Senior Machine Learning Engineer

As a scale-up company, Freeday aims to become the largest digital workforce employer in the world and unlock true human potential. We help clients with a fresh honest view, disruptive technologies, and a large dose of energy. We do this by building a team of digital employees who excel at repetitive tasks. We build this on a platform that allows us to scale these solutions easily, allowing us to deliver value fast! Thereby freeing us humans to create, collaborate and solve more complex problems and focus our attention on the more interesting and rewarding part of our work.

Freeday is seeking a Senior Machine Learning Engineer to enhance our innovative team. This role involves hands-on development and scaling of machine learning models that drive our AI-powered solutions. You will own projects from end to end, including model selection, development, deployment, and operation, ensuring they are efficient, scalable, and impactful. As a Senior Machine Learning Engineer at Freeday, you will lead the development and optimization of cutting-edge machine learning algorithms that power our automated services. You are expected to manage the full lifecycle of these models—from initial development, through rigorous testing and validation, to deployment in production environments. This role requires utilizing established MLOps frameworks to ensure models are robust, scalable, and seamlessly integrated into our services.

Responsibilities:

• Design, develop, and optimize machine learning algorithms to improve our automated services.

• Implement and oversee MLOps practices to streamline the lifecycle of model development, testing, deployment, and monitoring.

• Make strategic decisions about the use of machine learning models, evaluating whether a model is necessary and selecting the appropriate model for each use case.

• Lead and mentor a team of less experienced engineers, providing guidance and leadership to elevate their skills and understanding of machine learning applications.

• Collaborate with product and engineering teams to define project objectives, aligning machine learning projects with business goals and delivering innovative solutions.
  
  

Our Culture:

We value you as a person, a part of our A(i) team, not just for the work you do. Because we are a scale-up company, we need you to be flexible and take ownership. You feel comfortable working in an ambitious environment with people who have values such as:

• Deliver value fast and consistently

• Foster a fun and collaborative environment

• Dare to take risks and move quickly

• Prove our value to customers

• Being hungry to do the extra mile

• Build trust with others and prioritize progress

• Embrace innovation and tackle unprecedented challenges

• Respect others and thrive on helping them grow
  
  

“At Freeday we have the ambition, knowledge, and experience to do things smarter and better than others”

About Freeday:

Freeday is located in Rotterdam (within walking distance from the central station) and is a young, fast-growing IT company that helps organizations in unlocking human potential by automating repetitive tasks. Freeday has an informal, no-nonsense, and ambitious culture. Check out our LinkedIn page or visit Freeday.ai for more information!

This is what you can expect from us:

• A fast-growing and innovative work environment

• Plenty of room for new initiatives and ideas

• A driven team and no-nonsense culture

• A competitive salary, pension plan, and travel expense reimbursement

• A laptop to support your work effectively

• Opportunities for professional development to improve every day

• An incredibly friendly and inclusive atmosphere with regular social gatherings, sports events, and team activities.

Requirements:

• Proven experience as a Machine Learning Engineer or similar role, preferably within the tech sector, focusing on AI innovations.

• Strong programming skills in Python and familiarity with ML frameworks (TensorFlow, PyTorch).

• Experience with cloud technologies (AWS, Google Cloud) and comprehensive knowledge of MLOps tools (Kubeflow, MLflow).

• Ability to take full responsibility for the end-to-end implementation of machine learning projects.

• Passionate about clean energy and AI's potential to optimize workflows and reduce environmental impact.