Senior MLOps Engineer

• Monitor and maintain AI/ML models in production to ensure optimal performance and reliability, addressing any technical challenges that arise.
• Collaborate with development teams to understand the AI use cases and their integration into production environments.
• Design and implement scalable architectures ensuring that productionalized AI use cases are at optimal performance, scalable, accurate, and secure, adhering to ethical AI/ML practices, compliance and governance standards.
• Conduct regular assessments of AI models to identify areas for improvement. Enhance and fine-tune models to generate high-quality outputs for various applications.
• Guide team members for implementation of robust data pipelines and workflows to support data science and AI initiatives.
• Collaborate with ML engineers to establish & maintain CI/CD pipelines for model deployment, monitoring, and lifecycle management to ensure models remain reliable and efficient in production.
• Develop and maintain documentation related to AI operations, including monitoring processes, performance metrics, and governance compliance.
• Work with cross-functional teams to integrate AI models into websites, Tableau dashboards, and other applications as necessary.
• Provide support and troubleshoot issues in production environments, identifies solutions and implements resolutions swiftly.
• Partner with AI & Advanced Analytics development team in maintaining AI tools in production and monitoring for accuracy and support. Performs exploratory data analysis to identify trends, patterns, and anomalies, etc.
• Stay up to date with industry trends and emerging technologies in AI and machine learning and recommend innovative solutions to improve our operational capabilities.
• Facilitate communication and collaboration between the AI & BI Ops team and other business units to align AI initiatives with organizational goals. Provide technical guidance and mentorship to team members on AI best practices, tools, and methodologies.

• Experience: Min 8+ years of experience in data, with at least 5+ years of experience in AI, machine learning, or data science, with a focus on operationalizing AI solutions in a cloud environment.
• Programming Proficiency: Strong proficiency in programming languages such as Python, R, and SQL.
• Cloud Platforms: Experience with cloud platforms (e.g., AWS, Google Cloud, Databricks) and deploying AI models in production environments, including services like AWS (SageMaker, Redshift, Lambda, EC2/ECS), Google Cloud Platform (BigQuery, Vertex AI) and AI/ML automation tools.
• Deep Learning & ML Algorithms: Experience working with deep learning algorithms and large datasets including knowledge of generative AI models and various ML algorithms like RAGs, LLMs, NLPs, RNNs, CNNs, ARIMA, Neural Networks, etc.
• Predictive Modeling: Experience in data mining and predictive modeling inclusive of linear and non-linear regression, logistic regression, and time series analysis models.
• MLOps Tools: Hands-on experience with MLOps tools and frameworks (e.g., MLflow, Kubeflow, TensorFlow, PyTorch, Scikit-learn, VertexAI, SageMaker) for model tracking, versioning, and deployment.
• ETL Processes: Experience with ETL processes to ensure seamless data integration and preparation for AI/ML model training and deployment.
• Container Management: Skilled in Docker, Kubernetes, and other container management tools to ensure scalability and efficiency in model deployment and orchestration.
• Data Governance & Security: Familiar with data governance frameworks and security protocols, including encryption, authentication, and compliance requirements (GDPR, CPRA, etc.), especially related to the cloud-based AI solutions.

• Tableau: Familiarity with BI tools, particularly Tableau, for data visualization and dashboard integration.
• Web Scraping: Knowledge of web scraping techniques and tools for data collection.
• Industry Experience: Experience in industries such as manufacturing, agriculture, or supply chain, particularly in AI and data use cases is a plus.

• GLOBAL DIVERSITY – Diversity means many things to us, different brands, cultures, nationalities, genders, generations – even variety in our roles. You make us unique!
• ENTERPRISING SPIRIT- Every role adds value. We're committed to helping you develop and grow to realize your potential.
• POSITIVE IMPACT – Make it personal and help us feed the world.
• INNOVATIVE TECHNOLOGIES - You can combine your love for technology with manufacturing excellence – and work alongside teams of people worldwide who share your enthusiasm.
• MAKE THE MOST OF YOU – Benefits include health care and wellness plans and flexible and virtual work option……….

AGCO