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Senior Machine Learning Engineer - Tech Foundations - Global Machine Learning Platform(m/w/x)
Designing and maintaining scalable ML infrastructure for a global delivery platform. 5+ years of software or ML engineering experience required. 27 days holiday, with extra days on 2nd and 3rd year.
Requirements
- 5+ years Software Engineering, ML Engineering, MLOps, or Platform Engineering experience
- High-quality, maintainable code in Python or Golang
- Designing and building complex applications and distributed systems
- Software Design, Microservices, and Cloud Architecture Best Practices
- Containerization and orchestration tools (Docker, Kubernetes, Helm)
- CI/CD pipelines
- Infrastructure as Code (Terraform or equivalent)
- ML engineering ecosystem familiarity
- ML tools (Metaflow, MLflow, Argo Workflows, Jupyter Notebooks)
- Serving Frameworks (Triton)
- Public cloud platforms (Google Cloud and AWS)
- Technical deep-dives, investigations, debugging, and RCA
- Technical explorations and solution proposals
- Exceptional written and verbal English communication
- Contributing to and influencing architectural reviews and strategy
- English language proficiency
Tasks
- Define long-term technical vision and roadmap
- Lead design and maintenance of scalable ML infrastructure
- Manage entire ML lifecycle at scale
- Translate pain points into platform features
- Champion and implement new technologies
- Build highly available, secure systems
- Optimize performance, security, and efficiency
- Leverage modern cloud infrastructure
- Use Infrastructure as Code and container orchestration
- Define and enforce engineering best practices
- Write and share technical documents and RFCs
- Mentor junior and mid-level engineers
- Ensure code quality and consistency
- Promote team-wide technical excellence
Work Experience
- 5 years
Education
- Bachelor's degreeOR
- Master's degree
Languages
- English – Native
Tools & Technologies
- Python
- Golang
- GitOps
- MLOps
- DevOps
- Docker
- Kubernetes
- Helm
- Terraform
- Metaflow
- MLflow
- Argo Workflows
- Jupyter Notebooks
- Triton
- Google Cloud
- AWS
Benefits
More Vacation Days
- 27 days holiday
- Extra holiday day on 2nd year of service
- Extra holiday day on 3rd year of service
Additional Allowances
- 1000 EUR Educational Budget
- Digital meal vouchers
- Food vouchers
Learning & Development
- Language courses
- Udemy Business platform access
Family Support
- Parental support
Healthcare & Fitness
- Health checkups
- Yoga
- Gym subsidy
Mental Health Support
- Meditation
Company Bike
- Bicycle subsidy
Competitive Pay
- Employee Share Purchase Plan
Workation & Sabbatical
- Sabbatical bank
Public Transport Subsidies
- Public transportation ticket discount
Other Benefits
- Life insurance
- Accident insurance
Retirement Plans
- Corporate pension plan
Corporate Discounts
- Corporate discounts
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Senior Machine Learning Engineer - Tech Foundations - Global Machine Learning Platform(m/w/x)
Designing and maintaining scalable ML infrastructure for a global delivery platform. 5+ years of software or ML engineering experience required. 27 days holiday, with extra days on 2nd and 3rd year.
Requirements
- 5+ years Software Engineering, ML Engineering, MLOps, or Platform Engineering experience
- High-quality, maintainable code in Python or Golang
- Designing and building complex applications and distributed systems
- Software Design, Microservices, and Cloud Architecture Best Practices
- Containerization and orchestration tools (Docker, Kubernetes, Helm)
- CI/CD pipelines
- Infrastructure as Code (Terraform or equivalent)
- ML engineering ecosystem familiarity
- ML tools (Metaflow, MLflow, Argo Workflows, Jupyter Notebooks)
- Serving Frameworks (Triton)
- Public cloud platforms (Google Cloud and AWS)
- Technical deep-dives, investigations, debugging, and RCA
- Technical explorations and solution proposals
- Exceptional written and verbal English communication
- Contributing to and influencing architectural reviews and strategy
- English language proficiency
Tasks
- Define long-term technical vision and roadmap
- Lead design and maintenance of scalable ML infrastructure
- Manage entire ML lifecycle at scale
- Translate pain points into platform features
- Champion and implement new technologies
- Build highly available, secure systems
- Optimize performance, security, and efficiency
- Leverage modern cloud infrastructure
- Use Infrastructure as Code and container orchestration
- Define and enforce engineering best practices
- Write and share technical documents and RFCs
- Mentor junior and mid-level engineers
- Ensure code quality and consistency
- Promote team-wide technical excellence
Work Experience
- 5 years
Education
- Bachelor's degreeOR
- Master's degree
Languages
- English – Native
Tools & Technologies
- Python
- Golang
- GitOps
- MLOps
- DevOps
- Docker
- Kubernetes
- Helm
- Terraform
- Metaflow
- MLflow
- Argo Workflows
- Jupyter Notebooks
- Triton
- Google Cloud
- AWS
Benefits
More Vacation Days
- 27 days holiday
- Extra holiday day on 2nd year of service
- Extra holiday day on 3rd year of service
Additional Allowances
- 1000 EUR Educational Budget
- Digital meal vouchers
- Food vouchers
Learning & Development
- Language courses
- Udemy Business platform access
Family Support
- Parental support
Healthcare & Fitness
- Health checkups
- Yoga
- Gym subsidy
Mental Health Support
- Meditation
Company Bike
- Bicycle subsidy
Competitive Pay
- Employee Share Purchase Plan
Workation & Sabbatical
- Sabbatical bank
Public Transport Subsidies
- Public transportation ticket discount
Other Benefits
- Life insurance
- Accident insurance
Retirement Plans
- Corporate pension plan
Corporate Discounts
- Corporate discounts
Like this job?
BetaYour Career Agent finds similar jobs for you every day.
About the Company
Delivery Hero
Industry
Other
Description
The company is a pioneering local delivery platform operating in over 70 countries, focused on delivering an amazing experience.
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