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Crowe · 2 weeks ago

Machine Learning Tech Lead

Indianapolis IN USA

Full-time

Hybrid

Lead/Staff

$126K/yr - $300K/yr

Crowe LLP is a leading public accounting, consulting, and technology firm in the United States. They are seeking a Machine Learning Tech Lead to provide architectural vision and leadership for AI projects, ensuring high-quality code and effective stakeholder communication while fostering team development and innovation.

AccountingAdviceConsultingFinanceFinancial ServicesInformation TechnologyProfessional ServicesTax Consulting

No H1B

Responsibilities

Provide solutions architecture and vision for existing solutions, supporting new feature development and testing, and preparing for release of high-quality, deployment-ready code

Translate business problems into AI solution designs, reference architectures, and implementation roadmaps

Architect the transition of AI projects from Proof of Concept to robust, production-ready solutions that transform 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

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 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

Qualification

PythonMachine learningGenAI ExperienceCloud ExperienceSoftware Development LifecycleAgile experienceAI Agent ExperienceAI-Assisted Software EngineeringKnowledge sharingCuriosity about AIProfessional Services experienceCommunication

Required

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