Machine Learning Architect

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 Service Now 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.

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.

• 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.

• 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 Git Hub contributions, blog posts, or technical talks on Linked In or You Tube 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 Dev Ops 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

• Technical Expertise:
• Languages/Frameworks
  :
  Python, working knowledge of Scala, Java, or PySpark. Pandas, numpy, sklearn, Lang Chain
• Azure
  :
  Deep knowledge of Azure's ecosystem including Azure ML, Data…