Sr Software Engineer (AI & ML Technical Lead)

As a Sr Software Engineer (AI & ML Technical Lead) at NISC, you will be responsible for architecting and deploying AI/ML solutions used in production. You'll lead a talented team through the entire development process, focusing on the latest advancements in AI, including large language models and agentic architectures. You'll work collaboratively across departments to ensure our solutions align with our cooperative mission and serve our Members effectively.

To be considered for the Sr Software Engineer (AI & ML Technical Lead) position at NISC, you should have at least 10 years of software development experience, with 5+ years specifically in AI/ML software development. A strong background in Python, TensorFlow, PyTorch, and cloud-based ML solutions is essential, along with proven experience in model training, deployment, and scalable system design.

NISC offers a hybrid work environment for the Sr Software Engineer (AI & ML Technical Lead) position, allowing you to work from one of our office locations or fully remotely if you meet the necessary experience criteria. We promote a culture of collaboration and innovation, where teamwork and personal development are highly valued.

The Sr Software Engineer (AI & ML Technical Lead) plays a critical role in shaping NISC's AI strategy, directly impacting our mission to empower cooperatives and enhance the services they provide. By developing AI-driven tools that improve operational efficiency and member service, you will help rural utilities and broadband providers make a real difference in their communities.

At NISC, we offer an attractive benefits package for the Sr Software Engineer (AI & ML Technical Lead) that includes medical, dental, and vision insurance, a Health Savings Account, employee educational assistance, and generous PTO. We also have programs rewarding wellness activities, along with financial support for unexpected hardships, demonstrating our commitment to our team’s well-being.

When answering this question, highlight specific projects where you've designed and implemented AI or ML solutions. Discuss the technologies you used, the challenges you faced, and how your solutions provided business value, specifically in production environments.

Provide examples of your experience with large language models, such as OpenAI’s models or custom-trained variants. Discuss the areas of application you’ve worked on and any relevant performance metrics or outcomes achieved.

Outline your approach to optimizing machine learning models, including techniques like hyperparameter tuning, feature engineering, and regularization methods. Provide examples of results from previous optimizations and their impact.

Discuss your understanding of cooperative business principles and how you involve stakeholders in the development process. Showcase experiences where you tailored solutions to meet the specific needs of Member organizations.

Explain your background with agentic architecture design, providing specific examples of projects where you utilized these systems. Discuss how they enhanced the functionality or adaptability of AI solutions that you implemented.

In your response, describe your leadership style and methods for fostering collaboration and innovation. Share a specific project where you successfully led a team to overcome challenges and achieve goals.

Address the importance of ethical AI development, mentioning the need for fairness, transparency, and accountability in AI solutions. Provide any examples where you have implemented ethical guidelines in your work.

Candidates should discuss strategies for continuous learning, such as attending conferences, engaging with academic journals, and participating in relevant online communities or forums where AI topics are discussed.

Share a specific scenario where you utilized AI to address a complex challenge. Emphasize your problem-solving process and how your solution led to measurable outcomes or improvements.

Discuss trends and predictions for AI's role in this sector, focusing on how innovations can improve service delivery, operational efficiencies, and overall Member satisfaction, tying your insights back to your experience.