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 Node.js 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 solutions. In this context, Employee may contribute to inventions, designs, other work product, including know-how, copyrights, software, innovations, solutions, and other intellectual assets.

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

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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