Member of Engineering (Post-training AI)

TL;DR

Member of Engineering (Post-training AI): Turning pre-trained LLMs into well-aligned and highly capable AI systems for coding and software development with an accent on post-training algorithms, agentic use cases, data pipelines, and experiment design. Focus on researching specialization techniques, implementing fine-tuning methods, analyzing training experiments, and building scalable AI infrastructure.

Location: Remote (EMEA/East Coast)

Company

hirify.global aims to build AGI as the engine for economically valuable work and scientific progress through applied research, engineering, and massive scaling.

What you will do

• Research and experiment on specializing foundational models for agentic use cases in coding.
• Build and maintain data and training pipelines for post-training workflows.
• Design, analyze, and iterate on fine-tuning, alignment, and data generation experiments.
• Stay current with state-of-the-art in LLMs, alignment, synthetic data, and code generation.
• Write high-quality, pragmatic code and collaborate closely with the team on planning and communication.

Requirements

• Deep experience with LLMs: Transformers, deep learning fundamentals, post-training, probing capabilities, distributed training.
• Strong machine learning and engineering background with research experience in proposing and evaluating novel ideas.
• Familiarity with fine-tuning, alignment, synthetic data, continual learning, RLHF, or code generation.
• Programming: Linux, strong algorithms, Python with PyTorch or JAX, modern tools including code agents.
• Comfortable in fast-iterating environments with critical thinking and clear team communication.

Nice to have

• Prior non-ML programming experience, especially outside Python.

Culture & Benefits

• Fully remote-first with flexible hours and monthly 3-day in-person meetups plus biannual offsites.
• 37 days/year vacation and holidays.
• Health insurance allowance for you and dependents, company equipment, wellbeing/learning/home office stipends.
• Diverse, inclusive, people-first culture emphasizing high-quality engineering and rapid iterations.

Hiring process

• Intro call with Founding Engineer.
• Technical interview(s) with Founding Engineer.
• Team fit call with People team.
• Final interview with Founding Engineer.