GenAI/ML Architect Pittsburgh, PA $$$ bonus
GenAI/ML Architect Pittsburgh, PA $$$ bonus
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Salary Not Disclosed
1 Vacancy
Job Description
GenAI/ML Architect machine learning frameworks (TensorFlow PyTorch Scikit-learn) and cloud platforms (AWS GCP Azure) MLOps tools (Kubeflow MLflow Airflow Docker Kubernetes)
If you post this job on a job board please do not use company name or salary. Experience level: Mid-senior Experience required: 10 Years Education level: Bachelors degree Job function: Information Technology Industry: Information Technology and Services Pay rate : $57 per hour Total position: 1 Relocation assistance: No Visa sponsorship eligibility: No
Role GenAI/ML Architect
Business Vertical: Life Sciences Health Care Energy Resources and Utilities
Responsibility:
Design and architect end-to-end AI/ML solutions ensuring scalability security and efficiency.
Guide data scientists and engineers in developing training and deploying machine learning models.
Define best practices for MLOps including model versioning monitoring and retraining strategies.
Develop AI frameworks and reusable components to accelerate AI adoption across the organization.
Collaborate with stakeholders to understand business requirements and align AI solutions accordingly.
Optimize data pipelines and AI infrastructure to support high-performance model training and inference.
Evaluate emerging AI technologies and recommend suitable tools frameworks and methodologies.
Ensure compliance with AI ethics governance and data privacy regulations.
Implement microservices architecture to build scalable and resilient software solutions.
Use Cloud platforms like AWS Azure to deploy and run software applications.
Key Skills:
12 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.
Employment Type
Full Time
