AI Architect - Houston, TX, United States - TEKsystems

Description

Description:

MUST HAVE experience architecting and implementing an enterprise-wide, scalable MLOps platform in a multi-product environment.

This person should have a strong technical understanding and the ability to sketch out a detailed architectural diagram based on a given framework. The AI Architect will be responsible for defining the organization's ML Ops tech stack and ensuring the ability to build and deploy models at scale in a standardized fashion.

100% remote (may be asked to travel in for important meetings on occasion, approved expenses will be reimbursed).

Our client is expanding their Enterprise MLOps and Analytics Platform capabilities to enhance support for MLOps and ModelOps, facilitating the operationalization, monitoring, and management of in-house and third-party AI solutions. This expansion is integral to strengthening their overall AI Governance framework.

They are actively seeking an AI Architect to lead and establish a team of MLOps engineers tasked with designing and enhancing our Enterprise MLOps and Analytics Platform. The Principal MLOps Engineer will be pivotal in managing the operations and overseeing the entire MLOps and ModelOps tech stack, ensuring a robust end-to-end lifecycle management and governance of machine learning models throughout the organization. As the principal figure in MLOps, this role involves defining the team dynamics, shaping the culture, and implementing processes and technologies essential for supporting ML solutions within our hybrid data and compute framework. Collaborating closely with IT, cybersecurity, and compliance teams, the AI Architect will be instrumental in creating a secure and compliant infrastructure for the scalable management of AI/ML models.

Key responsibilities include:

Lead and mentor a team of MLOps Engineers to create a scalable MLOps and Analytics platform within a hybrid compute environment, including Kubernetes and Azure.

Design, implement, and oversee CI/CD pipelines, ensuring the infrastructure is conducive to ML model training, deployment, and monitoring while upholding security, scalability, reliability, and performance.

Develop, refine, and standardize Model Governance integrations, performance tracking for bias and impact, and a model catalog with standardized scorecards and deployments.

Innovate automated validation, deployment, observability, and management tools for scalable and reproducible AI solutions.

Design fallback and decommissioning strategies for AI solutions to ensure operational continuity.

Deliver training on AI solutions to enhance understanding and application across the organization.

Engage with technology trends, contribute to tech communities, and foster a culture of continuous learning and innovation.

Technical Expertise

Demonstrate deep understanding of the AI/ML Platform infrastructure and cloud architecture.

Experience developing and deploying AI/ML algorithms into production.

Strong proficiency in Python and C++ or C#, complemented by experience with machine learning libraries such as TensorFlow, PyTorch, and Scikit-learn.

Knowledge of DevOps practices, CI/CD pipelines, including tools like Azure DevOps or Git Actions.

Proficiency in working with containers such as Docker and container orchestration systems like Kubernetes. Familiarity with process orchestration/DAGs tools.

Experiences with AI/ML algorithms, packages (e.g. scikit, PyTorch, tensor flow).

Experience with data, code, and model artifact management processes and MLOps tools.

Experience with on-premises, cloud-based, and hybrid computing environments, as well as cloud-native tools and services.

Knowledge of ISO standards for software and/or AI development lifecycle management.

Analytical Skills

Experience with project management methodologies (e.g. SAFe agile, PRINCE2, Lean methodology)

Deep understanding of the AI/ML Model Lifecycle Management.

Proficient in decision-making, problem-solving, and the successful execution of AI/ML solutions in a healthcare environment.

Manage AI/ML projects throughout their lifecycle, ensuring timely delivery, budget adherence, and quality standards compliance.

Experience leading an ML engineering and/or data scientist team focused on developing, deploying, and maintaining production-ready models.

Experience working closely with third-party vendors and partners to integrate new AI solutions into existing infrastructure and workflows.

Experience implementing risk identification and mitigation strategies, including contingency planning, to prevent project delays and complications.

Preference for working knowledge of hospital workflows.

Preference for experience with healthcare data privacy and security protocols, such as HIPAA.

Preference for experience with flowcharts, business process models, mapping tools, data flow diagrams, and process flow diagrams.

Professionalism: Oral and Written

Work closely with data scientists, ML engineers, software engineers, and other stakeholders to understand requirements and integrate machine learning models into the overall system.

Create and maintain comprehensive documentation for CI/CD pipelines, deployment processes, and infrastructure configurations.

Experience reporting on project progress, impact, and risks to leadership and stakeholders, providing strategic advice to help prioritize AI/ML solutions use-cases.

Experience stakeholder management to drive adoption, address concerns, and prioritize solution support.

Other duties as assigned

Education Required: Bachelor's degree in Computer Science, Software Engineering, Data Science, Physics, Math & Statistics, or another related engineering discipline.

Preferred Education: Master's Level Degree

Experience Required : Seven years of experience in machine learning engineering, data science, data engineering, and/or software engineering. With Master's degree, five years' experience required. With PhD, three years of experience required.

Preferred Experience: Experience working on production quality healthcare focused machine learning solutions.

Proficiency in architecting, implementing, and using MLOps solutions.

Experience Level:

Expert Level

About TEKsystems:

We're partners in transformation. We help clients activate ideas and solutions to take advantage of a new world of opportunity. We are a team of 80,000 strong, working with over 6,000 clients, including 80% of the Fortune 500, across North America, Europe and Asia. As an industry leader in Full-Stack Technology Services, Talent Services, and real-world application, we work with progressive leaders to drive change. That's the power of true partnership. TEKsystems is an Allegis Group company.

The company is an equal opportunity employer and will consider all applications without regards to race, sex, age, color, religion, national origin, veteran status, disability, sexual orientation, gender identity, genetic information or any characteristic protected by law.