Machine Learning Architect
Concurrency
Full-time
On-site
Brookfield, Wisconsin, United States
Technology
Who We Are
At Concurrency, we embody innovation. We're not just tech consultants; we are forward thinkers with a purpose. Our team thrives on disrupting the norm, constantly seeking the next challenge and pushing boundaries to redefine what's achievable. Recognized as a Microsoft Gold Partner, a ServiceNow Elite Partner, and recipient of multiple Partner of the Year awards, Concurrency is synonymous with excellence. If you're fueled by the desire to transform technology into real-world solutions, join us and unleash your potential as a change catalyst.
Who We’re Looking For
We’re looking for a full stack ML Architect to help take our Product Engineering team to the next level. Your main responsibility will be designing and implementing data-intensive ML applications in Azure that solve customer problems. Your second responsibility is helping grow the group by setting internal technical direction, finding and scoping new projects, and publishing thought leadership. The ideal candidate excels at solving stubborn business problems and enjoys working across the ML software lifecycle from requirements gathering to system design, implementation, and documentation. You thrive in early-stage environments that provide freedom to move fast and ship new features at high velocity without compromising quality standards. You’ll work with a high-performance engineering team and report directly to the technical Practice Manager of Engineering, significantly influencing our technical direction and that of our customers.
At Concurrency, we believe in living out our core values every day. These principles guide our actions, decisions, and interactions:
Be Yourself: Be the best version of your whole self. Your authenticity matters.
Be Bold: Bravely and respectfully take risks and challenge the norm.
Have a Growth Mindset: Be open to learning and apply your expertise.
Be the Difference: Ensure that every interaction with your colleagues, clients and community improves their lives.
Assume Positive Intent: Lead with giving the benefit of the doubt.
What You'll Do
- Lead and Architect
- Confidently drive every stage of the ML software development lifecycle, from initial concept to full-scale production deployment
- Lead workshops to gather technical and business requirements, translating customer pain points into actionable AI and data science strategies
- Advise internal and external stakeholders on trends in Data & AI, influencing both technical direction and strategic initiatives to scale the company's ML market share
- Architect and implement robust, scalable, and data-driven machine learning applications within Azure, balancing business value with technical innovation
- Produce thought leadership through GitHub contributions, blog posts, or technical talks on LinkedIn or YouTube to elevate both personal and company profiles
- Build
- Build end-to-end machine learning pipelines across supervised, unsupervised, and deep learning paradigms, with strengths in inferential statistics, time series, computer vision, or LLMs.
- Engineer ML solutions that integrate seamlessly with Azure cloud infrastructure, ensuring performance, scalability, and maintainability.
- Utilize state-of-the-art DevOps and MLOps practices (CI/CD pipelines, containerization, and automated governance) to build production-ready systems.
- Collaborate and Persuade
- Serve as the bridge between sales, leadership, and customers, identifying client pain points and translating them into tailored, profitable ML solutions
- Communicate complex technical architectures and ML solutions to diverse audiences, simplifying concepts for non-technical stakeholders
- Navigate ambiguity in customer goals and evolving technical landscapes, while driving towards clear, measurable outcomes
- Mentor and Cultivate
- Be a mentor and role model for team members, fostering a high-performance MLE culture
- Foster psychological safety where team members are encouraged to challenge the status quo, propose new approaches, and fail productively
- Help grow and shape a technical team capable of delivering high-impact ML projects at scale
What You'll Need
- Technical Expertise:
- Languages/Frameworks: Python, working knowledge of Scala, Java, or PySpark. Pandas, numpy, sklearn, LangChain
- Azure: Deep knowledge of Azure's ecosystem including Azure ML, Data Factory, Databricks, Data Lake Storage, Cosmos DB, and Azure SQL DB.
- System Design: Expertise in designing Azure architecture following Domain-Driven Design principles
- AI & ML Skills: Proficiency in supervised, unsupervised, and deep learning models, including hands-on experience with LLM architectures, time series forecasting, and computer vision solutions
- MLOps & DevOps: Strong understanding of MLOps pipelines and MLFlow, CI/CD automation with Azure DevOps or GitHub Actions, and containerization technologies like Docker and Kubernetes
- Tools: Proficient in GitHub, PowerShell, Azure CLI, and infrastructure-as-code tools such as ARM templates or Terraform
- Soft Skills & Leadership:
- Proven experience leading high-performance teams in a fast-paced, customer-centric environment
- Strong ability to communicate technical concepts to non-technical stakeholders, and to translate business objectives into scalable ML systems
- Ability to mentor and grow teams, setting high standards for both technical quality and engineering discipline
- Experience:
- 10+ years of experience in system design, ML/AI architecture, and enterprise data infrastructure
- Demonstrable experience building ML applications in industries such as Manufacturing, Retail, Financial Services, and Healthcare
- Hands-on experience with LLM architectures, including Retrieval-Augmented Generation (RAG), single and multi-agent systems, and custom router solutions
- Experience with API development frameworks (FastAPI, Django REST framework) to support scalable data services
What Will Set You Apart
- Microsoft MVP.
- Strong software engineering experience.
- Experience in professional services organizations.
- Demonstrable thought leadership through an active GitHub, blog posts, or publications.
- LLM experience: RAG, single and multi-agent, custom routers.
- Azure Fabric implementation.
- Scala, Java, Terraform.
Concurrency is committed to revolutionizing consulting by embracing diverse perspectives, fostering collaboration, and promoting resilience. Our workplace is both innovation-driven and enjoyable. We provide flexible work schedules, competitive compensation, and comprehensive benefits for our employees and their families. Additionally, all team members have access to recognition programs, comprehensive training opportunities to thrive both professionally and personally.