Job Description

Job Title: Member of Technical Staff – Model Training Role Overview Join 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 Us 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. #J-18808-Ljbffr Hireclout

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