Machine Learning Tech Lead

Crowe•Indianapolis, IN

1d•Remote

About The Position

Your Journey at Crowe Starts Here: At Crowe, you can build a meaningful and rewarding career. With real flexibility to balance work with life moments, you’re trusted to deliver results and make an impact. We embrace you for who you are, care for your well-being, and nurture your career. Everyone has equitable access to opportunities for career growth and leadership. Over our 80-year history, delivering excellent service through innovation has been a core part of our DNA across our audit, tax, and consulting groups. That’s why we continuously invest in innovative ideas, such as AI-enabled insights and technology-powered solutions, to enhance our services. Join us at Crowe and embark on a career where you can help shape the future of our industry. Job Description: Machine Learning Tech Lead Job Description< >Team: AI ProductsLocation: Chicago, Indianapolis, or RemoteReports To: Thomas CallaghanLevel: ManagerWe 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. As a Tech Lead in AI Products, your responsibilities will vary across the development lifecycle, and include providing solutions architecture and vision for existing solutions, supporting new feature development and testing, and preparing for release of high-quality, deployment-ready code.AI Product Tech Leads must have strong stakeholder-facing skills to translate business problems into AI solution designs, reference architectures, and implementation roadmaps.AI Product 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. 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.You seek deep understanding and take ownership of the impact your technical decision-making has on driving costs for the firm and/or clients.Oversee the implementation of testing protocols, including smoke tests and unit tests, to maintain high-quality outputs, in collaboration with members of the AI Platform and Infrastructure 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 and proactively identify big picture improvements that benefit the client, product, and/or development team.Act as a career coach, fostering the growth and development of 3+ team members through knowledge-sharing, constructive code review, and by setting the standard for code quality and research best practices.Willingness to travel domestically to meet client needs

Requirements

Programming experience. You’re experienced writing scalable, production-level code in Python. You’re familiar with Linux/UNIX systems.
Machine learning experience. You’re proficient in machine learning packages, such as Tensorflow and Pytorch, and have proven expertise in designing/developing AI/ML models. You understand the mechanics of supporting ML solutions in a production environment and can help develop/maintain tests that validate functionality and evaluate model performance.
GenAI Experience. Experience designing and implementing AI agents using large language models (LLMs), including prompt engineering, tool use, memory, and multi-agent orchestration patterns. Proficiency with modern AI/ML frameworks, tools, and agent platforms (e.g. MCP, A2A, Microsoft Foundry, OpenAI Agent SDK, Semantic Kernel, LangChain, LlamaIndex, Microsoft Copilot Studio, or equivalent). Knowledge of retrieval-augmented generation (RAG), vector databases, embeddings, and techniques for grounding model outputs in enterprise data.
Software Experience. You’re familiar with the software development lifecycle, and ideally tenets of MLOps. You have exposure to CI/CD frameworks and tools like Docker and Git. You’re experienced deploying code in production environments.
AI-Assisted Software Engineering: Demonstrated ability to embrace and advocate for AI-assisted software engineering practices, including the effective use of coding assistants (e.g. Claude Code), automated testing, and design-time AI tools to accelerate solution design, improve quality, and enhance developer productivity.
Communication. Excellent communication skills, capable of effectively documenting and summarizing technical details for non-technical stakeholders.
Agile experience. You’re experienced attending Scrum or Kanban meetings; you favor incremental, iterative improvements through regular releases, testing, and monitoring.
AI Agent Experience. Familiarity with evaluation, monitoring, and observability of AI agents, including guardrails, hallucination mitigation, and human-in-the-loop designs. Ability to translate business requirements into agent behaviors, decision logic, and measurable performance outcomes. Proven ability to design end-to-end AI architectures that integrate agents with enterprise systems (ERP, CRM, data platforms, APIs) using scalable, secure integration patterns.
Cloud Experience: Experience designing and deploying AI/ML solutions on major cloud platforms (AWS, Azure, and/or GCP), including the use of managed AI services, cloud-native integration patterns, scalable data architectures, and secure, enterprise-grade deployments.
Knowledge sharing. You enjoy sharing what you learn, whether by offering cross-training opportunities, giving internal team “lightning talks,” or by writing detailed comments on tickets when you close them.
Curiosity about AI and machine learning. You want to stay fresh in AI and machine learning. You demonstrate curiosity and continuous learning mindset in Generative AI and applied machine learning, with an interest in staying current on emerging models, architectures, and techniques, including engaging with original research, technical papers, and pre-release concepts before they are broadly commercialized
Professional Services experience. You’re familiar with the landscape of a professional services firm and interested in engaging with the unique value proposition of products associated with a diverse range of services, from advising and consulting to tax and public accounting.
Willingness to travel domestically to meet client needs

Responsibilities

providing solutions architecture and vision for existing solutions
supporting new feature development and testing
preparing for release of high-quality, deployment-ready code
translating business problems into AI solution designs, reference architectures, and implementation roadmaps
architecting the transition of AI projects from Proof of Concept to robust, production-ready solutions
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 AI Platform and Infrastructure 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 and proactively identify big picture improvements that benefit the client, product, and/or development team
Act as a career coach, fostering the growth and development of 3+ team members through knowledge-sharing, constructive code review, and by setting the standard for code quality and research best practices