Job Title:

Member of Technical Staff – Model Training

Role Overview

Join our Client, a fast-moving AI company focused on enterprise-grade conversational intelligence. This organization is a mission-driven public benefit corporation that equips businesses with customizable language models, proprietary data pipelines, and intelligent tuning systems—allowing virtual assistants to become smarter, more accurate, and brand-aligned over time.

This role sits at the intersection of ML research and production engineering. As a Model Training Engineer, you’ll help turn general-purpose LLMs into finely tuned, high-performing assistants using cutting-edge post-training and fine-tuning techniques. You'll have access to massive GPU clusters, real-world feedback loops, and the autonomy to experiment, iterate, and deploy improvements rapidly.

Key Responsibilities

• Develop and maintain scalable post-training workflows including dataset curation, evaluation, hyperparameter tuning, and rollout
• Experiment with and deploy advanced alignment methods such as RLHF, DPO, GRPO, and RLAIF
• Build training automation tools, dashboards, and pipeline components to improve reproducibility and traceability
• Define key training metrics, run A/B tests, and quickly iterate to hit performance goals
• Collaborate cross-functionally with inference, safety, and product teams to integrate model improvements into user-facing systems

Education & Qualifications

• Hands-on experience training large transformer models on distributed GPU systems (multi-GPU, multi-node)
• Strong proficiency with Python and PyTorch, including ecosystem tools like Torchtune, FSDP, and DeepSpeed
• Practical understanding of reinforcement learning techniques (RLHF, DPO, GRPO, RLAIF)
• Effective communicator across both technical and non-technical stakeholders
• Proven ability to build reproducible and automated training infrastructure

Preferred Experience

• Experience with multimodal (vision-language, audio-text) or voice models
• Familiarity with cross-modal data preparation and model alignment
• Contributions to open-source ML tooling

Why Our Client

• High-impact mission – Shape the future of enterprise AI by building assistants that reflect each brand’s voice authentically
• Massive compute resources – Access thousands of NVIDIA and Intel Gaudi GPUs for rapid iteration and experimentation
• Growth & autonomy – Competitive compensation ($200K–$350K base), meaningful equity, and ownership of critical projects
• Open-source culture – Actively contribute to projects like Torchtune, PyTorch, and vLLM; every engineer is encouraged to give back

Applicants must be currently authorized to work in the United States on a full-time basis now and in the future. This position does not offer sponsorship.