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Neptune.ai

Neptune.ai

Neptune.ai

Leading company in the artificial intelligence industry

Machine Learning

Data Science

Model Management

Experiment Tracking

MLOps

San Francisco, California

51-200

2018年設立(8年目)

リモート

Private

累計調達額

$52M

直近ラウンド

Series B

募集中のポジション

3件のポジション

Technical Product Manager

Product

Remote in Europe

On-site

Lead

Full-time

Remote Work

フレックスタイム

ストックオプション

詳細を見る

1ヶ月前

Principal Solutions Architect

Solutions Architect

Canada

On-site

Staff

Contract

Remote Work

フレックスタイム

ストックオプション

無制限休暇

詳細を見る

1ヶ月前

Principal Solutions Architect

Solutions Architect

USA

On-site

Staff

Contract

Remote Work

フレックスタイム

ストックオプション

無制限休暇

詳細を見る

1ヶ月前

製品・サービス

Neptune Experiment Tracking

Neptune Experiment Tracking

MLOps

NE

Neptune Experiment Management

Experiment Tracking

Neptune Model Registry

Neptune Model Registry

MLOps

NE

Neptune Model Registry

Model Management

Neptune Metadata Store

Neptune Metadata Store

Data Management

NE

Neptune Metadata Store

Metadata Management

Neptune Monitoring

Neptune Monitoring

ML Monitoring

NE

Neptune Notebooks

Notebook Management

Neptune Notebooks

Neptune Notebooks

Development Tools

NE

Neptune Dashboard

Visualization

Neptune API & SDK

Neptune API & SDK

Integration

NE

Neptune API & Integrations

Integration

NE

Neptune Teams & Collaboration

Collaboration

Neptune Dashboard

Neptune Dashboard

Visualization

NE

Neptune Monitoring

Monitoring

Neptune Integrations

Neptune Integrations

Integration

ニュース&話題

All

Reddit

X

News

HN

LinkedIn

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

Reddit

·

1ヶ月前

·

1

·

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

Reddit

·

1ヶ月前

·

83

·

19

What Neptune.ai Got Right (and How to Keep It)

HN

·

2ヶ月前

·

2

Show HN: Pluto – open-source Experiment Tracker for Neptune users

Hey HN! We&#x27;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&#x27;re shutting down, our customers didn&#x27;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

·

2ヶ月前

·

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.

Reddit

·

2ヶ月前

·

11

·

30

もっと見る (残り15件)

総閲覧数

2

応募クリック数

0

模擬応募者数

0

スクラップ

0

レビュー

3.6

10件のレビュー

ワークライフバランス

3.8

報酬

2.5

企業文化

3.2

キャリア

2.8

経営陣

2.3

65%

友人に勧める

良い点

Flexible working hours

Good team culture and collaboration

Comprehensive benefits

改善点

Below average compensation

Limited career advancement

Poor management communication

給与レンジ

0件のデータ

Intern

Intern

0件のレポート

$107,063

年収総額

基本給

-

ストック

-

$91,035

$123,090

面接体験

36件の面接

難易度

4.0

/ 5

期間

3-6w

内定率

23%

体験

ポジティブ 65%

普通 20%

ネガティブ 15%

面接プロセス

1

Recruiter Screen

2

ML Coding

3

ML System Design

4

Research Discussion

5

Team Interviews

連絡先・所在地