GenAIML Architect
Share
Job Location:
Hourly Salary:
Experience Required:
Posted on:
30+ days ago
Vacancies:
1 Vacancy
Job Summary
GenAI/ML Architect
A leading global technology firm is seeking a GenAI/ML Architect to drive the design and deployment of advanced AI and machine learning solutions across complex enterprise environments. This role combines deep technical expertise in ML architecture cloud platforms and MLOps with a strategic understanding of how to apply Generative AI to real-world business challenges.
This position is 100% onsite in Pittsburgh PA.
Position Overview
The GenAI/ML Architect will oversee the end-to-end design development and implementation of machine learning and AI systems ensuring scalability performance and compliance with enterprise standards. This role requires 12 years of experience in AI/ML engineering including at least 3 years in an architectural capacity and a proven ability to lead cross-functional teams in delivering production-grade ML systems.
Key Responsibilities
Architect and Design: Build end-to-end AI/ML architectures that support large-scale data-intensive applications.
Lead and Mentor: Guide teams of data scientists and engineers in developing training and deploying ML models and pipelines.
Generative AI Integration: Implement and optimize GenAI solutions including NLP deep learning and reinforcement learning models.
MLOps & Automation: Define and enforce best practices for model deployment versioning monitoring retraining and governance.
Infrastructure Optimization: Design scalable data pipelines and distributed systems for high-performance model training and inference.
Innovation & Evaluation: Assess and implement emerging AI technologies frameworks and tools to accelerate innovation.
Compliance & Ethics: Ensure AI systems align with governance data privacy and ethical AI principles.
Cloud Deployment: Deploy and manage AI/ML workloads on AWS GCP and Azure leveraging microservices and containerized environments.
Cross-Functional Collaboration: Partner with business data and infrastructure teams to align AI solutions with strategic enterprise objectives.
Requirements
Required Qualifications
Bachelors degree in Computer Science Engineering or a related technical field.
12 years of experience in AI/ML engineering with 3 years in an architectural role.
Proven expertise in machine learning frameworks such as TensorFlow PyTorch and Scikit-learn.
Hands-on experience with Generative AI NLP deep learning and reinforcement learning.
Proficiency in Python Java or C for model development and integration.
Strong knowledge of MLOps tools such as Kubeflow MLflow Airflow Docker and Kubernetes.
Experience with big data technologies (Spark Hadoop) and distributed computing frameworks.
Skilled in building and deploying models on cloud platforms (AWS GCP Azure).
Familiarity with Edge AI IoT and real-time inference pipelines.
Understanding of ethical and responsible AI frameworks.
Experience applying Agile methodologies for rapid iterative delivery.
Preferred Experience & Skills
Background in Life Sciences Healthcare Energy or Utilities industries.
Experience with AI-driven digital transformation and enterprise AI strategy.
Strong analytical leadership and mentoring skills.
Excellent communication and stakeholder management abilities.
Required Skills:
2 years of experience in AI/ML engineering including at least 3 years in an architectural role Extensive experience in AI/ML model development deployment and lifecycle management. Expertise in machine learning frameworks (TensorFlow PyTorch Scikit-learn) and cloud platforms (AWS GCP Azure). Strong programming skills in Python Java or C Proficiency in MLOps tools (Kubeflow MLflow Airflow Docker Kubernetes). Deep understanding of distributed computing big data technologies (Spark Hadoop) and scalable data pipelines. Experience with NLP deep learning reinforcement learning generative AI Experience in AI-driven business transformation and enterprise AI strategies. Familiarity with edge AI IoT or real-time AI processing. Knowledge of ethical AI frameworks and responsible AI principles. Strong problem-solving skills and ability to mentor AI/ML teams. Experience in agile development methodologies to deliver solutions and product features.
Required Education:
Bachelors degree in computer science computer engineering or a related engineering field. Masters degree preferred.
Company Industry
IT Services and IT Consulting
Key Skills
- APIs
- Pegasystems
- Spring
- SOAP
- .NET
- Hybris
- Solution Architecture
- Service-Oriented Architecture
- Adobe Experience Manager
- J2EE
- Java
- Oracle
