AI/ML Enterprise Sales Engineers (USA)

As an AI/ML Enterprise Sales Engineer at Deepomatic, you will manage all technical customer-facing activities, driving success through collaboration with sales and product teams. Your primary responsibilities will include developing proof-of-concepts, training neural networks, and implementing end-to-end workflows. You'll also hold customer meetings to assess progress and offer ongoing support, ensuring our telecommunications and utilities clients achieve the maximum value from our solutions.

To qualify for the AI/ML Enterprise Sales Engineer position at Deepomatic, you should hold a bachelor’s degree in engineering, computer science, or a related field, with a master’s degree being a plus. We prefer candidates with 3 to 5 years of experience in Python for data science, a solid understanding of machine learning, deep learning, and computer vision, as well as excellent communication skills. Familiarity with telecommunications, utilities, and construction will also be an advantage.

Deepomatic is committed to the growth of its employees, especially in technical roles like the AI/ML Enterprise Sales Engineer. You will undergo a comprehensive onboarding process, gaining hands-on experience with our platform and tools. As you progress in your role, you'll have opportunities to mentor new hires, develop internal tools, and participate in high-impact projects, helping you expand your skill set while contributing to the team's success.

At Deepomatic, we believe in valuing our employees. As an AI/ML Enterprise Sales Engineer, you will receive competitive benefits, including comprehensive insurance coverage for yourself and your family at 100% monthly premiums covering medical, dental, vision, and life insurance. Additionally, we promote a diverse and inclusive work culture that fosters innovation and collaboration.

In the AI/ML Enterprise Sales Engineer role at Deepomatic, you're expected to conduct on-site visits to assess customer needs and ensure the technical feasibility of our solutions. This travel is essential for building strong relationships with clients and understanding their unique requirements as you guide them through the deployment and implementation processes.

When answering this question, detail your specific experience with machine learning algorithms, especially those used in computer vision projects. Discuss any relevant projects, the challenges you faced, and how you overcame them. Highlight your familiarity with data preprocessing and model evaluation metrics, ensuring to tie your experiences back to how they can benefit Deepomatic’s operations.

In your response, emphasize your structured approach by first understanding the client’s specific needs and objectives. Describe how you utilize Deepomatic’s models to create tailored proof-of-concepts that not only demonstrate our technology but also address the client’s pain points. Share examples where this approach has successfully worked in the past.

Explain how you adapt your communication style based on your audience, whether it’s a technical team or C-suite executives. Discuss how you ensure all parties understand the technical aspects while relating them to business outcomes. Sharing a specific instance where you successfully navigated such discussions will make your answer more impactful.

Discuss the various resources you leverage for staying informed, such as academic journals, online courses, webinars, and industry conferences. Highlight any key developments in AI/ML that significantly influenced your work. This shows your enthusiasm and commitment to continually improving your expertise in the field.

In your response, share a situation where a customer faced a significant challenge with their implementation or understanding of the technology. Detail the steps you took to identify the issue, how you collaborated with other teams (like product or engineering), and the eventual outcome. Emphasizing teamwork and problem-solving will demonstrate your capability in this role.

Highlight the importance of understanding the customer’s operational needs and clearly defining the goals of the proof-of-concept. Discuss the importance of realistic expectations, continuous communication with stakeholders, and how collecting feedback post-deployment is crucial for adjusting future deployments. This ties back to Deepomatic’s commitment to customer success.

Share specific tools and techniques you have used for data manipulation and visualization in your previous roles, and how these have contributed to the success of your projects. This could include discussing practical applications, like developing dashboards that informed decision-making or improved operational performance.

Talk about your familiarity with project management methodologies and tools. Describe past experiences leading projects, ensuring you emphasize your organizational skills, the importance of timelines, and adaptability to changing circumstances. Highlighting your collaborative approach will signal that you understand the cross-functional nature of the AI/ML Enterprise Sales Engineer role.

Discuss your methods for evaluating project timelines, stakeholder expectations, and deliverables. You can speak about using tools or frameworks that help you prioritize effectively, enabling you to manage workload efficiently. Example-driven responses here can exemplify your organizational skills and foresight.

Share your passion for the potential of AI and machine learning to transform industries, particularly telecommunications and utilities in this context. Discuss specific innovations you see on the horizon and how they could positively impact Deepomatic’s solutions. This response should reflect your enthusiasm for both technology and the opportunity to innovate at Deepomatic.