Looking for a Senior Data Engineer to build reliable data systems, shape how data is collected/used for ML systems, real-time product experiences, and analytics.
Responsibilities
Design and build scalable batch and streaming data pipelines
Build real-time data infrastructure used by production ML inference
Develop feature pipelines and feature serving for machine learning models
Create reliable datasets for analytics, experimentation, and business intelligence
Develop data models and infrastructure that support product and engineering teams
Lead the development of physics-based machine learning models and infrastructure, collaborating with simulation engineers and research scientists to deliver production-grade solutions.
Responsibilities
Work closely with simulation engineers and research scientists
Transform prototype implementations to robust production-grade model implementations, libraries and tooling
Work with multi-GPU/multi-node distributed systems for training and inference
Optimize models and pipelines at all levels
Design and build scalable infrastructure for end-to-end ML applications on cloud
The AI / ML DevOps Engineer designs, develops, deploys, and supports scalable machine learning solutions that enable advanced analytics and AI capabilities across HonorHealth.
Responsibilities
Design and implementation of the environment that deploys scalable AI/ML solutions, including predictive models, large language model use cases, and agentic workflows that support clinical, operational, and business objectives.
Develops and maintains end-to-end machine learning and RAG pipelines supporting data ingestion, application feature engineering, training, evaluation, deployment, and lifecycle management.
Architects and supports production-grade DevOps practices, including CI/CD, model versioning, automated testing, monitoring, alerting, retraining, and rollback strategies.
Deploys and manages AI/ML applications in cloud environments, ensuring solutions are secure, reliable, performant, and operationally supportable.
Implements observability and performance evaluation practices to manage compute resource utilization, performance, and cost efficiency.
Lead the engineering organization responsible for defining, building, and delivering complex data and AI infrastructure software.
Compensation
The target salary range for this position is 266,050 - 396,000 USD.
Responsibilities
Own end-to-end engineering delivery, from design through implementation, testing, and production reliability.
Provide deep technical leadership, design reviews, and guidance on performance, scalability, security, and system tradeoffs, including accelerated computing where relevant; partner with senior architects to turn technical direction into robust products.
Translate product priorities and customer commitments into realistic engineering plans with clear owners, milestones, dependencies, quality gates, and measurable outcomes.
Build a disciplined execution culture with high engineering velocity, transparent progress, timely decisions, and accountability for commitments.
Recruit, coach, and retain exceptional engineers and engineering leaders; define team structures, clarify decision rights, develop successors, and raise the technical bar.
Senior Data Architect responsible for defining, governing, and evolving the Asset Management Group data architecture across analytical, operational, and digital domains.
Locations (2)
Cleveland, Ohio, United States
Pittsburgh, Pennsylvania, United States
Compensation
Base Salary: $112,000.00 – $228,800.00
Responsibilities
Define and maintain target-state architecture for domain analytical and operational data platforms
Lead architecture efforts to evolve legacy data platforms toward modern lakehouse and open-data architectures
Define migration strategies for existing Hadoop-based analytical environments and data workloads
Evaluate emerging technologies and industry trends to improve scalability, interoperability, operational efficiency, and long-term sustainability
Drive adoption of modern data management practices, storage architectures, metadata strategies, and platform operating models
Lead the engineering organization responsible for defining, building, and delivering complex data and AI infrastructure software.
Compensation
The target salary range for this position is 266,050 - 396,000 USD.
Responsibilities
Own end-to-end engineering delivery, from design through implementation, testing, and production reliability.
Provide deep technical leadership, design reviews, and guidance on performance, scalability, security, and system tradeoffs.
Translate product priorities and customer commitments into realistic engineering plans with clear owners, milestones, dependencies, quality gates, and measurable outcomes.
Build a disciplined execution culture with high engineering velocity, transparent progress, timely decisions, and accountability for commitments.
Recruit, coach, and retain exceptional engineers and engineering leaders; define team structures, clarify decision rights, develop successors, and raise the technical bar.
Design, implement, and optimize sophisticated machine learning models in Banking domain for Credit Risk modeling.
Responsibilities
Design, implement, and optimize sophisticated machine learning models in Banking domain for Credit Risk modeling.
Enable us to uncover meaningful patterns, trends, and insights from data, ultimately solving analytical use cases.
Utilize sophisticated algorithms and methodologies to refine and improve the performance of credit risk/ marketing mix models, enabling accurate predictions and actionable outputs for analytical use cases.
Stay updated on the latest machine learning advancements, actively identifying and integrating cutting-edge techniques to continuously improve our models and address diverse analytical use cases.
Provide data-driven insights and recommendations that support decision-making processes and enable us to overcome analytical hurdles.
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