AI Engineer / Machine Learning Engineer

SmartAssets is on the lookout for an experienced and innovative Lead AI Engineer to join our dynamic team. In this role, you will take a leadership position in developing and optimizing AI-driven features, guiding junior engineers, and ensuring the robustness and scalability of our AI solutions. You will play a pivotal role in shaping our platform's future by leading new projects and enhancing existing functionalities.

• Lead the development and deployment of advanced AI and machine learning models to support and enhance our workflows.
• Collaborate with cross-functional teams to integrate AI technologies with other system components.
• Ensure the scalability, efficiency, and robustness of AI solutions.
• Oversee the maintenance and improvement of existing AI features, adapting to new technologies and methodologies.
• Conduct and participate in code and design reviews to uphold high-quality standards.
• Mentor and guide junior AI engineers, fostering a collaborative and growth-oriented environment.
• Drive the analysis and measurement of ad-hoc studies, measuring marketing effectiveness and providing actionable insights.

Preferred Skills (Bonuses)

• Experience with cloud computing platforms (GCP) and their AI services.
• Familiarity with front-end technologies for AI-driven application development.
• Advanced understanding of data engineering and the ability to work with large datasets.

Education

• Master’s or Ph.D. degree in Computer Science, Artificial Intelligence, Data Science, or a related field, or equivalent practical experience.

• English & Spanish

hybrid

Incubated within the Stagwell Marketing Cloud, our AI platform empowers brands and creative agencies to produce high-quality advertising content by providing insight into the effectiveness of their creative choices. As part of the Stagwell Marketing Cloud, we leverage industry-leading technology and enjoy privileged access to agencies across the advertising spectrum.

1. Collaboration. We believe that bringing together different and varied expertise delivers results greater than the sum of their parts. Part of collaboration is ensuring we challenge each other constructively. This way we ensure that what we are building is really robust, and that we have mutual understanding and transparency.
2. Curiosity. We want to know why an ad works or doesn’t work. We want to get under the skin of what engages and audience and moves them to action. We believe that data is key to the creative process and enables us to really celebrate excellence in advertising. Something not working is still a valuable data point, which we embrace, bringing science into the art of advertising. We want to know what we don’t know.
3. Commitment. Bringing innovation to the market requires belief and drive. We have incredible momentum and great backing. We must remain committed to making SmartAssets the success we know it can be, focusing on what clients really need and delivering against that every single day.

Note: Successful applicants will receive a coding challenge to evaluate their programming knowledge and skills as outlined in this job description. This step is an essential part of our selection process to ensure a good match with our team's needs and the demands of the role.

• Extensive experience with version control tools, preferably Git.
• Proficiency in Docker and container orchestration.
• Advanced proficiency in Python and familiarity with AI and machine learning libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
• Strong understanding of algorithms, data structures, and software engineering principles.
• Experience in deploying AI models in a production environment.
• Proven ability to collaborate effectively with cross-functional teams and manage project timelines.
• Exceptional problem-solving skills and meticulous attention to detail.
• Deep understanding of data science fundamentals and experience with statistical analysis.
• Demonstrated experience in leading and mentoring technical teams.

• Extensive experience in applying theoretical knowledge in practical scenarios through traditional employment, freelance projects, open-source contributions, or coding bootcamps.
• Demonstrated leadership experience in AI and machine learning projects.