Lead Technical Engineer - Commercial

As a Lead Technical Engineer at IV.AI, you will be directly involved in identifying client needs alongside the CEO and Commercial Operations team. You'll strategize technical approaches, manage a team of engineers and data scientists, and ensure strong relationships with clients are maintained. Writing clean code, addressing technical requests, and communicating project progress are essential tasks. Your aim will be to create exceptional customer experiences while meeting project deliverables on time.

Candidates for the Lead Technical Engineer position at IV.AI should possess at least 5 years of experience in Software Engineering, Data Science, or Machine Learning. Proficiency in Python is crucial, along with experience in tools like scikit-learn, Tensorflow, and Pytorch. Experience with data integration, managing stakeholders, and critical thinking is also important. A background in Go, Scala, or TypeScript, as well as data modeling, will be advantageous.

To thrive as a Lead Technical Engineer at IV.AI, you should be a strong communicator with excellent interpersonal skills. Being customer-oriented, creative in problem-solving, and possessing good time-management abilities is essential. Experience in managing multiple stakeholders and switching contexts efficiently will also play a vital role in your success. Moreover, having a collaborative spirit and a focus on delivering exceptional results will help you excel in our fast-paced environment.

At IV.AI, collaboration is at the heart of our culture, especially for the Lead Technical Engineer role. You’ll be part of a diverse, globally distributed team that values each member's contributions. We encourage open communication, continuous problem-solving, and knowledge sharing among team members. This collaborative effort enhances our ability to address complex challenges and maintain high-quality client relationships, contributing significantly to our success.

As a Lead Technical Engineer at IV.AI, you will work on a variety of exciting projects aimed at helping enterprise clients leverage our AI technology effectively. You'll be involved in developing technical solutions that address clients' specific needs, integrating AI models, and facilitating data-driven decisions. These projects often require a mix of software engineering, data science techniques, and client management to ensure successful outcomes.

In interviews, emphasize the projects where you've effectively used Python to design and implement scalable solutions. Mention specific libraries you’ve utilized, the challenges you faced, and how you overcame them. Highlight your ability to write clean, maintainable code and collaborate with teammates during development.

Share your approach to stakeholder management by discussing how you assess urgency and importance. Explain how good communication and setting clear expectations help you keep all parties informed and aligned, ensuring that their needs are met while maintaining project timelines.

Discuss your strategies for maintaining open lines of communication with clients, such as regular updates, feedback sessions, and ensuring you actively listen to their concerns. Showcase your ability to balance technical jargon with layman's terms depending on the audience.

Provide a specific example of a technical challenge, the steps you took to analyze the issue, and the solutions you implemented. Emphasize your critical thinking skills and your approach to testing and iterating solutions until the problem was resolved.

Detail your experience with Machine Learning frameworks by discussing relevant projects. Mention the algorithms you implemented, the data preprocessing steps you took, and how you validated your models. Showcasing measurable outcomes from your work can strengthen your response.

Talk about your practices for ensuring code quality, such as code reviews, pair programming, and using version control systems. Explain how you create a collaborative atmosphere where team members feel comfortable discussing improvements and best practices.

Share a project story where you faced strict deadlines. Detail your planning and time management strategies, how you coordinated with your team, and the methods you used to ensure the project was completed on time without compromising quality.

Discuss the resources you utilize to keep your knowledge current, like attending conferences, online courses, webinars, and reading industry blogs or research papers. Highlight how staying informed allows you to implement best practices in your work effectively.

Emphasize the importance of teamwork in your problem-solving approach. Describe how you actively seek input from colleagues, brainstorm solutions together, and leverage the diverse skills within your team to arrive at the best outcomes.

Outline the key performance indicators (KPIs) you track to measure project success. Discuss post-launch reviews for assessing project outcomes and client satisfaction, as well as any methodologies you employ for continuous improvement based on feedback.