Machine Learning Engineer 100% (f/m/d)

Julius Baer

Madrid

On-site

EUR 60,000 - 110,000

Full time

15 hours ago
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Job summary

Julius Baer in Madrid is seeking a skilled machine learning engineer (ML Eng) to join an agile development team within our ML & AI ART. You will design, build, and maintain robust, scalable AI solutions in a DevOps environment, collaborating across data engineers, data scientists, and platform teams to deliver high-quality digital solutions.

You will work across the full lifecycle from concept to deployment, create multi-agent systems with function/tool-calling capabilities, ground AI responses

Qualifications

  • Bachelor's or Master's degree in Data Science, Computer Science, Mathematics, Statistics, or a related field.
  • Strong programming skills in Python with experience in machine learning libraries and deep learning frameworks such as TensorFlow or PyTorch.
  • Proven experience working with Large Language Models (LLMs).
  • Good understanding of AI agents, agentic workflows, LLM orchestration frameworks and reasoning patterns.
  • Experience with data preprocessing, feature engineering, and model selection and evaluation techniques.
  • Knowledge of statistical and mathematical concepts relevant to machine learning, such as probability, linear algebra, and optimization.
  • Understanding software development best practices, including version control, testing, and documentation.

Responsibilities

  • Develop, deploy, and optimize machine learning and AI solutions that address complex business challenges.
  • Create multi-agent systems and equip AI models with function/tool-calling capabilities.
  • Design and implement RAG systems to ground AI responses in enterprise data.
  • Assess and integrate AI models (e.g. LLMs) ensuring optimal performance and reliability.
  • Optimize agentic workflows and AI agents for production use cases.
  • Testing and optimizing system prompts and few-shot examples to ensure accurate , consistent, and safe AI outputs.
  • Performance evaluation of machine learning and AI models using appropriate metrics, evaluation sets and techniques.
  • Collaborate with platform teams, data engineers, data scientists, and other stakeholders to integrate machine learning solutions into existing systems and processes.
  • Participate in code reviews, testing, and debugging to ensure the quality and reliability of machine learning solutions.

Skills

Python programming
ML libraries & DL frameworks
LLMs experience
AI agents & agentic workflows
Data preprocessing & feature eng
Statistics & linear algebra
Software development practices
Problem solving & debugging

Education

Bachelor's or Master's in Data Science/CS/Math/Stats

Tools

TensorFlow
PyTorch
LLM orchestration frameworks

Job description

At Julius Baer, we celebrate and value the individual qualities you bring, enabling you to be impactful, to be entrepreneurial, to be empowered, and to create value beyond wealth. Let’s shape the future of wealth management together.

We are seeking a skilled machine learning engineer (ML Eng) to join one of our agile development teams in our ML & AI ART. In this role, you will play a key part in designing, building, and maintaining robust, scalable AI solutions within a DevOps environment. You'll contribute across the entire lifecycle - from concept to deployment - and collaborate closely with cross-functional teams to deliver high-quality digital solutions.

YOUR CHALLENGE
  • Develop, deploy, and optimize machine learning and AI solutions that address complex business challenges.
  • Create multi-agent systems and equip AI models with function/tool-calling capabilities
  • Design and implement RAG systems to ground AI responses in enterprise data
  • Assess and integrate AI models (e.g. LLMs) ensuring optimal performance and reliability
  • Optimize agentic workflows and AI agents for production use cases
  • Testing and optimizing system prompts and few-shot example to ensure accurate , consistent, and safe AI outputs
  • Performance evaluation of machine learning and AI models using appropriate metrics, evaluation sets and techniques, and continuously iterate and improve upon them
  • Collaborate with platform teams, data engineers, data scientists, and other stakeholders to integrate machine learning solutions into existing systems and processes
  • Participate in code reviews, testing, and debugging to ensure the quality and reliability of machine learning solutions
YOUR PROFILE
  • Strong problem-solving and analytical skills, with the ability to think critically and creatively about complex challenges
  • Excellent communication and collaboration skills, with the ability to work effectively with cross-functional teams and stakeholders at all levels of the organization
  • Ability to manage personal workloads effectively, to prioritize tasks, manage timelines, and deliver high-quality results on schedule
  • Continuous learning mindset, with a passion for staying up-to-date with the latest advancements in machine learning and artificial intelligence
  • Attention to detail and commitment to producing high-quality, reliable, and maintainable code
  • Bachelor's or Master's degree in Data Science, Computer Science, Mathematics, Statistics, or a related field
  • Strong programming skills in Python with experience in machine learning libraries and deep learning frameworks such as TensorFlow or PyTorch
  • Proven experience working with Large Language Models (LLMs)
  • Good understanding of AI agents & agentic workflows, LLM orchestration frameworks and reasoning patterns
  • Experience with data preprocessing, feature engineering, and model selection and evaluation techniques
  • Knowledge of statistical and mathematical concepts relevant to machine learning, such as probability, linear algebra, and optimization
  • Understanding software development best practices, including version control, testing, and documentation
  • Excellent problem-solving and debugging skills, with the ability to identify and resolve issues quickly and effectively
  • Relevant work experience in machine learning, data science or a related field
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