We’re Hiring! Our key client is hiring and looking to add a Senior MLOps Engineer (Multi-Cloud & Snowflake) to their team. Please check the description below and reach out to us for more details if you are interested.
Pay Rate: $85.31/hour on W2
Work Type: Hybrid – In-Office (Mon – Thu) | Remote (Fri)
Location: Houston, TX 77002
Work Schedule: 1st Shift | 8:00 AM – 5:00 PM CST
Duration: 8-month contract (with possible extension and/or conversion)
Job Overview:
* We are seeking a Senior MLOps Engineer to design, deploy, monitor, and maintain machine learning solutions in production across AWS, Azure, and Snowflake environments.
* This role will collaborate with data scientists and cloud teams to operationalize ML models, automate pipelines, and build scalable, secure ML platforms.
Key Responsibilities:
* Design and implement end-to-end ML pipelines (ingestion → deployment → monitoring)
* Deploy and manage ML models across AWS, Azure, and Snowflake ecosystems
* Build batch and real-time inference pipelines
* Implement CI/CD for model packaging, testing, release, and rollback
* Integrate ML workflows with:
* AWS SageMaker, AWS Lambda
* Azure Machine Learning, Azure Data Factory
* Snowflake
* Build orchestration workflows (Airflow, ADF, etc.)
* Implement experiment tracking, model registry, and governance
* Monitor model performance (accuracy, drift, latency, failures)
* Apply deployment strategies (canary, blue-green, shadow, rollback)
* Collaborate with cross-functional teams to productionize models
* Ensure security, compliance, and access control
* Optimize performance, reliability, and cost
* Document architecture and operational procedures
Required Qualifications:
* Master’s or PhD in Computer Science, Engineering, or related field
* 5+ years of relevant experience
* Strong experience in MLOps / ML Engineering / DevOps
* Hands-on experience with AWS, Azure, and Snowflake
* Strong programming skills in Python and SQL
* Experience deploying ML models in production
* Experience with:
* AWS SageMaker, Azure ML
* Data pipelines and Snowflake integration
* CI/CD, infrastructure automation, model versioning
* Docker, Kubernetes
* Airflow, Azure Data Factory (or similar)
* Knowledge of monitoring, logging, and observability
* Strong understanding of data engineering and distributed systems
* Strong troubleshooting and communication skills
Preferred Qualifications:
* Experience with Snowflake Cortex AI, Snowpark, or ML workloads in Snowflake
* Experience with AWS Bedrock, Azure OpenAI, or LLM workflows
* Experience with real-time inference and serverless architectures
* Familiarity with feature stores, vector databases, and RAG systems
* Experience with Terraform, CloudFormation, or Azure IaC tools
* Knowledge of security, compliance, and governance in regulated environments
* Experience with A/B testing, shadow deployments, and rollback strategies
Raise PBC is committed to a policy of nondiscrimination and equal opportunity for all employees and qualified applicants without regard to race, color, religious creed, national origin, ancestry, age, disability, genetics, gender identity, veterans' status, sexual orientation, or any other characteristic protected by law. Raise PBC is an equal-opportunity employer encouraging diversity in the workplace.