Operate, improve, and extend ShipHero’s data infrastructure. Support engineering teams in enhancing the performance of reports, searches, and other data services. Be part of the Platform Team to address performance and reliability challenges in our data systems.
Help to design, build, and deploy intelligent models and ML-powered workflows that solve real-world challenges at scale, working closely with data engineers, product owners, and AI specialists to turn ideas into production-ready solutions, embedding AI seamlessly into business processes.
We are seeking a Data Engineer with deep experience in managing and processing high-volume IoT data to enable the cloud-based training of machine learning models that power real-time inference on edge devices. You will architect and maintain cloud-based data infrastructure and pipelines that support ML workflows for training, validation, and deployment of machine learning models optimized for deployment in edge environments.
We are seeking a talented and motivated tech data engineer to join our team who will be responsible for designing, developing, and maintaining our data infrastructure and developing backend systems and solutions that support real-time data processing, large-scale event-driven architectures, and integrations with various data systems.
As a Data Engineering Manager, you will be part of the Data Engineering team. Your role involves defining the team’s roadmap based on business priorities, contributing technically to the design and implementation of end-to-end data solutions, and collaborating with stakeholders to enable data-driven decision making across the company.
As an Analytics Engineer within the Biostatistics team, you'll establish and manage robust, scalable pipelines for data analysis and infrastructure, optimize Posit environments on AWS, and champion reproducible analytic workflows. Aside from working closely with your fellow Biostatistics teammates, you’ll collaborate with AI platform, AI model development, and platform engineering teams.
As a Sr Data and Insight Engineer, you will play a pivotal role in ensuring data accuracy, reliability, and accessibility, enabling the organization to derive meaningful insights and make informed decisions. You will collaborate with cross-functional teams to understand data requirements, develop efficient data pipelines, and utilize expertise in Python and AI to enhance data processing and analysis capabilities, working with platforms such as AEP, Google Cloud, and AWS.
As an experienced Cloud Data Architect & Engineer with AWS and healthcare data systems, you will report to Experian Health. You will lead the migration of legacy healthcare data systems to AWS, and build secure, scalable ETL/ELT pipelines using AWS Glue, Lambda, Step Functions, and Athena. You will integrate healthcare data from EHRs, HL7/FHIR APIs, claims, and IoT devices into centralized data lakes.
Work on large-scale solutions for mining challenging driving scenarios to boost learned model performance across various autonomous driving tasks. Collaborate with ML infrastructure teams and contribute to workflows for continuous learning through iterative mining, error analysis, training and deployment. Research and develop methods for extracting uncertainty and informativeness indicators to automatically mine for challenging scenes and analyze model performance.
The Senior Manager for Cytiva is responsible for leading a team of AI/ML professionals, providing technical guidance and apply strategic vision to drive projects that enhance business outcomes. This position is part of the Data and Analytics Team located in Poland and will be on-site in Krakow or remote across Poland.