MLOps Engineer - Principal

As a Principal MLOps Engineer at Pathward, you will be responsible for leading the design and implementation of our machine learning operations infrastructure. This includes architecting enterprise-wide MLOps platforms, ensuring model monitoring, deploying scalable solutions, and establishing best practices for ML system reliability. You're not just a builder; you're a leader who drives strategic technical decisions and mentors teams to ensure success in ML practices.

To thrive as a Principal MLOps Engineer at Pathward, candidates should have at least 10 years of software engineering experience, focusing on ML/AI systems for at least 5 of those years. Expert knowledge of ML frameworks such as TensorFlow and PyTorch, along with deep experience in cloud platforms like AWS, GCP, or Azure, is essential. A strong academic background, preferably a Master’s degree, will significantly enhance your candidacy.

Absolutely! Pathward embraces a hybrid work model, which means you can work remotely from anywhere. However, we do have onsite locations in various cities if you prefer that flexibility. Our commitment to innovation spans across geographies, making it easier for you to contribute to our mission regardless of your physical location.

The salary range for a Principal MLOps Engineer at Pathward is quite competitive, falling between $99,501.91 and $183,764.31. The exact figure will be tailored based on your experience, skills, qualifications, and location. Plus, this role offers additional performance-based incentives, allowing you to reap the benefits of your contributions!

Pathward is deeply committed to fostering a culture of diversity and inclusion. We believe the strength of our company lies in our differences, and we actively encourage applications from candidates of all backgrounds. Our initiatives ensure that everyone feels valued and included, which in turn enhances our innovative capabilities.

Joining Pathward means you'll enjoy a comprehensive benefits package, including health insurance, 401(k) retirement benefits, life insurance, disability benefits, and ample paid time off. We prioritize the well-being of our employees, knowing that a happy team is a productive team!

As a Principal MLOps Engineer, your impact is significant! You will lead the charge in building and optimizing machine learning operations that can transform how we provide financial products. By ensuring reliable and efficient ML systems, you'll directly contribute to enhancing financial inclusion and economic mobility for diverse communities.

When answering this question, highlight specific MLOps frameworks you’ve worked with, such as TensorFlow or PyTorch. Discuss how you implemented these tools in previous projects, focusing on deployment strategies, monitoring, and scaling. Providing examples of challenges faced and how you overcame them will show your depth of experience.

In your response, remember to frame the challenge clearly and explain why it was significant. Share the steps you took to analyze the problem, the innovative solutions you implemented, and the outcome. This demonstrates your problem-solving mindset and technical expertise.

Explain your approach to creating robust testing and validation pipelines for ML models. Discuss version control practices, environment management, and the importance of monitoring models post-deployment. Share any tools and methodologies you use to ensure that results are consistent and reliable.

Highlight your evaluation criteria, which might include scalability, ease of integration, cost-effectiveness, community support, and alignment with the company's strategic goals. Share any past experiences where you successfully evaluated and selected a new technology that improved ML practices in your organization.

Share specific examples of how you've mentored and developed ML engineers or data scientists, highlighting any successful initiatives or projects. Explain your mentoring approach—whether it's hands-on training, code reviews, or collaboration on projects—to showcase your leadership skills.

Discuss various best practices you have implemented, such as automating workflows, using efficient algorithms, or leveraging cloud services for cost savings. Cite specific examples from your past experiences where efficiency measures led to improved performance or reduced costs.

Explain the importance of addressing technical debt and provide strategies you've utilized to manage it, such as refactoring code, improving documentation, or conducting regular reviews. Emphasize your proactive approach to minimizing technical debt in ML initiatives.

Share your philosophy on collaboration, including how you ensure alignment between teams, encourage knowledge sharing, and foster an inclusive environment. Cite specific collaborative projects that highlight successful outcomes resulting from teamwork.

Outline your methods for staying informed about MLOps advancements, which may include attending conferences, participating in online courses, engaging with professional communities, or reading research papers. Display your dedication to continuous learning and growth in the field.

Customize your response based on your genuine interests in Pathward’s mission of financial inclusion. Highlight how the role aligns with your expertise and passion and express excitement about the potential impact you could make within the organization.