Job Title: Senior Data & AI Engineer Healthcare Analytics Git MLOps
Location: Tampa, FL
Duration: 1 year
Bill Rate: $89/hour on C2c
Job Type: C2C/1099
Client: To Be Discussed Later
Work Authorization: US-Citizen, H-1B, OPT-EAD, GC-EAD
Role Descriptions:
The MLOps Engineer is responsible for building| automating| deploying| monitoring| and maintaining Machine Learning (ML) models and platforms in production environments. The role bridges Data Science| Software Engineering| and DevOps practices to ensure scalable| reliable| and secure ML solutions.
Key Responsibilities
- Design| build| and maintain end-to-end ML pipelines for training| testing| deployment| and monitoring.
- Automate CI/CD processes for machine learning models and data workflows.
- Deploy and manage ML models on cloud platforms such as Azure| AWS| or Google Cloud Platform.
- Implement model monitoring| performance tracking| drift detection| and retraining strategies.
- Collaborate with Data Scientists| Data Engineers| and Application Development teams to operationalize ML solutions.
- Manage containerization and orchestration using Docker and Kubernetes.
- Ensure security| compliance| scalability| and reliability of ML platforms.
- Optimize infrastructure utilization and cloud costs for ML workloads.
- \Troubleshoot production issues and perform root cause analysis.
- Maintain documentation| standards| and best practices for MLOps processes.
Required Skills
- Strong programming skills in Python.
- Experience with ML frameworks such as TensorFlow| PyTorch| or Scikit-learn.
- Hands-on experience with CI/CD tools (Azure DevOps| Jenkins| GitHub Actions).
- Knowledge of Docker| Kubernetes| and Infrastructure as Code (Terraform| ARM| etc.).
- Experience with cloud platforms (Azure ML| AWS SageMaker| Google Cloud Platform Vertex AI).
- Familiarity with version control systems such as Git.
- Knowledge of monitoring and logging tools (Prometheus| Grafana| ELK| Azure Monitor).
- Understanding of data engineering concepts and ETL pipelines.
Preferred Qualifications
- Bachelors or Masters degree in Computer Science| Data Science| Engineering| or related field.
- Relevant certifications in Azure| AWS| Kubernetes| or DevOps.
- Experience implementing enterprise-scale AI/ML solutions.
Equal Opportunity Employer: We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.
