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

Benefits

• Diverse medical, dental and vision options 
• 401k matching program 
• Unlimited paid time off 
• Parental leave and flexibility for all parents and caregivers
• Support of country-specific visa needs for international employees living in the Bay Area

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.

#LI-KB1

Job Title: LLM Infrastructure & Backend Engineer

Role Overview
Join a mission-driven AI company focused on building secure, scalable platforms for enterprise-grade machine learning products. Backed by one of the world’s most powerful large language models, this organization is transforming conversational AI into real-world business applications. You’ll be part of a collaborative, fast-paced environment that values kindness, innovation, and impact.

This role is ideal for backend engineers who are passionate about ML systems and excited to shape the technical foundation of a cutting-edge enterprise AI product.

Key Responsibilities

• Design and build backend services to support LLM integration, inference orchestration, and data flow.

• Develop clean, production-grade Python code for experimentation, model serving, and system integration.

• Partner closely with ML researchers to rapidly prototype and deploy new product features.

• Build infrastructure capable of handling scalable inference workloads and complex enterprise use cases.

• Take ownership of backend components—ensuring reliability, observability, and maintainability.

Education & Qualifications

• Proficient in backend development using Python, TypeScript, or Node.js.

• Experienced in building and deploying production PyTorch models, including inference pipelines and checkpoint handling.

• Strong foundation in developing scalable, secure APIs and backend services.

• Familiar with FastAPI, Postgres, Redis, Kubernetes, and React.

• Comfortable working in a high-velocity startup environment with evolving goals and systems.

Preferred Experience

• Experience bridging ML systems and backend engineering at the infrastructure level.

• Hands-on work in real-time inference orchestration or ML platform tooling.

• Familiarity with startup or early-stage product development environments.

Why Us

• Impact: Directly influence the next generation of ML-powered enterprise applications.

• Team: Join a kind, experienced, and collaborative team of engineers and researchers.

• Innovation: Help shape infrastructure for one of the most advanced LLMs in the world.

• Career Growth: Opportunity to take on leadership roles as the company scales.

Benefits

• Competitive salary ($200k-350k depending on experience).
• Diverse medical, dental and vision options 
• 401k matching program 
• Unlimited paid time off 
• Parental leave and flexibility for all parents and caregivers
• Support of country-specific visa needs for international employees living in the Bay Area
•  

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.

#LI-KB1