Lead design and architecture of scalable AI/ML platforms, collaborate with stakeholders, evaluate AI technologies, implement infrastructure (cloud, containers, orchestration), ensure production reliability, governance, and optimization, mentor teams, and communicate architecture decisions.
Greetings Everyone
Who are we?
For the past 20 years, we have powered many Digital Experiences for the Fortune 500. Since 1999, we have grown from a few people to more than 4000 team members across the globe that are engaged in various Digital Modernization. For a brief 1 minute video about us, you can check https://youtu.be/uJWBWQZEA6o.
What will you do? What are we looking for?
Job Requisition for AI-ML Platform Tech Lead & Arch
Location: Charlotte NC
Key Responsibilities:
- Design and architect scalable AI platforms to develop, deploy AI solutions leveraging ML techniques and Deep Learning Techniques.
- Drive Joint Architecture Design to collaborating with business stakeholders, data scientists, engineering teams, product, and other key partners to gather functional, non-functional requirements for solving AI use case on the AI Platform
- Evaluate emerging technologies and tools in AI area and do fitment analysis to the Enterprise AI Platform and capabilities strategy.
- Define and implement AI/ML architecture best practices, frameworks, and standards.
- Lead AI/ML infrastructure setup, including cloud services selection, data pipelines, and model deployment.
- Ensure robustness, reliability, and scalability of AI/ML solutions in production environments.
- Design and implement data governance, security, and compliance measures for AI/ML platforms.
- Optimize AI/ML workflows for performance, cost efficiency, and resource utilization.
- Provide technical leadership and mentorship to AI/ML development teams.
- Communicate AI/ML architecture decisions and strategies to stakeholders and executives.
Key Requirements:
- Proven experience as an AI/ML platform architect
- Deep understanding of ML algorithms, Deep Learning architechture, models, and frameworks (e.g., TensorFlow, PyTorch, Scikit-Learn).
- Expertise in cloud platforms (e.g., GCP, Azure) and their AI services.
- Strong knowledge of Model development life cycle, software engineering principles, data engineering principles
- Experience with containerization and orchestration tools onprem and cloud (e.g., AKS, GKE, OpenShift Container Platform, Docker, Kubernetes) for deploying AI/ML models.
- Ability to design and optimize distributed computing systems for AI/ML workloads.
- Familiarity with DevOps practices, CI/CD pipelines, and automation tools in AI-ML contexts.
- Excellent problem-solving skills and ability to address complex technical challenges.
- Effective communication skills to collaborate with cross-functional teams and stakeholders.
What will make people successful in the team:
- Superior tech skills with coding to design to presentation
- On the feet thinking
- Outstanding communication skills
- 15 day rampup time
What you need to know about the NYC Tech Scene
As the undisputed financial capital of the world, New York City is an epicenter of startup funding activity. The city has a thriving fintech scene and is a major player in verticals ranging from AI to biotech, cybersecurity and digital media. It also has universities like NYU, Columbia and Cornell Tech attracting students and researchers from across the globe, providing the ecosystem with a constant influx of world-class talent. And its East Coast location and three international airports make it a perfect spot for European companies establishing a foothold in the United States.
Key Facts About NYC Tech
- Number of Tech Workers: 549,200; 6% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Capgemini, Bloomberg, IBM, Spotify
- Key Industries: Artificial intelligence, Fintech
- Funding Landscape: $25.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Greycroft, Thrive Capital, Union Square Ventures, FirstMark Capital, Tiger Global Management, Tribeca Venture Partners, Insight Partners, Two Sigma Ventures
- Research Centers and Universities: Columbia University, New York University, Fordham University, CUNY, AI Now Institute, Flatiron Institute, C.N. Yang Institute for Theoretical Physics, NASA Space Radiation Laboratory
