Together We Talent
Job Description
GenAI/ML Architect
Pittsburgh, PA (Onsite) Contract $57/hour
Design and lead enterprise-scale AI and ML architecture to power innovation, automation, and data-driven transformation across industries.
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
Bachelor's 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.
Pittsburgh, PA (Onsite) Contract $57/hour
Design and lead enterprise-scale AI and ML architecture to power innovation, automation, and data-driven transformation across industries.
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
Bachelor's 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.