Machine Learning Engineer Tech Lead 2

Crowe - Chicago, IL

Full-time - Mid Level

Remote - Chicago, IL

Professional, Scientific, and Technical Services

About the position

At Crowe, you have the opportunity to deliver innovative solutions to today's complex business issues. Crowe's accounting, consulting, and technology personnel are widely recognized for their in-depth expertise and understanding of sophisticated process frameworks and enabling technologies, along with their commitment to delivering measurable results that help clients build business value. Our focus on emerging technology solutions along with our commitment to internal career growth and exceptional client value has resulted in a firm that is routinely recognized as a “Best Place to Work.” We are 75 years strong and still growing. Come grow with us! As a member of AI Engineering, you are a builder excited to realize an AI idea's impact at scale, distinguishing Crowe in the market and driving the firm's technology and innovation strategy. We foster good science. You are given the time and resources to build your expertise in your project and beyond; you will guide fellow MLEs and product stakeholders through your work. We want to make good scientists better. MLEs have plenty of options on the job market. We want to be one of the best. We have regular ethics and book club meetings, monthly lightning talks where team members teach each other, support for conferences, and weekly “10P” independent time for ongoing learning. We truly value work-life balance. Our distributed team offers unlimited PTO and a flexible work-from-home policy. We actively discourage weekend and off-hours work (unless that's genuinely your thing). As a Tech Lead in AI Engineering, your responsibilities will vary across the development lifecycle, and include providing solutions architecture and vision for existing solutions, including the support of new feature development, testing, and preparing for release of high-quality, deployment-ready code. AI Engineering Tech Leads are responsible for architecting the transition of AI projects from Proof of Concept to robust, production-ready solutions that transform our business offerings.

Responsibilities

• Provide solutions architecture and vision for existing solutions, including support for new feature development, testing, and preparing for release of high-quality, deployment-ready code.
• Conduct lightweight sprint planning and review sessions, prioritizing features and managing project timelines.
• Write, review, and ensure the quality of production-ready code, setting high standards for the team.
• Oversee the implementation of testing protocols, including smoke tests and unit tests, to maintain high-quality outputs, in collaboration with members of the MLOps software engineers.
• Prepare and refine Service Level Agreements (SLAs) and release documentation in preparation for production deployment; collaborate with Enablement team to create user upskilling materials that support effective use and drive adoption of AI solutions and latest features.
• Lead ethical reviews and risk/security evaluations to ensure compliance and safeguard our solutions.
• Engage with business stakeholders to refine project objectives and demonstrate the value and impact of implemented features.
• Act as a career coach, fostering the growth and development of team members through knowledge-sharing, constructive code review, and by setting the standard for code quality.

Requirements

• Programming experience in writing scalable, production-level code in Python and familiarity with Linux/UNIX systems.
• Proficiency in machine learning packages, such as Tensorflow and Pytorch, with proven expertise in designing/developing AI/ML models.
• Familiarity with the software development lifecycle and ideally tenets of MLOps, with exposure to CI/CD frameworks and tools like Docker and Git.
• Excellent communication skills, capable of effectively documenting and summarizing technical details for non-technical stakeholders.
• Experience attending Scrum or Kanban meetings, favoring incremental, iterative improvements through regular releases, testing, and monitoring.

Nice-to-haves

• Expertise in prompt engineering and experience with tools like Enterprise ChatGPT, Microsoft Copilot, and Azure AI Studio.
• Enjoyment in sharing knowledge through cross-training opportunities, internal team “lightning talks,” or detailed comments on tickets.
• Curiosity about machine learning and willingness to engage with deep learning papers.
• Familiarity with the landscape of a professional services firm and interest in engaging with the unique value proposition of products associated with a diverse range of services.

Benefits

• Unlimited PTO
• Flexible work-from-home policy
• Comprehensive benefits package
• Career coaching and guidance in career goals and aspirations