At a Glance
- Tasks: Transform AI research into scalable solutions and build robust data pipelines.
- Company: Join a forward-thinking tech company at the forefront of AI innovation.
- Benefits: Enjoy competitive pay, flexible work options, and opportunities for growth.
- Other info: Be part of a dynamic team with endless learning opportunities.
- Why this job: Make a real impact by developing cutting-edge AI systems that change the game.
- Qualifications: Experience in machine learning and strong problem-solving skills required.
The predicted salary is between 60000 - 80000 € per year.
We are looking for a Machine Learning Engineer who excels at turning AI research into scalable, production-grade reality. You will be responsible for the 'heavy lifting' building the frameworks that allow our AI models to reason, the pipelines that feed them, and the infrastructure that ensures they are fast, ethical, and cost-efficient. You will bridge the gap between Data Science prototypes and enterprise-scale deployment.
Key Responsibilities
- AI Model design and build: Work closely with data scientists and business to design and implement AI algorithms, frameworks and architectures.
- AI model Data Preprocessing: Design, build, and maintain robust ETL/ELT pipelines to ingest, transform, and load data from various sources.
- AI model Feature Engineering: Integrate structured and unstructured data from internal and external systems into centralized data platforms.
- Performance Tuning of AI models: Optimize data workflows and queries for performance, scalability, and cost-efficiency.
- Building Agentic Systems: Developing intelligent AI agents that can reason, plan, and execute tasks autonomously using LLMs and other tools.
- LLM application Development: LLM fine-tuning adapting pretrained LLMs for specific tasks using techniques like parameter-efficient fine-tuning (PEFT) (e.g., LoRA, QLoRA).
ML Engineer employer: Randstad Digital
Join a forward-thinking company that prioritises innovation and collaboration, where as a Machine Learning Engineer, you will have the opportunity to work on cutting-edge AI technologies in a dynamic and inclusive environment. We offer competitive benefits, a strong focus on employee development, and a culture that encourages creativity and teamwork, all set in a vibrant location that fosters both professional and personal growth.
StudySmarter Expert Advice🤫
We think this is how you could land ML Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with other ML enthusiasts. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving AI models and pipelines. This is your chance to demonstrate your expertise and make a lasting impression on potential employers.
✨Tip Number 3
Prepare for technical interviews by brushing up on your algorithms and data structures. Practice coding challenges that focus on ML concepts, as this will help you feel more confident when it’s time to showcase your skills.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented ML Engineers, and applying directly can give you a better chance of landing that dream job. Plus, it shows your enthusiasm for joining our team!
We think you need these skills to ace ML Engineer
Some tips for your application 🫡
Show Your Passion for AI:When you're writing your application, let your enthusiasm for AI and machine learning shine through. We want to see how excited you are about turning research into real-world applications, so share any relevant projects or experiences that highlight your passion!
Tailor Your CV and Cover Letter:Make sure to customise your CV and cover letter for the ML Engineer role. Highlight your experience with AI model design, data preprocessing, and performance tuning. We love seeing how your skills align with our needs, so don’t hold back!
Be Clear and Concise:Keep your application clear and to the point. We appreciate well-structured documents that make it easy for us to see your qualifications. Use bullet points where possible and avoid jargon unless it's relevant to the role.
Apply Through Our Website:Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re keen on joining the StudySmarter team!
How to prepare for a job interview at Randstad Digital
✨Know Your AI Models
Make sure you brush up on the latest AI models and frameworks relevant to the role. Be ready to discuss how you've implemented these in past projects, especially focusing on any challenges you faced and how you overcame them.
✨Showcase Your Data Pipeline Skills
Prepare to talk about your experience with ETL/ELT processes. Have specific examples ready that demonstrate your ability to design and maintain robust data pipelines, as well as how you’ve optimised them for performance and cost-efficiency.
✨Feature Engineering is Key
Be ready to discuss your approach to feature engineering. Highlight any innovative techniques you've used to integrate structured and unstructured data, and how this has impacted the performance of your AI models.
✨Performance Tuning Know-How
Expect questions on performance tuning of AI models. Prepare to share your strategies for optimising data workflows and queries, and be specific about the tools and methods you've employed to achieve scalability and efficiency.
