Salary
💰 $130,000 - $150,000 per year
Tech Stack
AirflowAWSAzureCloudCyber SecurityGoogle Cloud PlatformPythonPyTorchScikit-LearnTensorflow
About the role
- Drive transformative AI solutions by designing, building, and deploying robust, scalable AI systems for clients
- Collaborate with Data Scientists and Data Engineers to implement custom machine learning models and AI solutions
- Write and maintain production-grade code following industry-leading software engineering practices
- Deploy and fine-tune advanced machine learning and deep learning models to meet performance and scalability goals
- Integrate models into clients’ production pipelines ensuring robustness, reliability, and business alignment
- Participate in build-outs of reusable AI components and accelerators to standardize delivery
- Track and manage billable utilization, ensuring accurate invoicing, strong client ROI, and CBTS profitability
- Own delivery quality and utilization to drive client outcomes and reinforce consultative excellence at CBTS
Requirements
- 3–5 years of hands-on experience as an ML Engineer or AI Engineer, delivering production-grade solutions
- Experience with MLOps, model deployment, and scalable infrastructure
- Strong proficiency in Python and ML frameworks such as TensorFlow, PyTorch, or scikit-learn
- Experience with cloud-based AI/ML services (AWS, Azure, GCP)
- Demonstrated ability to translate model prototypes into production deployments
- Track record of contributing to reusable assets, accelerators, and solution frameworks
- Solid coding practices and familiarity with production-quality engineering workflows
- Exposure to operational monitoring, automation, and AI lifecycle tools (e.g., MLflow, Airflow)
- Non-US citizens may be required to submit to an extensive government agency background check which will necessitate disclosure of sensitive Personally Identifiable Information.