Senior Staff Machine Learning Engineer

About Tekion:

Positively disrupting an industry that has not seen any innovation in over 50 years, Tekion has challenged the paradigm with the first and fastest cloud-native automotive platform that includes the revolutionary Automotive Retail Cloud (ARC) for retailers, Automotive Enterprise Cloud (AEC) for manufacturers and other large automotive enterprises and Automotive Partner Cloud (APC) for technology and industry partners. Tekion connects the entire spectrum of the automotive retail ecosystem through one seamless platform. The transformative platform uses cutting-edge technology, big data, machine learning, and AI to seamlessly bring together OEMs, retailers/dealers and consumers. With its highly configurable integration and greater customer engagement capabilities, Tekion is enabling the best automotive retail experiences ever. Tekion employs close to 3,000 people across North America, Asia and Europe.

Summary:

Responsible for leading the strategic design and development of scalable machine learning infrastructure and systems across the organization. As a top-tier individual contributor, this role provides deep technical expertise, sets engineering standards, and drives the long-term architecture of ML platforms. The Senior Staff ML Engineer partners with cross-functional leaders, mentors engineering teams, and delivers reliable, high-impact ML solutions at scale.

Duties & Responsibilities:

• Architect and lead the development of large-scale machine learning platforms and services that support model training, deployment, and lifecycle management.

• Collaborate with Data Science, Applied Science, and Product teams to productionize ML models with performance, reliability, and compliance in mind.

• Define and implement MLOps best practices, including model versioning, automated retraining, monitoring, and CI/CD workflows.

• Lead technical decision-making and platform evolution to ensure scalability, security, and maintainability of ML infrastructure.

• Optimize inference systems for real-time and batch applications across cloud and hybrid environments.

• Serve as a technical advisor to leadership and engineering teams on architectural decisions and ML infrastructure investments.

• Mentor and develop senior-level engineers across teams and contribute to technical capability building across the organization.

• Evaluate and incorporate new technologies and frameworks to advance the ML engineering roadmap.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field.

• 12+ years of experience in software or ML engineering, with significant time spent in leadership and architecture roles.

• Proven experience building and scaling machine learning systems in production environments.

• Deep proficiency in Python and ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).

• Expert in distributed systems, cloud platforms (AWS, GCP, Azure), and container orchestration (Kubernetes).

• Strong understanding of MLOps tools, model performance monitoring, and continuous delivery of ML solutions.

• Experience mentoring senior engineers and influencing cross-functional architectural strategies.

• Excellent communication, collaboration, and problem-solving skills.