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Head of Field Engineering
Высокий балл за работу в перспективной сфере Open Source AI, наличие опционов и возможность занять руководящую позицию на раннем этапе развития компании. Предложение включает отличный соцпакет и гибкий формат работы.
Сложность вакансии
Роль требует редкого сочетания глубокой технической экспертизы в области LLM/ML и управленческих навыков уровня Head. Кандидату предстоит строить функцию с нуля в условиях высокой неопределенности стартапа.
Анализ зарплаты
Для позиции Head of Field Engineering в сфере AI/ML в США (Сиэтл/Сан-Франциско) рыночные зарплаты значительно выше средних по IT. Учитывая стадию роста компании, основная часть компенсации может приходиться на опционы (Equity), однако фиксированная часть должна соответствовать высокому уровню ответственности.
Сопроводительное письмо
I am writing to express my strong interest in the Head of Field Engineering position at Oumi. With a robust background in applied machine learning and a proven track record of leading customer-facing technical teams, I am excited about Oumi's mission to make frontier AI open and accessible. My experience in bridging the gap between complex AI research and practical enterprise solutions aligns perfectly with your goal of helping organizations build custom models in hours.
Throughout my career, I have specialized in guiding customers through the entire lifecycle of AI adoption—from initial technical discovery to the deployment of fine-tuned LLMs and RAG systems. I am particularly drawn to Oumi's research-driven and community-powered approach. I am confident that my technical depth in Python and ML frameworks, combined with my strategic mindset for building GTM playbooks, will allow me to effectively scale your field engineering function and drive long-term customer success.
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Описание вакансии
About Oumi
Why we exist: Oumi is on a mission to make frontier AI truly open for all. We are founded on the belief that AI will have a transformative impact on humanity, and that developing it collectively, in the open, is the best path forward to ensure that it is done efficiently and safely. By providing the safest, highest quality, and most flexible AI, we aspire to unlock positive impact for every individual, enterprise, and humanity overall.
What we do: Oumi provides an end-to-end, AI-native to build custom AI models in hours, not months – automating the loop of evaluation, data synthesis, training, and repeat. Oumi also develops an open research stack and models in collaboration with academic collaborators and the open community.
Our Approach: Oumi is built on a foundation of open source, with open collaboration at the heart of everything we do. Our work is:
- Research-driven: We conduct and publish original AI research, working closely with academic research labs and collaborators across the globe.
- Community-powered: We believe in the strength of open collaboration and actively welcome contributions from researchers and developers worldwide.
- Accessibility-focused: We design Oumi to help any organization—regardless of size or resources—effectively build, deploy, and benefit from AI by lowering barriers to access, experimentation, and adoption.
Role Overview
We’re hiring a Head of Field Engineering at Oumi to build and lead the customer-facing technical function that bridges Oumi’s platform, product, and research capabilities with customer outcomes. This leader will own the strategy and execution for field engineering across the customer lifecycle, from technical discovery and solution design through proof of concept, deployment, onboarding, and expansion.
This is a highly cross-functional role for someone who combines strong technical depth in AI/ML systems with a track record of leading customer-facing technical teams. You will partner closely with Sales, Product, Research, and Engineering to help customers successfully adopt Oumi, shape technical strategy in the field, and build the team, processes, and playbooks that scale.
The ideal candidate has experience leading or working closely with sales engineering, applied AI, forward-deployed engineering, solutions architecture, or field engineering teams in fast-moving technical environments.
You will:
Build and lead the field engineering function: Define the vision, operating model, and roadmap for Oumi’s field engineering organization, including hiring, mentoring, and scaling a high-performing team.
Own technical customer engagement: Partner with customers across the pre-sales and post-sales lifecycle, from technical qualification and solution architecture to proofs of concept, deployment, and long-term success.
Lead applied AI work: Guide customers in designing, training, and deploying custom models using Oumi’s platform, including data preparation, model training, fine-tuning, evaluation, and production deployment.
Partner closely with Sales: Serve as a strategic technical partner to GTM leadership, helping shape deal strategy, remove technical blockers, and improve conversion, expansion, and customer satisfaction.
Translate customer needs into product direction: Build strong feedback loops between customers and Oumi’s Product, Research, and Engineering teams to influence roadmap, prioritization, and platform improvements.
Establish repeatable playbooks: Develop the technical demos, implementation patterns, enablement materials, and best practices that help both customers and internal teams succeed.
Represent Oumi externally: Act as a senior technical ambassador in customer meetings, executive conversations, strategic accounts, and community or partner engagements.
What You’ll Bring:
- Total experience: You have 5+ years of experience across applied machine learning, machine learning infrastructure, solutions engineering, sales engineering, forward-deployed engineering, field engineering, or related customer-facing technical roles.
- Leadership experience (preferred, not required): You have 2+ years of experience leading teams or managing senior individual contributors in customer-facing technical organizations such as sales engineering, solutions architecture, applied AI, forward-deployed engineering, or field engineering.
- Customer-facing leadership: You have a strong track record of leading complex enterprise customer engagements and communicating effectively with both technical practitioners and executive stakeholders.
- Applied AI and ML expertise: You bring a deep understanding of modern machine learning workflows, with hands-on experience training, fine-tuning, evaluating, or deploying foundation models such as LLMs, multimodal systems, or other advanced AI models.
- Technical depth: You are proficient in Python and have strong practical experience with modern AI/LLM systems, model training frameworks, and production use cases such as RAG, agents, or agentic systems.
- GTM partnership: You have experience partnering closely with Sales and customer success functions to shape technical strategy, support strategic deals, and improve customer adoption.
- Builder mindset: You are excited to build a function from the ground up, define processes in ambiguity, and scale what works.
- Operational excellence: You can operate effectively in fast-changing environments, prioritize well, and drive cross-functional execution end to end.
- Values: You embody Oumi’s core values: Beneficial for All, Customer-Obsessed, Radical Ownership, Exceptional Teammates, Science-Grounded.
Benefits:
- Equity in a high-growth startup
- Comprehensive health, dental, and vision insurance
- 21 days PTO
- Regular team offsites and events
Location:
- Remote OR hybrid work environment, with offices in:
+ San Mateo, CA
+ Seattle, WA
+ New York, NY
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Навыки
- Python
- Machine Learning
- LLM
- Fine-tuning
- RAG
- Solution Architecture
- AI Infrastructure
- Sales Engineering
Возможные вопросы на собеседовании
Проверка опыта масштабирования команд в стартапах.
Опишите ваш подход к найму и обучению первых пяти инженеров в отдел Field Engineering: какие навыки будут приоритетными?
Оценка технической глубины в области современных ИИ-архитектур.
С какими основными техническими сложностями сталкиваются клиенты при внедрении RAG-систем или агентных архитектур, и как ваша команда может их нивелировать?
Проверка умения работать на стыке продаж и разработки.
Как вы будете разрешать конфликт приоритетов, когда крупному клиенту нужна специфическая фича для закрытия сделки, а она не входит в текущий роадмап продукта?
Оценка опыта работы с жизненным циклом ML-моделей.
Расскажите о самом сложном случае внедрения кастомной модели (fine-tuning) у клиента: как вы оценивали успех и какие метрики использовали?
Проверка лидерских качеств и стратегического мышления.
Как вы планируете выстраивать процесс сбора обратной связи от клиентов, чтобы он напрямую влиял на исследовательскую деятельность (Research) компании?
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