GenAI/ML Architect
Together We TalentGenAI/ML Architect<\/b>
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A leading global technology firm is seeking a GenAI/ML Architect<\/b> 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.
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This position is 100% onsite<\/b> in Pittsburgh, PA.<\/b>
<\/p>Position Overview<\/b>
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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.
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Key Responsibilities<\/b>
<\/h3>Architect and Design:<\/b> Build end -to -end AI/ML architectures that support large -scale, data -intensive applications.
<\/p><\/li>Lead and Mentor:<\/b> Guide teams of data scientists and engineers in developing, training, and deploying ML models and pipelines.
<\/p><\/li>Generative AI Integration:<\/b> Implement and optimize GenAI solutions, including NLP, deep learning, and reinforcement learning models.
<\/p><\/li>MLOps & Automation:<\/b> Define and enforce best practices for model deployment, versioning, monitoring, retraining, and governance.
<\/p><\/li>Infrastructure Optimization:<\/b> Design scalable data pipelines and distributed systems for high -performance model training and inference.
<\/p><\/li>Innovation & Evaluation:<\/b> Assess and implement emerging AI technologies, frameworks, and tools to accelerate innovation.
<\/p><\/li>Compliance & Ethics:<\/b> Ensure AI systems align with governance, data privacy, and ethical AI principles.
<\/p><\/li>Cloud Deployment:<\/b> Deploy and manage AI/ML workloads on AWS, GCP, and Azure<\/b>, leveraging microservices and containerized environments.
<\/p><\/li>Cross -Functional Collaboration:<\/b> Partner with business, data, and infrastructure teams to align AI solutions with strategic enterprise objectives.
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Requirements<\/h3>
Required Qualifications<\/b>
<\/p>Bachelor’s degree in Computer Science, Engineering, or a related technical field.
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12+ years of experience<\/b> in AI/ML engineering, with 3+ years in an architectural role.<\/b>
<\/p><\/li>Proven expertise in machine learning frameworks<\/b> such as TensorFlow, PyTorch, and Scikit -learn.<\/b>
<\/p><\/li>Hands -on experience with Generative AI, NLP, deep learning, and reinforcement learning.<\/b>
<\/p><\/li>Proficiency in Python, Java, or C++<\/b> for model development and integration.
<\/p><\/li>Strong knowledge of MLOps tools<\/b> such as Kubeflow, MLflow, Airflow, Docker, and Kubernetes.<\/b>
<\/p><\/li>Experience with big data technologies<\/b> (Spark, Hadoop) and distributed computing frameworks.<\/b>
<\/p><\/li>Skilled in building and deploying models on cloud platforms<\/b> (AWS, GCP, Azure).
<\/p><\/li>Familiarity with Edge AI, IoT, and real -time inference pipelines.<\/b>
<\/p><\/li>Understanding of ethical and responsible AI<\/b> frameworks.
<\/p><\/li>Experience applying Agile methodologies<\/b> for rapid, iterative delivery.
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Preferred Experience & Skills<\/b>
<\/p>Background in Life Sciences, Healthcare, Energy, or Utilities<\/b> industries.
<\/p><\/li>Experience with AI -driven digital transformation<\/b> and enterprise AI strategy.
<\/p><\/li>Strong analytical, leadership, and mentoring skills.
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Excellent communication and stakeholder management abilities.
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Architect and Design:<\/b> Build end -to -end AI/ML architectures that support large -scale, data -intensive applications. Lead and Mentor:<\/b> Guide teams of data scientists and engineers in developing, training, and deploying ML models and pipelines. Generative AI Integration:<\/b> Implement and optimize GenAI solutions, including NLP, deep learning, and reinforcement learning models. MLOps & Automation:<\/b> Define and enforce best practices for model deployment, versioning, monitoring, retraining, and governance. Infrastructure Optimization:<\/b> Design scalable data pipelines and distributed systems for high -performance model training and inference. Innovation & Evaluation:<\/b> Assess and implement emerging AI technologies, frameworks, and tools to accelerate innovation. Compliance & Ethics:<\/b> Ensure AI systems align with governance, data privacy, and ethical AI principles. Cloud Deployment:<\/b> Deploy and manage AI/ML workloads on AWS, GCP, and Azure<\/b>, leveraging microservices and containerized environments. Cross -Functional Collaboration:<\/b> Partner with business, data, and infrastructure teams to align AI solutions with strategic enterprise objectives. Required Qualifications<\/b> Bachelor’s degree in Computer Science, Engineering, or a related technical field. 12+ years of experience<\/b> in AI/ML engineering, with 3+ years in an architectural role.<\/b> Proven expertise in machine learning frameworks<\/b> such as TensorFlow, PyTorch, and Scikit -learn.<\/b> Hands -on experience with Generative AI, NLP, deep learning, and reinforcement learning.<\/b> Proficiency in Python, Java, or C++<\/b> for model development and integration. Strong knowledge of MLOps tools<\/b> such as Kubeflow, MLflow, Airflow, Docker, and Kubernetes.<\/b> Experience with big data technologies<\/b> (Spark, Hadoop) and distributed computing frameworks.<\/b> Skilled in building and deploying models on cloud platforms<\/b> (AWS, GCP, Azure). Familiarity with Edge AI, IoT, and real -time inference pipelines.<\/b> Understanding of ethical and responsible AI<\/b> frameworks. Experience applying Agile methodologies<\/b> for rapid, iterative delivery. Preferred Experience & Skills<\/b> Background in Life Sciences, Healthcare, Energy, or Utilities<\/b> industries. Experience with AI -driven digital transformation<\/b> and enterprise AI strategy. Strong analytical, leadership, and mentoring skills. Excellent communication and stakeholder management abilities.
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