Role Overview
Cognizant is seeking an experienced MLOps Architect (Snowflake) to design, build, and operationalize enterprise machine learning platforms utilizing Snowflake's native AI and ML capabilities.
In this strategic and hands-on role, you will own the end-to-end machine learning lifecycle across Snowflake, from feature engineering and model development through deployment, monitoring, governance, and optimization. You will collaborate with Data Scientists, Data Engineers, Platform Teams, Security Organizations, and Business Stakeholders to deliver scalable, secure, and production-ready AI solutions.
The ideal candidate brings deep expertise in Snowflake ML technologies, MLOps architecture, AI platform engineering, and cloud-native modernization.
Work Model
This position follows a hybrid work model based in Boston, Massachusetts. Team members are expected to work onsite and remotely based on business and client requirements.
Occasional travel may be required for stakeholder meetings, architecture reviews, planning workshops, and strategic transformation initiatives.
Key Responsibilities
Architecture & Platform Design
- Design and implement end-to-end MLOps architectures leveraging:
- Snowpark
- Snowflake ML
- Snowflake Model Registry
- Snowflake Feature Store
- Snowflake Container Runtime
- Snowpark Container Services (SPCS)
- Define scalable reference architectures supporting:
- Batch Inference
- Real-Time Inference
- Near Real-Time Inference
- Establish best practices for compute optimization, warehouse sizing, GPU resource allocation, and cost management.
- Design enterprise patterns utilizing:
- Cortex AI Functions
- Cortex Agents
- Cortex Search
- Cortex Analyst
ML Lifecycle Management & Automation
- Build and optimize CI/CD/CT pipelines supporting model development, validation, deployment, and governance.
- Implement automated ML workflows using:
- GitHub Actions
- Azure DevOps
- GitLab
- Jenkins
- Snowflake CLI
- Git Integration
- Establish standards for:
- Experiment Tracking
- Model Versioning
- Promotion Workflows
- Release Governance
- Design and implement orchestration solutions utilizing:
- Snowflake Tasks
- Task Graphs
- Dynamic Tables
- Streams
- dbt
- Apache Airflow
- Standardize Feature Store architecture including:
- Feature Views
- Entities
- Training Datasets
- Online Features
- Point-in-Time Data Consistency
Model Deployment & Monitoring
- Deploy machine learning models through warehouse-based inference functions and Snowpark Container Services.
- Develop monitoring strategies utilizing:
- Snowflake ML Observability
- Data Metric Functions
- Model Performance Monitoring
- Drift Detection
- Build A/B testing frameworks and champion/challenger deployment strategies.
- Define rollback and recovery processes to minimize operational risk.
- Monitor model accuracy, latency, reliability, and business impact metrics.
Governance, Security & Compliance
- Design governance frameworks leveraging:
- Role-Based Access Control (RBAC)
- Data Masking
- Row-Level Security
- Data Tagging
- Lineage Management
- Ensure compliance with:
- HIPAA
- PHI/PII Data Handling Requirements
- SOC 2 Controls
- Enterprise Governance Policies
- Support model risk management and auditability requirements.
- Partner with security teams on:
- Secrets Management
- Network Security
- External Access Integrations
- Secure AI Operations
Leadership & Technical Enablement
- Serve as the technical authority for MLOps architecture and platform engineering.
- Mentor Machine Learning Engineers, Data Scientists, and Platform Teams.
- Develop reusable frameworks, templates, standards, and implementation accelerators.
- Evaluate emerging Snowflake AI and ML capabilities and provide recommendations for adoption.
- Drive architectural excellence and continuous improvement across AI and ML initiatives.
Required Qualifications
- Bachelor’s degree in Computer Science, Data Science, Engineering, Information Technology, or a related discipline, or equivalent work experience.
- 8+ years of experience in:
- Data Engineering
- Machine Learning Engineering
- Data Platforms
- Cloud Architecture
- 3+ years of experience designing and implementing MLOps and ML Platform architectures.
- Strong hands-on Snowflake experience, including:
- Snowpark Python
- Stored Procedures
- UDFs and UDTFs
- Tasks
- Streams
- Dynamic Tables
- Production experience with:
- Snowflake ML APIs
- Model Registry
- Feature Store
- Advanced expertise in:
- Python
- SQL
- Machine Learning Frameworks
- MLOps Best Practices
- Experience with:
- Scikit-Learn
- XGBoost
- LightGBM
- PyTorch
- TensorFlow
- Experience implementing:
- CI/CD Pipelines
- Infrastructure as Code
- Containerization with Docker
- Knowledge of:
- ML Monitoring
- Drift Detection
- Model Governance
- Responsible AI Practices
- Experience with at least one major cloud platform:
- AWS
- Azure
- GCP
Preferred Qualifications
- SnowPro Advanced Certification (Architect or Data Scientist).
- SnowPro Specialty: Snowpark Certification.
- Experience with:
- Snowpark Container Services (SPCS)
- GPU Workloads
- Distributed Training Frameworks
- Ray
- Hyperparameter Optimization Platforms
- Hands-on experience with:
- Cortex Functions
- Cortex Search
- Cortex Agents
- Retrieval-Augmented Generation (RAG)
- LLM Fine-Tuning
- Familiarity with:
- MLflow
- dbt
- Apache Airflow
- Kafka
- OpenFlow
- Experience migrating ML workloads from:
- Amazon SageMaker
- Databricks
- Azure ML
- On-Premises Environments
- Healthcare, Insurance, or Financial Services industry experience.
Technical Expertise
Candidates should demonstrate expertise in:
- Snowflake ML
- Snowpark
- Snowflake Model Registry
- Feature Store Architecture
- MLOps
- Machine Learning Operations
- AI Platform Engineering
- CI/CD for ML
- Snowpark Container Services (SPCS)
- Cortex AI
- Generative AI
- Retrieval-Augmented Generation (RAG)
- Python
- Advanced SQL
- Docker
- Infrastructure as Code
- ML Monitoring
- Model Governance
- Cloud Architecture
- AWS
- Azure
- GCP
Salary and Other Compensation
The annual salary for this position is anticipated to be between $155,000 and $170,000 USD, depending on experience, qualifications, geographic location, and other factors permitted by law.
In addition to base salary, this position may be eligible for:
- Annual Performance-Based Bonus
- Merit-Based Compensation Increases
- Employee Referral Bonuses, where applicable
Compensation information is accurate as of the date of this posting and may be modified based on business needs and applicable laws.
Benefits
Cognizant offers a comprehensive benefits package, including:
- Medical, Dental, and Vision Insurance
- Health Savings Account (HSA) and Flexible Spending Accounts (FSA)
- Life Insurance and AD&D Coverage
- Short-Term and Long-Term Disability Insurance
- Paid Time Off (PTO) and Company Holidays
- 401(k) Plan with Company Contributions (subject to eligibility)
- Employee Stock Purchase Plan (where available)
- Employee Assistance Program (EAP)
- Parental Leave and Family Support Benefits
- Tuition Reimbursement and Professional Development Programs
- Access to Learning, Certification, and Career Development Opportunities
Benefits are subject to eligibility requirements and plan terms.
Why Cognizant
- Lead enterprise-scale AI and MLOps transformation initiatives.
- Design and build next-generation machine learning platforms on Snowflake.
- Work with cutting-edge AI, GenAI, and cloud-native technologies.
- Collaborate with world-class data scientists, engineers, and architects.
- Influence the future direction of enterprise AI platforms and governance strategies.
- Access ongoing learning, certifications, and leadership development opportunities.
Equal Opportunity Employer
Cognizant is an equal opportunity employer. We are committed to fostering an inclusive workplace where all associates feel valued, respected, and empowered to contribute their unique perspectives. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, disability, protected veteran status, or any other characteristic protected by applicable law.
Applications will be accepted until the position is filled.
Things to know before you apply
- Work authorization: Cognizant will only consider applicants for this position who are legally authorized to work in Canada without requiring employer sponsorship, now or at any time in the future.
- Accommodations: If you have a disability that requires reasonable accommodation to search for a job opening or submit an application, please email [email protected] with your request and contact information.
- AI in hiring: We use artificial intelligence (AI) tools to help us screen and assess applications more efficiently. Our team performs additional human review and ultimately decides who moves forward in our hiring process.
- Open position: Unless otherwise stated, this job posting is for an open position on our team.
- Language proficiency: We ask that all candidates have basic English proficiency for company-wide communications purposes. For roles based in Quebec, professional English proficiency is required, as you’ll deliver services to and collaborate with stakeholders outside the province who may not speak French.
- Inclusion: Cognizant is an equal opportunity employer. Your application and candidacy will not be considered based on race, color, sex, religion, creed, sexual orientation, gender identity, national origin, disability, genetic information, pregnancy, veteran status or any other characteristic protected by federal, provincial or local laws.
About Cognizant
Cognizant (Nasdaq: CTSH) is an AI Builder and technology services provider, bridging the gap between AI investment and enterprise value by building full-stack AI solutions for our clients. Our deep industry, process and engineering expertise enables us to build an organization’s unique context into technology systems that amplify human potential, drive tangible outcomes and keep global enterprises ahead in a fast-changing world. See how at cognizant.ai or @cognizant.
