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Challenge

Machine Learning Engineer – Generative AI & LLMs (AI Factory)

Ranking: 32

Job Description:

Key Responsibilities:

Design Phase:

  • Collaborate with multidisciplinary teams to define solution architecture.

  • Analyze technical needs and estimate scalability requirements.

  • Document low-level designs and system blueprints.

Development Phase:

  • Apply software engineering best practices in GenAI projects.

  • Implement and industrialize the full agent management layer (infrastructure, RAG, orchestration).

  • Work alongside Data Scientists, Architects, and Data teams in full product lifecycle.

  • Conduct performance testing and define measurable quality metrics .

  • Continuously improve reliability , scalability, and performance.

  • Ensure seamless integration with banking systems and infrastructure.

  • Share knowledge and best practices within the team and broader unit.

  • Generate and maintain necessary technical documentation .

Deployment & Operation Phase:

  • Validate development quality before deployment.

  • Deploy solutions across different corporate environments.

  • Monitor and maintain operational behavior and technical performance.

  • Conduct corrective and evolutionary maintenance post-deployment.

Required Education & Experience:

  • Degree in Computer Science, Telecommunications, or Engineering .

  • Minimum 3 years of experience as a Machine Learning Engineer or similar role.

  • Strong experience in Python (at least 2 years).

  • Solid understanding of application architecture and distributed computing .

  • Hands-on experience with LLM architectures and models .

  • Familiarity with CI/CD tools like GIT, Jenkins , and DevOps practices .

  • Experience in application security , microservice development , and cloud platforms (preferably AWS , certification is a plus).

  • Knowledge of columnar/vector databases .

  • Comfortable working in Agile and fast-paced environments.

Core Competencies:

  • Eagerness to learn new technologies across platform, cloud, architecture, and security.

  • Ability to thrive in dynamic, innovation-driven settings.

  • Flexible and adaptable to evolving project requirements.

  • Proactive in proposing solutions and fostering collaboration.

  • Strong analytical and abstraction skills.

  • Clear communicator, team-oriented, responsible, and committed.

  • Solid experience in Agile methodologies as a foundation for project execution.

Machine Learning Engineer – Generative AI & LLMs (AI Factory)

Ranking: 32

Job Description:

Key Responsibilities:

Design Phase:

  • Collaborate with multidisciplinary teams to define solution architecture.

  • Analyze technical needs and estimate scalability requirements.

  • Document low-level designs and system blueprints.

Development Phase:

  • Apply software engineering best practices in GenAI projects.

  • Implement and industrialize the full agent management layer (infrastructure, RAG, orchestration).

  • Work alongside Data Scientists, Architects, and Data teams in full product lifecycle.

  • Conduct performance testing and define measurable quality metrics .

  • Continuously improve reliability , scalability, and performance.

  • Ensure seamless integration with banking systems and infrastructure.

  • Share knowledge and best practices within the team and broader unit.

  • Generate and maintain necessary technical documentation .

Deployment & Operation Phase:

  • Validate development quality before deployment.

  • Deploy solutions across different corporate environments.

  • Monitor and maintain operational behavior and technical performance.

  • Conduct corrective and evolutionary maintenance post-deployment.

Required Education & Experience:

  • Degree in Computer Science, Telecommunications, or Engineering .

  • Minimum 3 years of experience as a Machine Learning Engineer or similar role.

  • Strong experience in Python (at least 2 years).

  • Solid understanding of application architecture and distributed computing .

  • Hands-on experience with LLM architectures and models .

  • Familiarity with CI/CD tools like GIT, Jenkins , and DevOps practices .

  • Experience in application security , microservice development , and cloud platforms (preferably AWS , certification is a plus).

  • Knowledge of columnar/vector databases .

  • Comfortable working in Agile and fast-paced environments.

Core Competencies:

  • Eagerness to learn new technologies across platform, cloud, architecture, and security.

  • Ability to thrive in dynamic, innovation-driven settings.

  • Flexible and adaptable to evolving project requirements.

  • Proactive in proposing solutions and fostering collaboration.

  • Strong analytical and abstraction skills.

  • Clear communicator, team-oriented, responsible, and committed.

  • Solid experience in Agile methodologies as a foundation for project execution.

About the projects you will work on

You will work 100% remotely from wherever you decide. Sometimes you may have face-to-face meetings and for that reason you have to reside in Spain or in the European Union.

You will work on projects with a leading company in digital transformation with a passion for technology and innovation in sectors such as banking (35 of the main banks worldwide work with our client), insurance, industrial and automotive in Big Data projects, Blockchain, AI, Cloud, among others.

About the client

  • Global presence in more than 15 markets
  • 8,000+ employees
  • more than 35 years of experience

About the process and your contractual relationship

If you are interested in this offer, we will enroll you in the process and submit your application, blindly, that is, without your contact details, to the technical and human resources department so that they can evaluate your profile and your financial expectations.

If the answer is positive, we organize the meetings so that the client knows you and explains the project in detail.

If after the meeting both parties agree on the conditions, you receive a firm offer to work with us or directly be hired by the client.

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GFT Cliente

Cliente

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Teba Gomez-Monche

Agencia

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Sandra Lobero

Agencia

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Paco Romero

Agencia

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claudia herrero

Agencia

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Hugo Herrero

Manager

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Víctor M. herrero

Evaluador

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