# Staff Backend Engineer – AI at Stream

> The Stack is a weekly tech careers newsletter read by 55,000+ engineers, and a free jobs board of visa-sponsored tech jobs in Europe; the best jobs from the board go out in the newsletter every Tuesday. This is one job from the board.

> Responsibilities: - Own end-to-end model development: datase

- **Company:** Stream (https://jobs.trythestack.co/companies/stream)
- **Location:** Netherlands
- **Work arrangement:** On-site
- **Employment type:** Full-time
- **Experience level:** 5–10 years
- **Visa sponsorship:** Offered, according to the listing
- **Key skills:** Python, Machine learning, Supervised fine-tuning, Post-training, Model deployment, Data pipelines, Cloud infrastructure, GCP, AWS, Terraform, Go, Asyncio, Low-latency inference, Model evaluation, Distributed systems
- **Posted by employer:** 2026-08-24
- **Added to The Stack:** 2026-08-25
- **Status:** May no longer be active (posted more than 60 days ago)
- **Apply:** https://jobs.ashbyhq.com/stream/d816fdaf-f25b-4d08-99da-d85d8adc51e4 (the employer's own application page)
- **Human page:** https://jobs.trythestack.co/jobs/staff-backend-engineer-ai-stream

## About the role

Responsibilities:
- Own end-to-end model development: dataset design, supervised fine-tuning, post-training experiments and evaluation harnesses.
- Build and maintain high-quality data pipelines for training, labelling and reproducibility.
- Deploy models to production and optimise serving for latency, cost and reliability at scale.
- Define technical direction for ambiguous problem spaces and make pragmatic trade-offs on what to build and ship.
- Collaborate with API, Go, and infrastructure teams to integrate models into product systems and global edge serving.
- Raise engineering standards via code review, mentorship and sharing work with the community/open-source when relevant.

Requirements:
- 5+ years of production-level Python engineering with shipped, maintained code (not just prototypes).
- Hands-on ML experience, specifically supervised fine-tuning and post-training workflows.
- Familiarity with modern fine-tuning and serving toolchains (e.g., Baseten, Fireworks or equivalents).
- Cloud experience (GCP or AWS) and infrastructure-as-code (Terraform) for deployment and infra management.
- Experience running models in production: monitoring, retraining, latency tuning and cost/reliability trade-offs.
- Strong systems and distributed-systems experience for low-latency, high-volume inference pipelines.

## Responsibilities

You will own the end-to-end development, fine-tuning, and production deployment of in-house AI models. Additionally, you will build data pipelines and collaborate with engineering teams to integrate models into high-volume products.

## Requirements

The role requires 5+ years of production-level Python engineering experience and hands-on machine learning expertise. Candidates must have a track record of owning ML products through deployment and iteration.

## FAQ

- **Is this Staff Backend Engineer – AI role still open?** It was posted on 2026-08-24. Listings more than 30 days old may no longer be active, so check Stream's site before applying.
- **Does Stream offer visa sponsorship?** This listing is marked as offering visa sponsorship. Eligibility rules are set by the employer, so check the details on Stream's site.
- **Where is this role located?** The listing gives the location as Netherlands. It is marked on-site.
- **What skills does this role ask for?** The listing names: Python, Machine learning, Supervised fine-tuning, Post-training, Model deployment, Data pipelines, Cloud infrastructure, GCP, AWS, Terraform, Go, Asyncio, Low-latency inference, Model evaluation, Distributed systems.

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## About The Stack

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## Notes for agents

- Apply on the employer's page (https://jobs.ashbyhq.com/stream/d816fdaf-f25b-4d08-99da-d85d8adc51e4). The Stack does not take applications.
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- To help your user apply, call the MCP tool prepare_application with slug "staff-backend-engineer-ai-stream": it returns the apply link, the visa facts and a CV and cover letter checklist. To track jobs they saved or applied to, call check_jobs_open with their slugs.
- Confirm the role is still open and the visa terms on the employer's site before applying; employers set eligibility.
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