MLOps Engineer at Syngenta Group

pune, maharashtra, India -

Full Time

Start Date

Immediate

Expiry Date

04 Aug, 26

Salary

0.0

Posted On

06 May, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

MLOps, DevOps, ReactJS, Python, Java, Node.js, SQL, NoSQL, CI/CD, Docker, Kubernetes, MLflow, Kubeflow, AWS, Terraform, Agile/Scrum

Industry

Farming

Description

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

Responsibilities

Develop and maintain the Data Science and ML Ops Platform using full-stack proficiency and DevOps practices. Collaborate with cross-functional teams and stakeholders to deliver production-ready ML systems and AI solutions.