Python programmer állások IX. kerületben (ai és automatizáció)

• ETL Framework Development
• Pipeline Optimization
• Modern Engineering Practices Application
• Infrastructure And Automation

• Building and maintaining simulation environments for mobile robotic perception and navigation
• Developing and integrating robotic behaviours and learning pipelines for reinforcement learning and motion planning in complex outdoor environments

• Dashboard development for sustainability data visualization
• Data integration from internal databases, external APIs, and third-party platforms
• Client reporting with customized visual analytics solutions
• Data analysis to identify trends, patterns, and insights supporting sustainability initiatives

• AWS-based cloud architecture design and technical decision making for SaaS, PaaS, web application, and enterprise cloud environments
• Infrastructure as Code solution design and implementation using Terraform, AWS CloudFormation, or Pulumi

• Research, development, implementation, and testing of artificial intelligence algorithms to improve the quality and robustness of the static world model in automated vehicles
• Focus on road structure including lanes, curbs, and drivable trajectories

• Creation and preparation of 3D assets, environments, and scene layouts for Omniverse and OpenUSD workflows
• Assembly of digital-twin scenes for industrial, facility, product, or enterprise visualization use cases

• Automation and streamlining of fraud investigation processes
• Improvement of tooling for fraud investigations
• Creation of seamless experience for agents and customers during fraud investigations

• Setting the technical direction for AI-enabled platform
• Architecting secure, scalable, serverless systems on AWS
• Defining patterns and governance practices for multiple teams
• Guiding AI value addition across the stack
• Mentoring senior engineers
• Leading org-wide design decisions

• Design, development, and optimization of core ML models, especially in Computer Vision and Deep Learning
• Development of efficient, scalable training and inference pipelines
• Mentoring junior ML engineers, reviewing code and sharing best practices

• Configuration and evolution of enterprise AI platforms and orchestration components
• Implementation of platform capabilities and contribution to AI use case implementation
• Development of APIs, service components, and integration logic for AI-enabled solutions

Mastering Apache Spark and Databricks on AWS/Azure Delivering hands-on project work during bi-weekly sprint model Completing complex capstone projects Shadowing senior consultants on real-life engagements Delivering simulated projects Advising stakeholders and navigating requirements Contributing...

• Researching and designing new performance attribution models
• Collaborating with software developers to test and release new models into production
• Supporting existing performance attribution models in production
• Developing and improving model quality control and model performance monitoring

• Build and maintain data models and pipelines primarily using AI coding tools
• Build and improve agentic coding workflows to accelerate data modeling and testing
• Partner with stakeholders to surface conflicting metric definitions and run alignment workshops

• End-to-end AI solution ownership from problem definition through prototype validation and production support
• Partnership with product managers and business stakeholders to translate real-world problems into data science and AI initiatives

• End-to-end software release process management including branch management, software version control, release note documentation, and communication with collaborators
• Release automation enhancement through CI/CD pipeline improvements and defect logging and tracking

• Translation of AI opportunities into executable technical solution designs
• Definition of integration approaches with IT and business application/data owners
• Implementation of AI use cases using enterprise AI services and LLM APIs

• Design and implement automation of data platform
• Develop and maintain data platform infrastructure using Terraform
• Implement and manage CI/CD pipelines for automation of data and AI processes and pipelines
• Automate provisioning, configuration, and monitoring of resources in AWS

• Design, develop, and implement complex and scalable data solutions on the AWS cloud platform
• Design, build, and optimize data pipelines to ensure efficiency and reliability
• Write clean, efficient, and maintainable SQL and Python code
• Develop and maintain shell scripts to support automation

• Build And Operate Multi-Cluster Containerized Environments Across Cloud Platforms
• Create End-To-End CI/CD Pipelines For Cloud-Native Applications And Machine Learning Workloads
• Lead Cost-Optimization And FinOps Initiatives For GPU, Storage And Data-Egress Spend

• Design and implement modern data architectures and lakehouse solutions
• Provide technical leadership throughout the project lifecycle
• Collaborate with business stakeholders
• Create effort estimations and provide technical expertise during the pre-sales phase
• Mentor 3-6 person project teams