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Описание вакансии
Текст:
TL;DR
Solutions Engineering Lead, Consumer (AI): Building scalable GenAI solutions, technical playbooks, evaluation frameworks, and production architectures for consumer businesses with an accent on latency, throughput, cost-per-inference, and quality at volume. Focus on leading Solutions Engineers, owning strategic technical wins, designing prototypes and demos, and translating consumer-scale product patterns into roadmap input for Product and Engineering.
Company
Scale AI develops reliable AI systems, high-quality training data, and full-stack technologies for enterprises, governments, and leading AI applications.
What you will do
- Manage, coach, hire, and develop a team of 3–5 Solutions Engineers.
- Own technical wins for strategic consumer accounts through demos, prototypes, and architecture discussions.
- Build reusable reference architectures, demo environments, evaluation frameworks, and statements of work.
- Guide GenAI solutions for agentic customer experiences, personalization, search relevance, trust and safety, and content moderation.
- Partner with Account Executives, GTM leadership, Software Engineers, and Machine Learning Engineers from qualification through early implementation.
- Translate account-level patterns into prioritized input for Product and Engineering roadmaps.
Requirements
- Strong engineering background and significant experience in solutions engineering, solutions architecture, forward-deployed engineering, or technical consulting.
- Hands-on development experience in Python or a similar language.
- Experience leading or mentoring technical individual contributors.
- Experience with high-scale consumer systems such as recommendation, personalization, search, content moderation, or conversational products.
- Strong presentation skills and technical credibility with executives, product stakeholders, and engineers.
- Ability to evaluate performance, cost, latency, throughput, and quality tradeoffs in consumer-scale systems.
Nice to have
- Hands-on GenAI, LLM, or applied machine learning experience, especially evaluation and quality measurement at high volume.
- Background in retail, e-commerce, media, gaming, marketplaces, or social platforms.
- Experience building a new vertical, practice, or team from an early stage.
Culture & Benefits
- Inclusive and equal opportunity workplace with reasonable accommodation support.
- Comprehensive health, dental, and vision coverage.
- Retirement benefits, learning and development stipend, and generous paid time off.
- Additional benefits may include a commuter stipend and equity compensation for eligible roles.
Hiring process
- Compensation and level are determined during the interview process based on work location, skills, experience, qualifications, and interview performance.
- Candidates may not be reconsidered for the same role until 90 days after a previous application.
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