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We’re seeking a hands-on Generative AI Analyst with a background in Software, Data, or Machine Learning Engineering.
You’ll design, build, and deploy generative-AI-driven solutions focused on real-world applications (i.e., no research-only roles).
You’ll work closely with engineering teams to implement practical AI capabilities using LLMs and RAG setups.
Job type: Remote
Key Responsibilities
You’ll design, build, and deploy generative-AI-driven solutions focused on real-world applications (i.e., no research-only roles).
You’ll work closely with engineering teams to implement practical AI capabilities using LLMs and RAG setups.
Job type: Remote
Key Responsibilities
- Model Customization & RAG: Implement retrieval-augmented generation techniques to customize LLMs for practical business use.
- API & Platform Integration: Use AWS Bedrock, OpenAI or similar APIs to embed generative AI into existing systems.
- Applied Solution Development: Build AI-powered tools to enhance operational efficiency, decision-support systems, or customer workflows in industry settings.
- Data Prep & Collaboration: Work with data engineering to preprocess and manage data for model inputs, ensuring security and compliance.
- Performance Tuning & Production Deployment: Monitor and refine LLM deployments in scalable, reliable environments.
- Cross-Functional Partnership: Collaborate with software engineers, product managers, and stakeholders to deliver AI solutions that meet real needs.
- Documentation & Communication: Create clear documentation and explain technical concepts to both technical and non-technical audiences in a hands-on context.
- Background: 1–3 years (or more) of applied experience in Software, Data, or ML Engineering (e.g., backend, data pipelines, model implementation).
- Technical Fluency: Strong Python skills and experience with ML frameworks (TensorFlow, PyTorch, scikit‑learn).
- Cloud Experience: Familiarity with AWS, GCP, or Azure integration.
- Generative AI Passion: Interest in LLMs, prompt engineering, RAG, and applied AI—demonstrated through project work or prior deployments.
- Problem-Solving & Ownership: Ability to take a project from prototype to delivery, optimizing for performance and business value.
- Soft Skills: Clear communication, cross-functional collaboration, agile mindset.
- Education: Bachelor’s or Master’s in Computer Science, Engineering, Data Science—PhD not required.
- Experience with LLM fine-tuning, prompt engineering, or LangChain/Agent frameworks.
- Familiarity with MLOps tools (e.g., MLflow, Docker, CI/CD pipelines).
- Industry-specific experience (e.g. maritime, logistics, finance) is a bonus—but we prioritize applied engineering experience over domain knowledge.
Key Skills
Ranked by relevance
ai
aws
machine learning
tensorflow
pytorch
python
docker
mlflow
mlops
cicd
gcp
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- Posted
- Jun 20, 2025
- Type
- Full-time
- Level
- Mid-Senior
- Location
- Switzerland
- Company
- Umanova SA
Industries
IT Services
IT Consulting
Categories
Business Development
Sales
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3 roles aligned with this opportunity
View Job Details
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Data Scientist
2026-07-09
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View Job Details
Related
Sales Manager
2026-07-07
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View Job Details
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Business Analyst – Employee channels & Customer interaction @ING Hubs Romania
2026-07-09
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