Europe Arbeitnow ·
full-timeMachine Learning Engineer, Applied AI
Bjak · Switzerland
About There are over 5 billion users using basic applications today such email, notes, tasks, calendar and they're not AI-native. Our mission is to build proactive applications for anyone in the world, who are not used to complex prompting. We aim to bring intelligence to conversations, errands, organising and workflows, with minimal to no prompting. Our first application is an agent-first mobile communication app. We believe building applications that users use daily for communication, coordination and collaboration needs will help integrate AI into their lives. The net effect is to eliminate misinformation, achieve low coordination costs, enable high quality tasks and collaboration at scale with minimal or little prompting. Role Build and improve ML systems that power our AI-native applications. Work on classification, retrieval, ranking, personalization and evaluation, taking ownership from model development to production deployment. This role is for engineers who enjoy solving practical ML problems, improving model quality and shipping reliable systems used by real users. Focus Build and improve ML models for classification, ranking, retrieval and personalization. Develop efficient classifiers and optimize model accuracy, precision, latency and cost. Improve search relevance and context retrieval using embeddings, hybrid search and reranking. Build personalization models that learn from user behavior while respecting privacy. Develop evaluation pipelines, labeled datasets and metrics to measure model quality. Fine-tune and adapt existing models when supported by sufficient data. Build and maintain ML training, inference and deployment pipelines. Debug production issues, monitor model performance and ship improvements based on real-world feedback. Tech Stack Python PyTorch / JAX Embeddings, vector search and ranking models Production ML systems and inference pipelines Ideal Experience Strong foundations in machine learning and modern neural architectures. Hands-on experience building and deploying ML models in production. Experience in classification, ranking, retrieval, recommendation systems or personalization. Understanding of model evaluation, experimentation and performance metrics. Comfortable writing production-quality code and working with real-world datasets. Able to balance model quality, latency, cost and reliability. Strong ownership, problem-solving skills Outcomes ML models in production meet expected accuracy, relevance, latency and reliability targets. Classification and ranking improvements deliver measurable gains in model quality. Evaluation pipelines identify regressions and support reliable model releases. Training, inference and data pipelines are robust, reproducible and maintainable. Model improvements are driven by real-world feedback and measurable results. Collaborates effectively with engineering and product teams to deliver reliable ML-powered features. How We Work The best products in the world are built by small, world-class teams. We are a high-talent-density, hands-on team. We make decisions collectively and move quickly, balancing high-quality work with continuous learning. Joining our team requires the ability to bring structure, exercise judgment and execute independently. Our goal is to put a truly magical product into the hands of our users. Interview Process If there appears to be a fit, we'll reach out to schedule 3, but no more than 4 interviews. Applications are evaluated by our technical team members. Interviews will be conducted virtually and/or onsite. We value transparency and efficiency, so expect a prompt decision. If you've demonstrated the exceptional skills and mindset we're looking for, we'll extend an offer to join us. Find Jobs in Switzerland on Arbeitnow
| Role | Machine Learning Engineer, Applied AI |
|---|---|
| Company | Bjak |
| Location | Switzerland |
| Type | full-time |
| Compensation | Not disclosed |
| Deadline | Rolling |
Typical process for this type of role
A general guide — the exact steps for this specific listing may vary; check the original posting for details.
- 1ApplicationSubmit your resume through the apply link.
- 2ScreeningRecruiter reviews your background against the role.
- 3AssessmentA technical test, assignment, or coding round, depending on the role.
- 4Interview(s)One or more rounds with the hiring team.
- 5OfferOffer letter with compensation and start date.
Before you apply
0/4More at Bjak
Other jobs at Bjak
- Digital Marketing Manager · United Kingdom
- Head Of Finance · United Kingdom
- Brand And Content Manager · United Kingdom
- Growth Marketing Manager · United Kingdom
- Chief Technology Officer · United Kingdom
Explore Related Placements
// similar opportunities
You might also like
Machine Learning Engineer
Senior Software Engineer (typescript / Backend) - AI/ML
Recognised on the 2025 Forbes Cloud 100 list, ClickHouse is one of the most innovative and fast-growing private cloud companies. With more than 3,000 customers ...
Machine Learning Engineer
Deepjudge
About us: Founded by former Google search engineers with PhDs in AI from ETH Zurich, DeepJudge helps legal teams unlock and apply the knowledge inside their org...
Machine Learning Engineer
Grahamcapitalmanagement
Graham Capital Management, L.P. (collectively with its affiliates, "Graham") is an alternative investment manager founded in 1994 by Kenneth G. Tropin. Speciali...
Machine Learning Engineer
Scarlet
We pull medical technology from the future to solve human health. Scarlet is authorised to assess and certify medical devices. We combine clinical, technical an...
Machine Learning Engineer
Faculty
Why Faculty? We established Faculty in 2014 because we thought that AI would be the most important technology of our time. Since then, we’ve worked with over 35...
Machine Learning Engineer
Optimove
At Optimove, we believe people are capable of more than a single job description. You’re not hired just to fill a position- you’re empowered to shape it, grow i...