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.