CBTS

Compensation

Full Description

Position Overview As a client-facing AI/ML Engineer at CBTS, you’ll drive transformative AI solutions by designing, building, and deploying robust, scalable AI systems. Your delivery expertise and technical finesse will directly contribute to both client value and CBTS’s financial performance making every engagement count. What You’ll Do Collaborate with Data Scientists and Data Engineers to implement custom machine learning models and AI solutions that solve business challenges. 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. Help integrate models seamlessly into clients’ production pipelines, ensuring robustness, reliability, and business alignment. Participate in build-outs of reusable AI components and accelerators to standardize delivery and drive practice-level efficiencies. Track and manage your billable utilization, ensuring accurate invoicing, strong client ROI, and CBTS profitability. Why It Matters at CBTS By owning both delivery quality and utilization, you play a dual role: driving client outcomes through scalable, high-value AI systems and reinforcing CBTS’s consultative excellence through consistent billable productivity. Your engineering contributions convert technological innovation into measurable advantages, reinforcing CBTS’s reputation for delivering impactful, client-centered AI. Qualifications Required Preferred 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) Due to U.S. Government requirements applicable to foreign-owned telecommunications providers, non-US citizens may be required to submit to an extensive government agency background check which will necessitate disclosure of sensitive Personally Identifiable Information.