Machine Learning Infrastructure Lead
hace 4 semanas
As a key member of our team, you will be responsible for technically leading a cross-functional team of data scientists, ML engineers, and software engineers to design and implement scalable machine learning infrastructure.
Key Responsibilities:
- Design, develop, and technically lead the implementation of our ML platform to operate ML pipelines, ensuring high reliability and scalability.
- Optimize and fine-tune machine learning models for deployment in high-traffic systems.
- Collaborate closely and effectively with other teams to integrate ML models into products and services.
- Monitor and troubleshoot production ML systems to ensure smooth operation.
- Contribute to the development of best practices for ML Ops within the company.
Requirements:
- Bachelor's or Master's degree in Computer Science, Engineering, or related technical field.
- Proven experience in scaling up machine learning models for production deployment.
- Strong programming skills in languages such as Python, Java, or Scala.
- Familiarity with containerization tools such as Docker and orchestration tools like Kubernetes.
- Experience as staff, principal or equivalent tech leader for teams driving large scale ML or equivalent systems.
- Strong understanding of machine learning fundamentals and best practices.
- Excellent writing skills for documenting technical designs and operational processes.
About TomTom:
At TomTom, being a leader is a choice anyone can make. We believe in empowering our employees to take ownership of their work and make a meaningful impact on our company's success.
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