply: Please apply on Linkedin or our website for a specific role.

After speaking with one of our recruiters, you’ll enter our structured interview process, which includes the following stages:

1. Hiring Manager Conversation – An initial discussion with the hiring manager to assess fit and alignment.
2. Technical Interview – A deep dive with an Inflection Engineer to evaluate your technical expertise.
3. Onsite Interview – A comprehensive assessment, including:
• A domain-specific interview
• A system design interview
• A final conversation with the hiring manager

Depending on the role, we may also ask you to complete a take-home exercise or deliver a presentation.

For non-technical roles, be prepared for a role-specific interview, such as a portfolio review.

Decision Timeline
We aim to provide feedback within one week of your final interview.