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Senior AL/ML Engineer

Scalera AG · Zürich · Full time · Hybrid

About this role

Scalera AG is looking for a Senior AI/ML Engineer to own end‑to‑end machine‑learning models for its construction‑industry platform. The role involves building, fine‑tuning, serving and evaluating embedding, retrieval and LLM models on real customer data. It suits candidates with a proven track record of shipping production ML systems and direct customer interaction.

Key details

• Location: Zürich
• Work mode: Hybrid
• Pay: CHF 100'000 - 120'000 per year
• Level: Senior

What you'll do

• Own the ML pipeline from data collection, training, fine‑tuning to production serving.
• Develop document‑understanding models that extract structure, quantities and specs from tenders and catalogs.
• Build product‑matching retrieval and LLM agents for tender‑to‑product alignment.
• Design and maintain automated retraining pipelines, GPU serving and vector‑search infrastructure.
• Conduct offline benchmarks, per‑customer evaluations and gating to ensure model quality before release.
• Investigate and resolve model errors reported by customers.

What you'll need

Must have

• Experience taking a model from zero to production (embeddings, retrieval or document models).
• Hands‑on training and fine‑tuning of models, preferably embeddings, rerankers, classifiers or LLMs.
• Strong Python programming skills.
• Practical knowledge of Docker, CI/CD and cloud platforms (GCP, AWS or Azure).
• Ability to measure model performance with rigorous evaluation beyond a single aggregate score.
• Willingness to interact directly with customers and handle ambiguous, evolving requirements.

Nice to have

• Experience building LLM‑based agents in production.
• Fluent German (not required).
• Background as a founder, first ML engineer, or shipping paid‑for models.

Tech stack

AI, AWS, Azure, CI/CD, Cloud, CTO, Docker, Embedding Models, ERP, Fine-tuning, GCP, LLM, Model Serving, Python, Agentic AI, Langfuse, PostgreSQL

What's on offer

• Competitive salary
• Meaningful equity
• Occasional customer visits in Switzerland, Austria and Germany
• Direct work with CEO, CTO, VP Engineering and Customer Success

How to stand out for this role

Likely interview topics

• Describe a full‑cycle ML project you built, focusing on data preparation, model selection, fine‑tuning and production deployment.
• Explain how you set up automated retraining pipelines and monitoring to prevent regressions.
• Discuss strategies you used to evaluate document‑understanding models on real‑world tender data.
• Show how you integrated Docker/CI‑CD with a cloud provider (GCP, AWS or Azure) for model serving.
• Illustrate a situation where you worked directly with a customer to diagnose and fix a model error.

Keywords to mirror in your CV

embedding models, Docker, CI/CD, GCP, AWS, Azure, Python

What to show

• A case study of an end‑to‑end document‑understanding system that extracts structured data from PDFs or scanned tenders.
• A demo of a retrieval‑augmented generation or LLM agent that matches product listings to textual queries, deployed on a cloud GPU instance.
• An automated retraining workflow with CI/CD integration that triggers model updates and runs evaluation benchmarks before deployment.

How to apply

Use the Apply button on this page to submit your application.

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Source: Adzuna