採用
福利厚生
•Remote Work
•Flexible Hours
•Equity
必須スキル
Product Management
AI/ML Knowledge
Cross-functional Collaboration
Communication
We are seeking a Technical Product Manager with AI/ML Expertise to join our team. As a key member of the product and engineering team, you will play a crucial role in shaping the development of our AI research tools by working closely with our users (data scientists and AI researchers), identifying gaps in the market, and understanding the future of MLOps, in order to translate those needs into detailed product specifications, and managing their delivery. This position requires a deep understanding of AI/ML practices and an ability to work cross-functionally to deliver high-impact features.
Our tech stack:
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Languages: Rust, JVM (Java, Spring, Scala, Kotlin), Python.
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Data: Click House, Kafka, Elasticsearch, Redis, MySQL.
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Cloud platforms: Microsoft Azure, Google Cloud Platform (GCP).
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DevOps tools: Kubernetes, Terraform, Helm.
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Others: Protobufs, gRPC, Swagger.
Responsibilities:
As part of our team, you will be:
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Engaging with AI/ML researchers and data scientists to understand their workflows, use cases, and pain points.
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Translating domain-specific user needs into detailed, actionable product specifications for the engineering and UX teams.
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Creating and managing the product roadmap from inception to delivery, balancing innovation, user needs, and customer requirements.
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Collaborating with UX designers to ensure user needs are reflected in the design while keeping the interface polished and user-friendly.
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Driving discussions with internal stakeholders (CTO, Head of Design, Engineers) to balance technical feasibility with user requirements.
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Maintaining awareness of the competitive landscape and identifying must-have versus nice-to-have features to ensure market competitiveness.
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Leading the collaboration between cross-functional teams to align on product solutions and oversee development.
You might be a fit if you have:
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Strong AI/ML domain knowledge, including experience in model training, quality testing, and knowledge of the latest trends (e.g., reinforcement learning).
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Experience working directly with data scientists or in research environments.
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Python programming experience (a plus).
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Excellent communication skills, with the ability to engage both technical and non-technical audiences, including researchers and engineers.
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Strong problem-solving and analytical skills to address complex user challenges and translate them into product solutions.
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Proven experience in working with UX designers and engineering teams to build user-centric products.
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The ability to influence and drive initiatives within cross-functional teams without direct authority.
We offer:
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Flexibility: 100% remote work with offices (co-works) in Warsaw/Wrocław/Kraków/Poznań available and flexible working hours.
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Ownership and Impact: The opportunity to take action, shape product features, and make a significant impact on the future of AI/ML tools.
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Growth and Development: Work with cutting-edge AI/ML research teams and be part of a highly collaborative environment.
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Share in our success: Participate in the Employee Stock Option Plan and be part of our growth journey.
Any questions?
Check our ultimate guide for candidates to the neptune.ai team.
Don’t hesitate to contact our Talent Acquisition team, and check out our About us page to get to know the story and faces behind Neptune.
By applying, you consent for neptune.ai to process your personal data to assess your suitability for the role you have applied for in accordance with the General Data Protection Regulation (GDPR). Your personal data will remain confidential and shared only with authorized personnel involved in the recruitment process. You have the right to access, rectify, or delete your personal data at any time.
With your optional consent, we can retain your data for up to 12 months after the application to consider you for future suitable roles if you’re not a match for the current position.
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Neptune.aiについて

Neptune.ai
Series ANeptune.ai provides a metadata store and experiment management platform for machine learning teams to track, organize, and collaborate on ML experiments and model development.
51-200
従業員数
San Francisco
本社所在地
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 · Software Engineer
0件のレポート
$107,063
年収総額
基本給
-
ストック
-
ボーナス
-
$91,035
$123,090
面接体験
36件の面接
難易度
4.0
/ 5
期間
21-35週間
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
よくある質問
ML fundamentals
Design an ML system
Research paper discussion
Statistical concepts
ニュース&話題
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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6w ago
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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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7w ago
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83
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19
What Neptune.ai Got Right (and How to Keep It)
HN
·
9w ago
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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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10w ago
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2