Member of Technical Staff - Post-Training

Reflection AI; San Francisco (CA); On-site; USD 90,000 - 130,000; Full time

Benefits offered by this job

Top-tier compensation

Comprehensive health insurance

Fully paid parental leave

Paid time off

Daily meals and team celebrations

Job summary

A forward-thinking AI company in San Francisco is seeking a Member of Technical Staff - Post‑Training to build systems that transform powerful models. The ideal candidate has a deep understanding of machine learning and strong engineering skills. The role involves collaborating with teams to enhance model capabilities and improve model behavior. This full-time position offers competitive compensation and comprehensive benefits.

Qualifications

• Deep understanding of machine learning fundamentals.
• Strong engineering skills with complex ML codebases.
• Experience with data and reinforcement learning techniques.

Responsibilities

• Build systems for transforming pre‑trained models into aligned agents.
• Drive research and optimization of post‑training.
• Collaborate with teams to enhance model capabilities.

Skills

Machine learning fundamentals

Complex ML codebases

Reinforcement learning techniques

Strong communication skills

Job description

Member of Technical Staff - Post‑Training

Join to apply for the Member of Technical Staff - Post‑Training role at Reflection AI.

Our Mission

Reflection’s mission is to build open superintelligence and make it accessible to all. We’re developing open weight models for individuals, agents, enterprises, and even nation states. Our team of AI researchers and company builders come from DeepMind, OpenAI, Google Brain, Meta, Character.AI, Anthropic and beyond.

About The Role

• Build systems that transform powerful pre‑trained models into aligned and general agents.
• Drive research and engineering initiatives that push the frontier of post‑training, from data curation to large‑scale optimization.
• Develop data generation pipelines, reward models, reinforcement learning algorithms, and inference‑time scaling techniques.
• Collaborate across pre‑training and post‑training teams to deliver step‑function gains in model capability.
• Contribute to shaping our understanding of how large models learn to reason, follow instructions, and improve through reinforcement learning.

About You

• Deep understanding of machine learning fundamentals and practical experience with large‑scale LLM training.
• Strong engineering skills, comfortable diving into complex ML codebases and distributed systems.
• Experience improving model behavior through data, reward modeling, or RL techniques.
• Evidence of owning ambitious research or engineering agendas that led to measurable model improvements.
• Thrive in a fast‑paced, high‑agency startup environment; bias toward action and clarity of execution.
• Able to work fluidly across research and infra boundaries.
• Strong communication capabilities and comfort working collaboratively.
• Passionate about advancing the frontier of intelligence.

What We Offer

We believe that to build superintelligence that is truly open, you need to start at the foundation. Joining Reflection means building from the ground up as part of a small talent‑dense team. You will help define our future as a company, and help define the frontier of open foundational models.

We want you to do the most impactful work of your career with the confidence that you and the people you care about most are supported.

• Top‑tier compensation: Salary and equity structured to recognize and retain the best talent globally.
• Health & wellness: Comprehensive medical, dental, vision, life, and disability insurance.
• Life & family: Fully paid parental leave for all new parents, including adoptive and surrogate journeys. Financial support for family planning.
• Benefits & balance: paid time off when you need it, relocation support, and more perks that optimize your time.
• Opportunities to connect with teammates: lunch and dinner are provided daily. We have regular off‑sites and team celebrations.

Seniority Level

Entry level

Employment type

Full‑time

Job function

Engineering and Information Technology

Industries

Software Development