Lead ML Engineer — MLOps, CI/CD & Production-Ready

Stafide; Amsterdam; On-site; EUR 90,000 - 130,000; Full time

Benefits offered by this job

Advanced ML projects

Exposure to MLOps/CI-CD

Job summary

Stafide is seeking a senior data science and ML lead to design, develop and deploy production‑ready models. You will implement MLOps, build CI/CD pipelines for ML workflows and optimize model performance at scale.

Collaboration with data engineers, developers and business stakeholders is essential for delivering impactful data solutions. The role requires strong Python expertise, hands-on experience with ML frameworks, and a track record of deploying ML models in production across cloud

Qualifications

• 6-8 years of experience in Data Science and Machine Learning.
• Strong Python programming and development skills.
• Hands-on experience with MLOps and CI/CD pipelines.
• Experience in deploying and monitoring ML models in production.
• Knowledge of machine learning frameworks such as Scikit-learn, TensorFlow or PyTorch.
• Experience with cloud platforms, Docker, Kubernetes and Git.
• Strong understanding of model lifecycle management and automation.

Responsibilities

• Lead the design, development and deployment of machine learning models.
• Develop advanced data science solutions using Python.
• Implement and manage MLOps practices for model deployment, monitoring and lifecycle management.
• Design and maintain CI/CD pipelines for machine learning workflows.
• Optimize model performance, scalability and reliability.
• Collaborate with data engineers, developers and business stakeholders.
• Drive technical best practices and mentor team members.
• Ensure ML solutions are scalable, reliable and production-ready.

Job description

Stafide is seeking a senior data science and ML lead to design, develop and deploy production‑ready models. You will implement MLOps, build CI/CD pipelines for ML workflows and optimize model performance at scale.

Collaboration with data engineers, developers and business stakeholders is essential for delivering impactful data solutions. The role requires strong Python expertise, hands-on experience with ML frameworks, and a track record of deploying ML models in production across cloud