
Platform for deploying machine learning models
Technical Enablement Lead
福利待遇
•医疗保险
•401k
•股权
•无限假期
•育儿假
必备技能
Technical Communication
ML Inference Systems
Technical Enablement
ABOUT BASETEN
Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $300M Series E https://www.baseten.co/blog/announcing-baseten-s-300m-series-e/, backed by investors including BOND, IVP, Spark Capital, Greylock, and Conviction. Join us and help build the platform engineers turn to to ship AI products.
THE ROLE:
Forward Deployed Engineering (FDE) is Baseten’s most hands-on engineering function with customers. FDE owns outcomes in production and stays accountable throughout the entire customer lifecycle by accelerating customers to value while folding real-world learnings back into the core product.
We’re hiring a Technical Enablement Lead to make that excellence repeatable and scalable across the team. In this role, you will build the systems, content, and hands-on technical programs that enable Baseten’s customer-facing engineers to consistently deliver production-grade inference systems with clear quality, latency, and cost outcomes. Your will develop and operationalize "FDE University" at Baseten as our onboarding bootcamp for new FDEs and continued enablement and training on new product updates and best practices
WHAT YOU'LL DO:
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Build the enablement system that scales FDE
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Own and scale technical enablement for customer-facing engineers.
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Build structured onboarding, training, and delivery playbooks that reduce ramp time and improve production quality.
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Create learning labs, reference architectures, and opinionated templates for common inference workflows, including Truss and Chains.
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Own internal technical knowledge: Establish and maintain a single source of truth for runbooks, troubleshooting, and performance best practices.
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Close the loop between field learnings and product: Turn field learnings into durable enablement assets and product feedback in partnership with Product and Engineering.
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Measure impact and iterate: Define and track enablement KPIs and continuously iterate based on real-world outcomes.
EXAMPLE INITIATIVES
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A “Baseten Inference Expert Share” for new FDEs: Truss + Chains + observability + performance fundamentals + production readiness checklist.
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A certification path for “Production Inference Delivery” that standardizes how projects move from PoC to reliable production services.
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A reference library of architectures and templates (LLM serving, GPU performance triage, cost/latency tradeoffs, rollout + rollback patterns).
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A playbook for “own it, fix it, write it down” incident learning that reduces repeat escalations across accounts.
REQUIREMENTS:
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5+ years of experience supporting production software and systems teams.
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Proven ability to teach and communicate complex technical topics to technical audiences.
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Working knowledge of software engineering fundamentals, ML inference systems, and operating high-performance services (scaling, reliability, observability, incident response).
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Experience in technical enablement, developer education, solutions engineering, or a related role supporting customer-facing engineers.
BONUS
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Familiarity with modern inference ecosystems and serving engines (and the realities of performance debugging in production).
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Prior experience building structured onboarding / certification programs for technical teams (labs, simulations, curricula).
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Experience shipping reusable internal tooling or open-source enablement assets in a developer tools company.
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Familiarity with Baseten workflows (Truss / Chains) or similar model packaging + orchestration systems.
BENEFITS:
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Competitive compensation, including meaningful equity.
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100% coverage of medical, dental, and vision insurance for employee and dependents
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Generous PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!)
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Paid parental leave
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Company-facilitated 401(k)
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Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities.
Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you.
At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status.
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关于Baseten

Baseten
Series CBaseten provides a platform for deploying and scaling machine learning models in production environments. The company offers infrastructure and tools for ML engineers to build, deploy, and monitor AI applications.
51-200
员工数
San Francisco
总部位置
$1.0B
企业估值
评价
10条评价
3.9
10条评价
工作生活平衡
4.2
薪酬
2.8
企业文化
4.1
职业发展
2.5
管理层
3.2
72%
推荐率
优点
Good work-life balance
Supportive team and management
Great culture and teamwork
缺点
Limited career advancement opportunities
Compensation issues
Management communication problems
薪资范围
14个数据点
Junior/L3
L2
L6
Recruiter
Intern
L3
L4
L5
Junior/L3 · Recruiter
0份报告
$183,600
年薪总额
基本工资
-
股票
-
奖金
-
$156,060
$211,140
面试评价
52条评价
难度
3.3
/ 5
时长
14-28周
录用率
42%
体验
正面 66%
中性 21%
负面 13%
面试流程
1
Phone Screen
2
Technical Interview
3
Hiring Manager
4
Team Fit
常见问题
Technical skills
Past experience
Team collaboration
Problem solving
最新动态
Nvidia invests $150 million in AI inference startup Baseten - MSN
MSN
News
·
1w ago
Exclusive: Baseten, AI inference unicorn, raises $150 million at $2.15 billion valuation - MSN
MSN
News
·
1w ago
Nvidia invests $150 million in AI inference startup Baseten - MSN
MSN
News
·
2w ago
Baseten Introduces Delivery Network Aimed at Faster Large-Model Inference - TipRanks
TipRanks
News
·
7w ago