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Open nowPosted 71 days ago

Freelance Mid-Level AI Engineer

Umanova SA2 open roles

Where
Geneva or/and remote, Europe and/or remote, CH
Work mode
Remote
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Your applicationOpen nowFreelance Mid-Level AI EngineerUmanova SA · Geneva or/and remote, Europe and/or remote, CH

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

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The clock on this job

Early applications get read.

12.8% of postings close within 7 days. Measured by our own scanner across the market. Umanova SA postings stay open a median of 7 days.

Share of postings closed within
  1. 2.2%1 day
  2. 4.5%3 days
  3. 12.8%7 days
  4. 20.6%14 days
  5. 35.6%30 days
  6. 58.4%60 days
This job: posted 71 days ago

Umanova SA median: 7 days open

The posting

We are looking for a remote Mid-Level AI Engineer with hands-on experience building and deploying Generative AI solutions.

📍 Remote within Europe.

This is an engineering role focused on developing production-ready applications using Large Language Models (LLMs), RAG, and cloud AI platforms such as AWS Bedrock or OpenAI APIs. This is not a research-focused position.

Before you apply, please ensure you meet the following minimum requirements:

  • Professional experience developing applications in Python.
  • Hands-on experience building or deploying LLM-based applications.
  • Experience with RAG, OpenAI/AWS Bedrock APIs, or similar GenAI frameworks.
  • Experience integrating AI solutions into production or business applications.
  • Strong English communication skills.

Key Accountabilities

  • 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.

Qualifications Minimum Qualifications

  • 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.

Pluses (Nice to Have)

  • 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.

We are looking forward to your application.

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