Senior ML Engineer (Agentic Search)

pofft Technology Inc.; Amsterdam; À distance; EUR 140 000 - 200 000; Plein temps

Avantages offerts par ce poste

Competitive compensation

Career growth and learning

Flexibility and ownership

Collaborative and innovative culture

Work on impactful AI projects

International environment and talented

Résumé du poste

Nebyus is seeking a Senior ML Engineer to join a fast-growing team building an agent-native search platform for AI systems. You will train and deploy models for retrieval, ranking, and indexing at scale, enabling real-time access to fresh information.

You will work on data selection, crawling, and content understanding, and help maintain end-to-end training pipelines, experiment tracking, and model lifecycle in production. This role offers a remote arrangement with international collaboration.

Qualifications

• 5+ years of experience in software engineering or applied machine learning.
• Strong programming skills in Python and at least one of Go or C++.
• Proven experience deploying ML models in production systems.
• Solid understanding of machine learning and modern deep learning, including transformers and embeddings.
• Experience building data or ML pipelines and working with workflow orchestration.
• Ability to define meaningful model metrics and evaluate models rigorously.
• Product-oriented mindset with a focus on impact and iteration.

Responsabilités

• Train and deploy ML models for retrieval, reranking, and search relevance, such as embedding models and cross-encoders, in production
• Develop models supporting crawling, data selection, and content understanding
• Build and maintain the data, training and evaluation pipelines behind our models: training-data generation, evaluation sets and retraining
• Contribute to and improve our ML platform: training and orchestration workflows (Kubernetes, GPU scheduling, experiment tracking, model lifecycle) and inference optimisation for low-latency serving
• Work closely with engineering to integrate and deploy ML models in production services, balancing latency, quality and cost
• Apply the latest architectural advances and training procedures for retrieval and LLM-integrated systems

Connaissances

Python

Go

C++

ML in production

Data pipelines

Model evaluation

Transformers

Product mindset

Outils

Kubernetes

GPU scheduling

Experiment tracking

Model lifecycle

Description du poste

Senior ML Engineer (Agentic Search) Remote 1 gün 22 saat 34 dakika önce yayınlandı. Jobicy -

About Nebius:

Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure.

Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI.

Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D.

We are seeking a Senior ML Engineer to join a fast-growing team building an agent-native search platform for AI systems, the emerging web access layer for AI. Our focus is agentic search, where AI systems plan, retrieve and refine rather than just return results.

You will develop and deploy machine learning models that power retrieval, ranking, and indexing at scale, helping AI systems access fresh, reliable information in real time.

This is a high-impact role working on a production system used 24×7, operating at the scale of web search.

Your responsibilities:

Train and deploy ML models for retrieval, reranking, and search relevance, such as embedding models and cross-encoders, in production

Develop models supporting crawling, data selection, and content understanding

Build and maintain the data, training and evaluation pipelines behind our models: training-data generation, evaluation sets and retraining

Contribute to and improve our ML platform: training and orchestration workflows (Kubernetes, GPU scheduling, experiment tracking, model lifecycle) and inference optimisation for low-latency serving

Work closely with engineering to integrate and deploy ML models in production services, balancing latency, quality and cost

Apply the latest architectural advances and training procedures for retrieval and LLM-integrated systems

Must-haves:

5+ years of experience in software engineering or applied machine learning

Strong programming skills in Python and at least one of Go or C++

Proven experience deploying ML models in production systems

Solid understanding of machine learning and modern deep learning, including transformers and embeddings

Experience building data or ML pipelines and working with workflow orchestration

Ability to define meaningful model metrics and evaluate models rigorously

Product-oriented mindset with a focus on impact and iteration

Nice-to-haves:

Hands-on experience with retrieval, ranking, or recommendation

Experience with Kubernetes, distributed training or GPU scheduling, or inference optimisation (batching, quantisation, compilation)

Contributions to open-source projects, technical publications, or conference talks

Strong results on public benchmarks or leaderboards (e.g. MTEB, BEIR) or models released on Hugging Face

• Competitive compensation
• Career growth and learning opportunities
• Flexibility and ownership
• Collaborative and innovative culture
• Opportunity to work on impactful AI projects
• International environment and talented teams

What’s it like to work at Nebius:

...

Payment Type

-

Price Range

-

Work Type

-

Location

Remote

Source

Jobicy