MLOps Platform Architect

Tiger Analytics

69d

About The Position

Tiger Analytics is a global leader in AI and advanced analytics consulting, empowering Fortune 1000 companies to solve their toughest business challenges. We are on a mission to push the boundaries of what AI can do, providing data-driven certainty for a better tomorrow. Our diverse team of over 6,000 technologists and consultants operates across five continents, building cutting-edge ML and data solutions at scale. Join us to do great work and shape the future of enterprise AI. We are seeking a highly experienced and technically proficient MLOps Architect to lead the design, development, and implementation of our next-generation machine learning platforms. This role requires a unique combination of deep technical expertise in MLOps, a strong background with cloud technologies, and the ability to effectively manage complex client relationships. The ideal candidate will be a strategic thinker who can translate business needs into scalable and robust MLOps solutions.

Requirements

• 13+ years of professional experience in data engineering, machine learning, or software architecture, with a significant focus on MLOps.
• Proven, hands-on experience in building and deploying production-grade MLOps platforms.
• Demonstrated ability to handle challenging client management scenarios, acting as a trusted advisor and problem-solver.
• Strong expertise with the Databricks ecosystem for building scalable data and ML workflows.
• Extensive experience with at least one major cloud platform (AWS, GCP, or Azure) and its MLOps-related services.
• Deep understanding of the entire machine learning lifecycle, from data ingestion and feature engineering to model serving and monitoring.
• Proficiency in programming languages such as Python and experience with relevant ML libraries.

Nice To Haves

• A background in traditional software development or software engineering principles.
• Experience with containerization (Docker) and orchestration (Kubernetes).
• Certification in a relevant cloud platform (e.g., AWS Certified Machine Learning - Specialty, Google Cloud Professional Machine Learning Engineer).

Responsibilities

• Architect and Build MLOps Platforms: Lead the design and development of end-to-end MLOps platforms from the ground up, ensuring they are scalable, reliable, and secure.
• Client Management: Act as a primary technical point of contact for clients, managing expectations, communicating complex technical concepts clearly, and navigating challenging project requirements to ensure successful outcomes.
• Technical Leadership: Drive the technical vision for the MLOps practice, establishing best practices for model development, deployment, monitoring, and governance.
• Databricks Expertise: Leverage extensive, hands-on experience with Databricks to build and optimize data and machine learning pipelines.
• Cloud Integration: Design and implement solutions on one or more major cloud platforms (AWS, GCP, or Azure), utilizing their native services for data, compute, and machine learning.
• Collaboration: Work closely with cross-functional teams, including data scientists, software engineers, and business stakeholders, to deliver integrated and high-value solutions.

Benefits

• Significant career development opportunities exist as the company grows.
• The position offers a unique opportunity to be part of a small, fast-growing, challenging and entrepreneurial environment, with a high degree of individual responsibility.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Number of Employees: 1,001-5,000 employees