Develop scalable automatic proofreading methods leveraging barcode and shape information for optical connectomics datasets.
Responsibilities
Contribute to developing innovative ML approaches for automatic proofreading of segmentations in large PB-scale optical connectomics volumes, leveraging shape and barcode information
Own the deployment of scalable workflows to ingest large connectomic datasets into standard proofreading software (WebKnossos, CAVE)
Collaborate with academic and industry experts on building and extending tools for automated proofreading and interactive visualization
Develop, implement, and evaluate scalable pipelines for synapse detection and partner assignment in large-scale optical connectomics datasets, integrating morphological and protein labeling information
Identify and build ML-based image processing tools that remove key bottlenecks in our data processing and analysis pipeline
Requirements
Ph.D. in computer science, machine learning, applied math, computational biology or a related field in science and/or engineering or Ph.D.-equivalent publication history
Nice to have: Graph ML methods (GNNs, Transformers, Pointnets)
Nice to have: Sequence ML methods
Nice to have: Point based ML methods
Nice to have: Processing large chunked data (Zarr)
Develop and enhance the Scams Workbench platform, an application used by analysts to detect, investigate and action scam events in real time.
Locations (2)
Sydney, New South Wales, Australia
Melbourne, Victoria, Australia
Compensation
Competitive remuneration and employee discounts. Make life easier (and more affordable) with $80 monthly credit and 25% off Optus products and unique shopping discounts with our retail partners.
Responsibilities
Build and enhance the Scams Workbench application, delivering an intuitive and high-performing experience for scam analysts
Design and develop frontend components and workflows that enable efficient investigation and management of scam events
Build and maintain backend services and APIs that connect application features to data, machine learning outputs and detection engines
Develop secure, scalable and reliable application functionality that supports a high-volume production environment
Partner with analysts and business stakeholders to understand requirements and continuously improve the user experience
Join the Supply Data Solutions team to improve infrastructure, data pipelines, and translate business requirements into software solutions, focusing on building and maintaining scalable and reliable data deliverables like the Pricing Engine.
Locations (2)
Hamburg, Hamburg, Germany
Berlin, Germany
Responsibilities
Develop practical optimization and algorithmic solutions for business challenges
Build and maintain infrastructure and orchestration pipelines (using AWS Lambda, Batch, Step Functions)
Ensure services are up and running
Write efficient Python code
Manage CI/CD pipelines and infrastructure deployments using GitLab and CloudFormation
Applying understanding of company products and services and introducing technology innovations with respect to functionality, performance, reliability, and scalability
Designing, developing, and maintaining the machine learning infrastructure that powers the company
Performing research and development of machine learning algorithms to expand product capabilities
Participating in building new experiences, improving existing products, ensuring quality assurance test designs and contributing to test systems architecture discussions
Requirements
Master’s degree in Computer Science, Engineering, Mathematics, or a related field
Lead the implementation and administration of CyberArk Privilege Cloud and Endpoint Privilege Manager solutions, managing integrations, incident processes, automation, and global support.
Responsibilities
Lead the deployment and management of CyberArk Privilege Cloud and Endpoint Privilege Manager solutions.
Design and implement EPM policies and procedures to ensure effective endpoint security.
Manage integrations related to PAM and EPM during mergers and acquisitions.
Oversee incident, change, and problem management processes.
Develop automation scripts and reporting tools to enhance operational efficiency.
Requirements
Nice to have: CyberArk Sentry certification
Nice to have: Certified Delivery Engineer certification
Nice to have: Privilege Cloud SaaS operations
Nice to have: automation and reporting tools specific to CyberArk
Nice to have: designing EPM policies and administration
As the Ops Data Engineer, you will support ANZ Operations and the wider supply chain by driving efficiency, managing operational complexity, and improving decision-making through data engineering, technical automation, and practical AI-powered solutions.
Compensation
Competitive salary & employee benefits - 70% off HelloFresh
Responsibilities
Scale and optimize data pipelines, data quality, accessibility, and database efficiency to support reporting, automation, and AI workflows
Design, build, deploy, and maintain practical AI-powered applications, tools, and workflows that eliminate manual effort and streamline supply chain processes
Partner closely with business and operational stakeholders across Australia and New Zealand to translate business requirements into high-value technical solutions
Promote data and AI literacy across teams, championing the responsible and effective adoption of approved AI technologies
Implement robust engineering best practices, including version control, testing, lifecycle monitoring, and ongoing support for all deployed pipelines and applications
Requirements
Bachelor’s degree in Computer Science, IT, Engineering, or a related field (or equivalent practical experience)
Design, implement, and test innovative guidance, navigation, control, and perception algorithms in flight software for highly autonomous deep space missions
Develop 6-DOF dynamics simulation models used for GNC systems analysis and validation
Help push flight software to the edge in Monte Carlo and Hardware-in-the-loop testing and contribute fixes and performance improvements
Review algorithms and software contributed by GNC / flight software engineers
Requirements
Bachelor’s Degree in a STEM field
Master’s Degree in a STEM field focusing on dynamics & control
Nice to have: experience operating and/or developing spacecraft
Design, build, and maintain scalable data pipelines and integration solutions using Snowflake, DBT, Matillion, AWS, SQL, Python, and modern ETL/ELT technologies.
Compensation
$137,610.00 - $168,190.00
Responsibilities
Design, build, and maintain scalable data pipelines and integration solutions
Develop, optimize, and support enterprise data products
Design and maintain Power BI semantic models, datasets, dashboards, and reporting solutions
Translate business and technical requirements into data models
Partner with business stakeholders, product owners, architects, and engineers
Requirements
Bachelor's degree in Computer Science, Information Systems, Data Engineering, Software Engineering, or a related discipline
Apply SRE core tenets of measurement (SLI/SLO/SLA), eliminate toil, and reliability modeling.
Responsibilities
Apply SRE core tenets of measurement (SLI/SLO/SLA), eliminate toil, and reliability modeling
Enable and educate development teams on industry best practice design patterns, ways of working and operational knowledge to ensure platform continuity
Develop and architect solutions to infrastructure and operational aspects of new products and feature sets
Assist with go/no go preplanning, verification/validation, and review of existing and new product/services
Proactively analyze data and test the integrity of network/systems to ensure production applications and services are operating optimally
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