
Highly Skilled Machine Learning Engineer Wanted
15 hours ago
We are seeking an experienced professional to join our Data Science & AI Competency Center as a skilled Machine Learning Engineer. The ideal candidate will possess a strong understanding of ML/AI concepts, cloud architectures, and experience in implementing machine learning models into production.
">Main Responsibilities:
- Design and implement high-performing, scalable ML/AI applications in cloud environments
- Collaborate with Data Science, Data Engineering, and Cloud teams to implement Machine Learning models into production
- Develop innovative implementations of ML/AI automation for scale and efficiency
- Design, delivery, and management of industrialized processing pipelines
- Define and implement best practices in ML models life cycle and ML operations
- Implement AI/MLOps frameworks and support Data Science teams in best practices
- Gather and apply knowledge on modern techniques, tools, and frameworks in the area of ML Architecture and Operations
- Assess technical requirements and estimate planned work
- Present solutions, concepts, and results to internal and external stakeholders
- Act as Technical Lead on ML projects, defining tasks, guidelines, and evaluating results
- Create technical documentation
- Support and develop junior engineers
Requirements:
- Strong understanding of ML/AI concepts, including types of algorithms, machine learning frameworks, model efficiency metrics, and model life-cycle
- Experience in programming ML algorithms and data processing pipelines using Python
- At least 6-8 years of experience in production-ready code development
- Experience in designing and implementing data pipelines
- Practical experience with implementing ML solutions on GCP Vertex.AI and/or Databricks
- Excellent communication skills
- Ability to work in a team and support others
- Taking responsibility for tasks and deliverables
- Great problem-solving skills and critical thinking
- Fluency in written and spoken English
Nice to Have:
- Practical experience with other programming languages: PySpark, Scala, R, Java
- Practical experience with tools like AirFlow, ADF, or Kubeflow
- Good understanding of CI/CD and DevOps concepts and experience in working with selected tools (preferably GitHub Actions, GitLab, or Azure DevOps)
- Experience in applying and/or defining software engineering best practices
- Experience in productizing ML solutions using technologies like Docker/Kubernetes
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