채용
Neptune.ai

Neptune.ai
Leading company in the artificial intelligence industry
Machine Learning
Data Science
Model Management
Experiment Tracking
MLOps
채용 중인 포지션
3개 포지션
Technical Product Manager
Product
Remote in Europe
On-site
Lead
Full-time
Remote Work
유연 근무제
스톡옵션
1개월 전
Principal Solutions Architect
Solutions Architect
Canada
On-site
Staff
Contract
Remote Work
유연 근무제
스톡옵션
무제한 휴가
1개월 전
Principal Solutions Architect
Solutions Architect
USA
On-site
Staff
Contract
Remote Work
유연 근무제
스톡옵션
무제한 휴가
1개월 전
제품 및 서비스

Neptune Experiment Tracking
MLOps
NE
Neptune Experiment Management
Experiment Tracking

Neptune Model Registry
MLOps
NE
Neptune Model Registry
Model Management

Neptune Metadata Store
Data Management
NE
Neptune Metadata Store
Metadata Management

Neptune Monitoring
ML Monitoring
NE
Neptune Notebooks
Notebook Management

Neptune Notebooks
Development Tools
NE
Neptune Dashboard
Visualization

Neptune API & SDK
Integration
NE
Neptune API & Integrations
Integration
NE
Neptune Teams & Collaboration
Collaboration

Neptune Dashboard
Visualization
NE
Neptune Monitoring
Monitoring

Neptune Integrations
Integration
유사 기업

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51-200
Valuation $1.5B
232 open jobs

Haystack (deepset)
Series A
Open-source NLP framework
Berlin, Germany
51-200

Writer
Series C
Enterprise AI writing platform
San Francisco, CA
201-500
Valuation $1.9B
48 open jobs

Cerebras
Series F+
Leading company in the artificial intelligence industry
Sunnyvale, CA
201-500
Valuation $4.1B
92 open jobs

Copy.ai
Series A
AI-powered marketing copy generation
Memphis, Tennessee
51-200
뉴스 & 버즈
All
X
News
HN
YouTube
Are Book LLMs actually worth the ethical headache? Looking at alternatives
Been thinking about this a lot lately after reading about all the copyright disputes going on between publishers and AI companies. The whole "Book LLMs" situation feels like it's getting messier by the month, and I'm genuinely not sure the tradeoff is worth it anymore. Like, the bias risk from skewed source material combined with the legal exposure and the compensation debates. it just seems like there are cleaner ways to build these things. Synthetic data and open licensed datasets aren't perfe
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1개월 전
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1
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1
[P] We made GoodSeed, a pleasant ML experiment tracker
# GoodSeed v0.3.0 🎉 I and my friend are pleased to announce **GoodSeed** \- a ML experiment tracker which we are now using as a replacement for Neptune. # Key Features * **Simple and fast**: Beautiful, clean UI * **Metric plots:** Zoom-based downsampling, smoothing, relative time x axis, fullscreen mode, ... * **Monitoring plots**: GPU/CPU usage (both NVIDIA and AMD), memory consumption, GPU power usage * **Stdout/Stderr monitoring**: View your program's output online. * **Structured Configs
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1개월 전
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83
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19
What Neptune.ai Got Right (and How to Keep It)
HN
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2개월 전
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2
Show HN: Pluto – open-source Experiment Tracker for Neptune users
Hey HN! We're Roanak and Andrew from Trainy (YC S23). We build GPU infrastructure for ML teams (scheduling multi-node training jobs on Kubernetes). When Neptune announced they're shutting down, our customers didn't have a clear path forward. The alternatives exist but none of them matched the UI experience Neptune had, especially at scale. So we decided to build Pluto.<p>Pluto is an open-source experiment tracker based on our fork of MLOp. The main idea is that you can add one imp
HN
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2개월 전
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2
Setea de bani la buget reînvie proiecte vechi. Statul vrea, din nou, să intre pe piața apei îmbuteliate. Noul brand național - Știrile ProTV
Statul român a reluat un proiect mai vechi de a a-și face propriul brand de apă minerală, care se va numi Dacia. Societatea care administrează 30% din izvoarele țării are în plan deschiderea unei fabrici în Deva, cel puțin pentru început.
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2개월 전
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11
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30
더 보기 (15개 남음)
총 조회수
2
총 지원 클릭 수
0
모의 지원자 수
0
스크랩
0
리뷰
3.6
10개 리뷰
워라밸
3.8
보상
2.5
문화
3.2
커리어
2.8
경영진
2.3
65%
친구에게 추천
장점
Flexible working hours
Good team culture and collaboration
Comprehensive benefits
단점
Below average compensation
Limited career advancement
Poor management communication
연봉 정보
0개 데이터
Intern
Intern
0개 리포트
$107,063
총 연봉
기본급
-
주식
-
$91,035
$123,090
면접 경험
36개 면접
난이도
4.0
/ 5
소요 기간
3-6w
합격률
23%
경험
긍정 65%
보통 20%
부정 15%
면접 과정
1
Recruiter Screen
2
ML Coding
3
ML System Design
4
Research Discussion
5
Team Interviews
연락처 및 위치