ShiftCode Analytics, Inc. · 2 months ago
MLOps Engineer – AWS & Databricks - SGWS
Dallas, TX
Full-time
Hybrid
Mid, Senior Level
4+ years expShiftCode Analytics, Inc. is seeking a highly skilled MLOps Engineer with expertise in AWS and Databricks to design, implement, and maintain scalable machine learning infrastructure. The role involves automating and optimizing the ML lifecycle, including model development, deployment, and monitoring.
AnalyticsConsultingInformation Technology
No H1B
Responsibilities
Design, implement, and maintain CI/CD pipelines for ML applications using AWS CodePipeline, CodeCommit, and CodeBuild
Automate deployment of ML models into production using Amazon SageMaker, Databricks, and MLflow for versioning and lifecycle management
Develop, test, and deploy AWS Lambda functions for triggering workflows, automating pre/post-processing, and integrating with other AWS services
Maintain and monitor Databricks model serving endpoints for scalable, low-latency inference
Orchestrate complex ML pipelines using Airflow (MWAA) or Databricks Workflows, covering ingestion, training, evaluation, and deployment
Collaborate with Data Scientists and ML Engineers to convert notebooks into reproducible, version-controlled pipelines
Integrate model monitoring and alerting (drift detection, performance logging) using CloudWatch, Prometheus, or Datadog
Manage infrastructure-as-code (IaC) via CloudFormation or Terraform for secure, reproducible deployments
Ensure secure and compliant pipelines using IAM roles, VPC configurations, and secrets management (AWS Secrets Manager or SSM Parameter Store)
Champion DevOps best practices across the ML lifecycle, including canary deployments, rollback strategies, and audit logging
Qualification
Required
4+ years of hands-on MLOps experience deploying ML applications at scale
Proficient in AWS services: SageMaker, Lambda, CodePipeline, CodeCommit, ECR, ECS/Fargate, and CloudWatch
Strong experience with Databricks workflows and Model Serving, including MLflow for tracking and deployment
Proficient in Python and shell scripting; skilled in Docker containerization
Deep understanding of CI/CD principles for ML, including pipeline testing, data validation, and quality gates
Experience orchestrating ML workflows using Airflow (open-source or MWAA) or Databricks Workflows
Familiarity with monitoring/logging stacks: Prometheus, ELK, Datadog, or OpenTelemetry
Experience deploying models as REST endpoints, batch jobs, and asynchronous workflows
Strong Git/GitHub skills with experience in automated deployment reviews and rollback strategies
Preferred
Experience with Feature Stores (e.g., SageMaker Feature Store, Feast)
Familiarity with Kubeflow, SageMaker Pipelines, or Vertex AI
Exposure to LLM-based models, vector databases, or RAG pipelines
Knowledge of Terraform or AWS CDK for infrastructure automation
Experience with A/B testing or shadow deployments for ML models
Company
ShiftCode Analytics, Inc.
ShiftCode Analytics Inc is a Tampa, FL based firm formed with one sole purpose of delivering best and quick services to its clients nationwide.
51-200 employees
Funding
Current Stage
Growth StageCompany data provided by crunchbase