採用
福利厚生
•Equity
•Learning
•Flexible Hours
•Healthcare
必須スキル
Python
Node.js
PostgreSQL
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:
We’re looking for a customer-obsessed software engineer to come ship with us. You’ll own features like multi-node training and products like serverless reinforcement learning (RL) from conception to MVP (and from MVP to GA!). You’ll work through the stack, architecting solutions from API and UI down to our infrastructure layer. You’ll fine tune models yourself to develop an understanding of user workflows. You’ll work closely with research engineers leveraging state-of-the-art training techniques to build experiences that accelerate model development and solve for real pain points. If you’re excited to dive deep into the training, let’s talk!
THE PRODUCT
Take a look at what we’ve built so far:
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Overview of the product so far https://www.baseten.co/blog/baseten-training-is-ga/#training-is-now-ga
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Training docs overview https://docs.baseten.co/training/overview
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Story of the Training product https://www.baseten.co/blog/a-q-a-from-inference-to-training-the-inside-story-of-baseten-s-newest-product/
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Research we've done https://www.baseten.co/resources/research/
EXAMPLE INITIATIVES
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Checkpointing Pipeline: Our checkpointing pipeline starts with automated checkpointing, a feature that ensures that versions of models created during training are automatically backed up to the cloud. Users are able to then deploy checkpoints seamlessly into inference servers, providing point-and-click integrations into inference frameworks like vLLM and Baseten’s Inference Stack. This enables customers to quickly evaluate the performance of their checkpoints with real traffic.
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Multinode training: Multinode training enables customers to easily run training jobs across multiple compute nodes, enabling users to train large models like GLM 4.7 and Deep Seek. We’ve built deeply at the Kubernetes layer to ensure that scheduling, startup, inter-node communication, and shutdown happen seamlessly under the hood and as the user expects.
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Training DX: Customers come to train on Baseten because it helps them get to value fast. To do this, we ensure that the features we ship aren’t just fast, but are easy to iterate with. We enhanced Baseten’s metrics from pod-level GPU summaries to per-GPU and per-Node. We’ve built a CLI experience that caters to terminal users, and UI experiences that enable user to seamlessly manage their training jobs.
RESPONSIBILITIES:
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Iterate like crazy
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Design ergonomic APIs and abstractions to model complex resources and lifecycles
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Work throughout the stack (API layer, backend and database implementation, infra layer; frontend is a plus) to implement features.
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Fine-tune and deploy models to develop intuition around training workflows.
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Partner closely with model developers and world-class research engineers to understand the requirements and pain points of post-training workflows.
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Drive long-term improvements to improve reliability of systems and velocity of development
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Fix bugs & resolve customer issues with urgency
REQUIREMENTS:
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5+ years experience building software applications
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Deep knowledge of the web stack, databases, and distributed systems
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Experience developing developer tooling or infrastructure products for external or internal users.
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Good taste in product, particularly developer-oriented tools
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Interest in ML/AI infrastructure and willingness to learn
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Driven by high agency and ownership
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Strong communication skills with the ability to bridge technical depth and business needs
NICE TO HAVE:
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Experience launching features and products through different release cycles (MVP, Beta, GA, etc.)
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Experience with model development methods and paradigms, like Supervised Fine-Tuning, Reinforcement Learning, Synthetic Data Generation, LoRA, Full Finetunes, etc.
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Familiarity or experience with the open source training stack and frameworks (NCCL, Py Torch, Megatron, NemoRL, VeRL, Axolotl, HF Trainer) and distributed training techniques (FSDP, Deep Speed).
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Experience developing AI products, tooling, or agents
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Frontend fluency
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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0
応募クリック数
0
模擬応募者数
0
スクラップ
0
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Basetenについて

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
従業員数
San Francisco
本社所在地
$1.0B
企業価値
レビュー
4.1
10件のレビュー
ワークライフバランス
4.2
報酬
2.8
企業文化
4.3
キャリア
3.5
経営陣
3.2
72%
友人に勧める
良い点
Flexible work arrangements and schedules
Supportive team environment and good colleagues
Good benefits and health coverage
改善点
Below industry standard compensation and salary
Limited career advancement opportunities
High workload and stressful expectations
給与レンジ
9件のデータ
Junior/L3
L2
L3
L4
L5
L6
Recruiter
Junior/L3 · Recruiter
0件のレポート
$183,600
年収総額
基本給
-
ストック
-
ボーナス
-
$156,060
$211,140
面接体験
52件の面接
難易度
3.3
/ 5
期間
14-28週間
内定率
42%
体験
ポジティブ 66%
普通 21%
ネガティブ 13%
面接プロセス
1
Phone Screen
2
Technical Interview
3
Hiring Manager
4
Team Fit
よくある質問
Technical skills
Past experience
Team collaboration
Problem solving
ニュース&話題
Baseten Introduces Delivery Network Aimed at Faster Large-Model Inference - TipRanks
TipRanks
News
·
4w ago
Baseten Technologies - 2026 Funding Rounds & List of Investors - Tracxn
Tracxn
News
·
4w ago
Strat AE l Baseten vs Cursor?
I have an opportunity to go to Baseten or Cursor as a strat rep. I'm torn on the meteoric rose of Cursor vs getting into the inference game given its size & CAGR. What would you do? Anyone have experience with either?
·
5w ago
·
6
·
21
Inferless Joins Baseten
HN
·
9w ago
·
1