AWS and MLOps SageMaker Expert
Pune, India
Syngenta Group
Company Description
Syngenta Group is one of the world’s leading sustainable agriculture innovation companies, with roots going back more than 250 years. Our 53,000 people across more than 100 countries strive every day to transform agriculture through tailor-made solutions for the benefit of farmers, society and our planet – making us the world’s most local agricultural technology and innovation partner.
Syngenta Group is committed to operating at the highest standards of ethics and integrity. This is a commitment that we are making to investors, customers, society and employees. Syngenta Group is also Committed to maintaining a workplace environment free from discrimination and harassment.
Job Description
We are seeking a proficient and knowledgeable professional to join our Data Science Platform team. The chosen candidate will be tasked with leveraging their expertise in AWS SageMaker to propel the development and deployment of machine learning models in a production environment. Furthermore, they will play a pivotal role in instituting and upholding MLOps best practices to ensure the seamless integration of machine learning models into the software development lifecycle.
Key Responsibilities:
- Design, develop, and deploy machine learning models using AWS SageMaker.
- Implement MLOps best practices to streamline the deployment and management of machine learning models.
- Collaborate with cross-functional teams to integrate machine learning solutions into the software development lifecycle.
- Optimize and fine-tune machine learning pipelines for performance and scalability.
- Remain abreast of the latest AWS SageMaker features and contribute to the continuous improvement of our machine learning infrastructure.
Qualifications
We are looking for 6-10 years of experience for this role.
Proven experience in designing, developing, and deploying machine learning models using AWS SageMaker.
- In-depth knowledge of MLOps best practices and their implementation in a production environment.
- Strong collaboration and communication skills to work effectively with cross-functional teams.
- Proficiency in optimizing and fine-tuning machine learning pipelines for performance and scalability.
- Demonstrated ability to stay updated with the latest AWS SageMaker features and contribute to the enhancement of machine learning infrastructure.
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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* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: AWS Machine Learning ML infrastructure ML models MLOps Pipelines SageMaker
Perks/benefits: Career development
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