Machine Learning Engineer
At a glance
Mid-level Machine Learning Engineering role at Julius Baer Technology. Singapore · full-time.
Pay not stated Machine Learning Engineer salary
aimlroles summary, based on the employer's posting.
What you'll do
- Build, launch and refine machine learning solutions for complex business problems, taking them from early design through deployment
- Create multi-agent systems and give AI models ways to call tools and functions
- Ground AI responses in company data by designing and implementing retrieval-augmented generation systems
- Test prompts and examples, assess model performance, and tune AI agents and workflows for production
- Connect ML solutions to existing systems with platform teams, data engineers and data scientists; review code and debug issues
What you bring
- A bachelor's or master's degree in data science, computer science, mathematics, statistics or a related field
- Strong Python skills, including experience with machine learning libraries and TensorFlow or PyTorch
- Hands-on work with large language models, plus a solid grasp of AI agents, orchestration frameworks and reasoning approaches
- Relevant experience in machine learning, data science or a related area
Who this fits
This role suits a mid-level machine learning engineer who can work across the ML lifecycle and collaborate with technical and business stakeholders. You'll need to manage priorities and deadlines, communicate clearly, and keep your ML and AI knowledge current. The position is based in Singapore.
From the employer
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.
GENERAL DESCRIPTIONWe 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
KEY FEATURES and accountabilities
Key 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 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
Regulatory Responsibilities &/OR Risk Management
- Demonstration of appropriate values and behaviours including but not limited to standards on honesty and integrity, due care and diligence, fair dealing (treating customers fairly), management of conflicts of interest, competence and continuous development, adequate risk management, and compliance with applicable laws and regulations.
YOUR PROFILE
SKILLS REQUIREMENTS
Personal and Social
- 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
Professional and Technical
- 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 pre-processing, 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
We are looking forward to receiving your full job application through our online application tool. Further interesting job opportunities can be found on our Career site.
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