- Oficina en Pune
Company Description
About Syngenta
At Syngenta Group, we're a global community of 56,000 innovators across 90 countries, united by a 250-year legacy of agricultural excellence. As the world's most local agricultural technology partner, we create tailor-made solutions that transform farming while protecting our planet, driven by our commitment to innovation, ethics, and integrity. Through our inclusive environment and diverse perspectives, we pioneer breakthrough solutions for farmers, society, and future generations. Join our worldwide teams of agricultural pioneers in creating a more resilient and equitable food system for all.
Job Description
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.
Qualifications
- Bachelor’s degree in Computer Science, Software Engineering, Data Science, or related technical field
- Equivalent combination of education and professional experience considered
Additional Information
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, marital or veteran status, disability, or any other legally protected status.
#LI-Hybrid
