Contract Machine Learning Engineer
$75 - $110 per hourAtrium Staffing
About Atrium: What you do matters. Guided by our Applicant-Centric™ approach, we foster an environment of collaboration, high performance, and innovation where your talents are valued, and your achievements are celebrated. Join us and become part of an inclusive team committed to your growth and success. Client Overview: We are partnering with an innovative technology organization focused on delivering scalable AI and machine learning solutions across enterprise platforms. The team is building modern cloud-native infrastructure and advanced ML systems to support high-impact business initiatives, and they are looking to add a Contract Machine Learning Engineer. This is an opportunity for a Contract Machine Learning Engineer to work alongside experienced Engineers, Data Scientists, and Platform teams in a fast-paced and collaborative environment. Salary/Hourly Rate: $75/hr - $110/hr (Depending on experience, technical skill set, and project scope) Position Overview: Our client is seeking an experienced Contract Machine Learning Engineer to support the deployment, automation, and operationalization of machine learning platforms and production AI systems. This Contract Machine Learning Engineer will work closely with Data Science, DevOps, Cloud Engineering, and Software Development teams to streamline ML workflows, improve deployment reliability, and optimize scalable cloud infrastructure. The ideal candidate has hands-on experience supporting production ML environments and building automated MLOps pipelines. Responsibilities of the Contract Machine Learning Engineer:
EOE/M/F/D/V/SO
- Design, implement, and support scalable MLOps infrastructure and deployment frameworks.
- Build and maintain CI/CD pipelines for machine learning model training, testing, and deployment.
- Collaborate with Data Scientists and Engineering teams to productionize ML models and AI services.
- Automate model monitoring, validation, retraining, and performance tracking processes.
- Support containerized deployments using Kubernetes and Docker technologies.
- Manage and optimize cloud-based ML environments across AWS, Azure, or GCP.
- Implement model versioning, experiment tracking, and reproducibility standards.
- Monitor production systems for model drift, latency, reliability, and operational issues.
- Troubleshoot infrastructure and deployment-related challenges across distributed environments.
- Document MLOps workflows, platform architecture, and operational best practices.
- 4+ years of experience in MLOps, Machine Learning Engineering, DevOps, or Platform Engineering.
- Strong experience deploying machine learning models into production environments.
- Advanced Python programming skills and familiarity with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.
- Experience with CI/CD tools, including GitHub Actions, Jenkins, GitLab CI, or similar platforms.
- Hands-on expertise with Docker, Kubernetes, and container orchestration.
- Strong cloud platform experience with AWS, Azure, or Google Cloud Platform.
- Experience with ML orchestration and lifecycle management tools such as MLflow, Kubeflow, SageMaker, Vertex AI, or Airflow.
- Familiarity with Infrastructure-as-Code tools such as Terraform or CloudFormation.
- Strong understanding of APIs, distributed systems, and production monitoring tools.
- Excellent troubleshooting, communication, and collaboration skills.
- Experience supporting Generative AI, LLMOps, or AI platform engineering initiatives.
- Familiarity with vector databases, RAG architectures, and AI orchestration frameworks.
- Experience working within enterprise or highly regulated environments.
- Knowledge of Spark, Kafka, Snowflake, or large-scale data processing platforms.
- Exposure to GPU infrastructure and model optimization workflows.
- Cloud certifications or Kubernetes certifications preferred.
- Bachelor's degree in Computer Science, Engineering, Information Technology, Data Science, or a related technical discipline is preferred.
- Competitive hourly compensation.
- Opportunity for contract extension and long-term engagement.
- Exposure to enterprise-scale AI/ML initiatives.
- Access to modern cloud and AI technologies.
- Collaborative Engineering and Data Science teams.
- Weekly pay and dedicated recruiter support.
- Atrium Care Package available, upon eligibility (including healthcare plans, discount programs, and paid time off).
- Apply now
EOE/M/F/D/V/SO
Vacancy posted 1 day ago
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