Software Architect - ML Ops

JOB DESCRIPTION

Software Architect -   MLOps  

The Big Picture  

Sysco LABS is the Global In-House Center of Sysco Corporation (NYSE: SYY), the world’s largest foodservice company. Sysco ranks 56th in the Fortune 500 list and is the global leader in the trillion-dollar foodservice industry .    

Sysco employs over 75,000 associates, has 337 smart distribution facilities worldwide and over 14,000 IoT-enabled trucks serving 730,000 customer locations. For fiscal year 2025 that ended June 29, 2025, the company generated sales of more than   $81.4 billion .   Sysco LABS Sri Lanka delivers the technology that powers Sysco’s end-to-end operations . 

Sysco LABS’ enterprise technology is present in the end-to-end foodservice journey, enabling the sourcing of food products, merchandising, storage and warehouse operations, order placement and pricing algorithms, the delivery of food and supplies to Sysco’s global network and the in-restaurant dining experience of the end-customer.  

For more information visit:   www.syscolabs.lk  

The Opportunity  

We are currently on the lookout for a   Software Architect -   MLOps   to join our team.   This is a senior leader   who will   be   responsible for   building, scaling, and governing the enterprise’s Machine Learning Operations ( MLOps ) capability   -   ensuring that all ML and AI models are developed, deployed, and managed in a secure, compliant, and efficient manner.    
 

This role defines the   MLOps   platform, tools, processes, and operational controls that support end-to-end model lifecycle management, from development through deployment, monitoring, and retraining.    
 
The role partners closely with Data Platform Engineering, which leads CI/CD automation and model lifecycle   governance,   and   leads the Communities of Practice (COPs) for Data Scientists and   MLOps   Engineers to ensure standardization, scalability, and innovation across the enterprise .    

Responsibilities:  

MLOps   Platform & Tools:  

• Lead ing   the strategy, design, and operation of the enterprise   MLOps   platform to support scalable ML/AI model development and deployment  

• Own ing   the evaluation, integration, and administration of   MLOps   tools (e.g., Vertex AI,   MLflow , Kubeflow,   DataRobot , custom frameworks)  

• Partner ing   with the Data Platform Engineering team to align platform integrations with enterprise CI/CD pipelines and lifecycle governance frameworks  

• Implement ing   a unified model registry, metadata store, and lineage tracking system to ensure auditability and reproducibility of ML assets  

• Driv ing   automation for model testing, deployment, monitoring, and retraining, minimizing manual intervention  

Processes & Controls for ML/AI:   

• Defin ing   and   maintain ing   standardized   MLOps   processes for model release, testing, approval, and production promotion   

• Establish ing   operational controls and guardrails for model reliability, fairness, explainability, and compliance.   

• Embed ding   AI governance policies (ethical AI, bias detection, transparency, and accountability) into   MLOps   workflows  

• Develop ing   automated frameworks for model performance monitoring, drift detection, and retraining triggers  

• Collaborat ing   with Data Management and AI Governance teams to   align on   data quality, privacy, and regulatory standards  

Governance Metrics & Reporting:    

• Defin ing   and enforc ing   MLOps   operational standards, policies, and compliance frameworks  

• Develop ing   KPIs and dashboards to measure operational performance (e.g., deployment frequency, model uptime, drift incidents, retraining efficiency)  

• Repor ting   platform health, adoption rates, and compliance performance to senior D&A leadership  

• Ensur ing   all deployed models are traceable and visible within the enterprise data catalog and governance framework  

Leadership   & Team Development:    

• Build ing   and lead ing   a specialized   MLOps   Engineering team responsible for platform development,   reliability , and enablement  

• Coach ing   and mentor ing   Data Scientists and   MLOps   Engineers on modern operational practices, automation, and performance optimization  

• Develop ing   career paths, training programs, and certification plans for   MLOps   professionals  

• Foster ing   a product-based delivery culture, emphasizing agility, scalability, and automation  

Performance Metrics:  

• Enabling r eduction s   in model deployment cycle time and manual intervention  

• Increas ing the   percentage of models   monitored   and retrained automatically  

• Improv ing   model uptime, performance, and governance compliance  

• Increasing the p latform adoption rate across Data Science teams  

• Contributing to the m aturity growth of   MLOps   and Data Science COPs  

Requirements :  

• A   Bachelor’s or   Master’s   D egree in Computer Science , Data Engineering, or   a   related field    

• 8+ years of experience in Data Science, Machine Learning Engineering, or DevOps, including 5+ years in   a leadership   capacity  

• Proven experience implementing enterprise-grade   MLOps   platforms on cloud environments (GCP, AWS, or Azure)  

• A d eep understanding of machine learning lifecycle management, CI/CD automation, and AI governance  

• Must   possess   a s trong background in cloud-native technologies (Docker, Kubernetes, Terraform, Airflow)  

• Familiarity with data governance, security, and compliance frameworks (e.g., GDPR, HIPAA, Responsible AI)  

• Demonstrated ability to lead cross-functional technical teams and drive change across large organizations  

• Excellent communication and stakeholder management skills with both technical and business leaders  

• Strategic thinker with the ability to translate complex technical concepts into business value  

• Passion for operational excellence, automation, and continuous learning  

  Benefits:   

• US dollar-linked compensation    

• Performance-based annual bonus    

• Performance rewards and recognition    

• Agile Benefits - special allowances for Health, Wellness & Academic purposes    

• Paid birthday leave   

• Team engagement allowance    

• Comprehensive Health & Life Insurance Cover - extendable to parents and in-laws    

• Overseas travel opportunities and exposure to client environments    

• Hybrid work arrangement    

Sysco LABS is an Equal Opportunity Employer.