Python developer állások, munkák

Lead or participate in scoping the engagement, designing high-level architecture, defining subtasks, and project delivery schedules Deliver projects independently or within a mixed DS/DE team, often as technical lead Act as client-facing interface or SPOC to customers Provide ML/DS consultancy to...

Strengthen the completeness and reliability of the Group's Data Catalog (Data Galaxy) by conducting in depth analyses of data systems, governance frameworks, and business usage across the organization...

You define the AI system strategy for ADAS: model architectures, data flows, integration concepts: Grounded in methodological expertise and validated through technical feasibility assessments....

• Collaborate with cross-functional teams to define data requirements and ensure data quality
• Participate in monitoring, troubleshooting, and resolving data processing issues

Design and implement scalable, secure, and maintainable fullstack solutions for AI-enabled applications and platforms, including components that leverage LLMs to enable advanced user interactions and automation...

You will design and deliver end-to-end ADAS AI models such as object detection, behavior prediction, and trajectory planning - from data analysis and model design to SOP-ready release....

Your responsibilities will encompass overseeing the launch of the ESC in 2025, working closely with global AWS teams, and influencing the evolution of AWS services and technology. A typical day in this role involves collaborating with technology leaders, contributing to the enhancement of...

NEW SOLUTIONS EMERGE WHEN THINKING ISN'T HARD-WIRED. More than 90% of automotive innovations are based on electronics and software. That's why creative freedom and lateral thinking are so important in the pursuit of truly new solutions. Naturally, this includes flexible working models, so that our...

Cloud platform engineering: Develop and implement automation processes for the deployment and operation of cloud software and services using platform engineering, infrastructure as code (e.g., Terraform), and Kubernetes....

Architect and implement cloud-native data solutions using GCP (BigQuery, Dataflow, Pub/Sub, Dataproc, Cloud Composer, Cloud Storage) Lead the design and development of complex data pipelines and distributed processing frameworks that ensure scalability, performance, and operational reliability...

Visionary Domain Leadership: Architect and scale a high-performing multidisciplinary data organization. You will define the headcount strategy, career frameworks, and operational rhythms that allow Data Scientists and Engineers to deliver high-leverage outcomes....

Design, develop, and maintain components of the deployment stack and software kernels for AI compute platforms Optimize and implement core ML operators (e.g., GEMMs, convolutions, BLAS routines, SIMD kernels) Translate computational graphs from ML frameworks onto the underlying hardware Contribute...

Write and maintain clean, reusable, high-quality scripts that test product functionality automatically Contributing to bug finding and error reporting Contributing to the continuous improvement of automation frameworks/tools Preparing detailed test reports Take part in brainstorming to come up with...

• Collaborate with developers to establish processes that ensure delivery of quality backend and UI part of the platform.
• Write and run test cases based on real production work, and create scripts for automation.

Directly impact your team's tech scope: work hand in hand with PM and EM to manage product technical roadmaps and dependencies to minimise technical debt....

Lead and oversee the day-to-day operation of the Java backend team Continuously monitor overall project health by reviewing and improving development best practices and delivery processes across ongoing Java projects Take on line management responsibilities, supporting the team’s well-being, growth...

• Supporting the development and improvement of tools to quantify credit risk, analysing its results and proposing appropriate measures
• Supporting projects related to credit risk quantification, including data infrastructure and quality