MLOps Engineer

Role purpose

The MLOps Engineer is a developer with solid experience in systems management agile methodology and operational-ready products (DevOps). This role contributes to the development of our Data Science and ML Ops Platform applying efficient development practices with full-stack proficiency. Team collaboration and leadership potential are key success factors alongside effective stakeholder engagement and interaction with agronomists and product owners to deliver business impact.

Knowledge experience & capabilities

Experience

• 4 years of professional software development experience
• 3 years hands-on MLOps DevOps or platform engineering experience
• Demonstrated experience delivering production ML systems or data platforms
• Track record of working in cross-functional teams

Core Engineering Skills

• Strong full-stack development: ReactJS with Python Java or backends
• Proficient in SQL (PostgreSQL MySQL) and NoSQL (MongoDB DynamoDB) databases
• Solid CI/CD automation experience: Jenkins GitLab CI GitHub Actions automated testing
• RESTful API design and implementation following industry standards
• Microservices architecture and containerization with Docker/Kubernetes

MLOps & Cloud

• Hands-on experience with MLOps frameworks: MLflow Kubeflow SageMaker or similar
• AWS DS & AI Ecosystems
• AWS cloud services: EC2 S3 Lambda ECS/EKS model deployment pipelines
• Infrastructure as Code basics: Terraform or CloudFormation
• Agile/Scrum methodology with sprint delivery experience
• Experience mentoring junior engineers or leading small technical initiatives

Critical success factors & key challenges

Technical Execution

• Strong algorithm design and problem-solving capabilities
• Build and deliver Infrastructure environment and pipelines for DS ML and AI Solutions
• Support prioritization of business initiatives across complex technical landscapes

Collaboration & Communication

• Explain technical concepts clearly to non-technical stakeholders including agronomists
• Work effectively across data science engineering and business teams
• Contribute to technical documentation and knowledge sharing

Growth & Leadership

• Demonstrate problem-solving and sound decision-making skills
• Show teamwork emerging leadership abilities and mentorship potential
• Adapt quickly in dynamic environments with evolving requirements

Innovations

Employee may as part of his/her role and maybe through multifunctional teams participate in the creation and design of innovative this context Employee may contribute to inventions designs other work product including know-how copyrights software innovations solutions and other intellectual assets.

Qualifications :

• Bachelors degree in Computer Science Software Engineering Data Science or related technical field
• Equivalent combination of education and professional experience considered

Additional Information :

Note: Syngenta is an Equal Opportunity Employer and does not discriminate in recruitment hiring training promotion or any other employment practices for reasons of race color religion gender national origin age sexual orientation gender identity marital or veteran status disability or any other legally protected status. 

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Employment Type :

Full-time