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 billionSysco 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 -MLOpsto join our team.This is a senior leaderwho willberesponsible forbuilding, 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 theMLOpsplatform, 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 lifecyclegovernance,andleads the Communities of Practice (COPs) for Data Scientists andMLOpsEngineers to ensure standardization, scalability, and innovation across the enterprise

Responsibilities:

MLOpsPlatform & Tools:

• Leadingthe strategy, design, and operation of the enterpriseMLOpsplatform to support scalable ML/AI model development and deployment

• Owningthe evaluation, integration, and administration ofMLOpstools (e.g., Vertex AI,MLflow, Kubeflow,DataRobot, custom frameworks)

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

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

• Drivingautomation for model testing, deployment, monitoring, and retraining, minimizing manual intervention

Processes & Controls for ML/AI:

• DefiningandmaintainingstandardizedMLOpsprocesses for model release, testing, approval, and production promotion

• Establishingoperational controls and guardrails for model reliability, fairness, explainability, and compliance.

• EmbeddingAI governance policies (ethical AI, bias detection, transparency, and accountability) intoMLOpsworkflows

• Developingautomated frameworks for model performance monitoring, drift detection, and retraining triggers

• Collaboratingwith Data Management and AI Governance teams toalign ondata quality, privacy, and regulatory standards

Governance Metrics & Reporting:

• Definingand enforcingMLOpsoperational standards, policies, and compliance frameworks

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

• Reportingplatform health, adoption rates, and compliance performance to senior D&A leadership

• Ensuringall deployed models are traceable and visible within the enterprise data catalog and governance framework

Leadership& Team Development:

• Buildingand leadinga specializedMLOpsEngineering team responsible for platform development,reliability, and enablement

• Coachingand mentoringData Scientists andMLOpsEngineers on modern operational practices, automation, and performance optimization

• Developingcareer paths, training programs, and certification plans forMLOpsprofessionals

• Fosteringa product-based delivery culture, emphasizing agility, scalability, and automation

Performance Metrics:

• Enabling reductionsin model deployment cycle time and manual intervention

• Increasing thepercentage of modelsmonitoredand retrained automatically

• Improvingmodel uptime, performance, and governance compliance

• Increasing the platform adoption rate across Data Science teams

• Contributing to the maturity growth ofMLOpsand Data Science COPs

Requirements

• ABachelor’s orMaster’sDegree in Computer Science, Data Engineering, orarelated field

• 8+ years of experience in Data Science, Machine Learning Engineering, or DevOps, including 5+ years ina leadershipcapacity

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

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

• Mustpossessa strong 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.