Python developer állások, munkák ai és automatizáció kategóriában

• Definition and improvement of metrics representing product performance and operations efficiency
• Data collection from multiple sources ensuring accuracy and completeness
• Data cleaning, organization, and transformation into usable formats for analysis

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• Build-from-zero applications powered by the HawkAI Engine
• Bridge machine learning models and real-time data pipelines into APIs and user interfaces
• Integrate AI-assisted development tools into software architecture and data integrity workflows

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• Design and evolve robust cloud-native services and platforms with end-to-end ownership from ideation and prototyping to deployment, monitoring, and iteration
• Influence technical direction without direct authority by identifying architectural pain points and improving engineering standards

• Contribution to the ID Verification ML team building in-house ML solutions
• Delivery of high-quality NodeJS, TypeScript and Python code with simplicity, performance and scalability in mind

• Developing scalable library software using modern tools and languages for various numerical method
• Performance tuning, optimization, and benchmarking of algorithms on various architectures

• Resource account igénylése és összekötése namespacekkel
• Resource accountba kerülő komponensek megvalósítása RDS, APIk, S3, MSK, cognito, SES, private link endpoint és endpoint service nonprod és prod környezeteken
• RICE API kapcsolatok kialakítása

• Definition and improvement of metrics reflecting product performance, service quality, and operational efficiency
• Analysis of client behavior and service processes to identify trends, bottlenecks, inefficiencies, and drivers of performance

• Design, build and deploy LLM-powered pipelines and autonomous agents
• Scope and deliver AI solutions in collaboration with stakeholders
• Set best practices around MLOps and production-grade AI
• Mentor developers and contribute to internal knowledge-sharing

• Lead implementation of AI, GenAI, ML, automation, and AI-powered applications.
• Translate solution designs and requirements into development plans and working software.
• Drive engineering delivery aligned with the target architecture.

• Delivery of software releases on schedule with defined scope and quality
• Transition to continuous delivery
• Ensuring reliable operation of the CI/CD pipelines and improving their efficiency
• Contribution to the test strategy and coordination of its execution

• Lead the architecture, design, and implementation of enterprise-scale web applications using modern frontend technologies
• Serve as the technical lead for UI development while remaining actively involved in coding, design reviews, and implementation

• Design, build, and deploy production-grade agentic AI and automation solutions that collect, validate, and quality-assure data at scale
• Engineer multi-agent orchestrations, data pipelines, MCP integrations, and API connections that power autonomous, end-to-end data workflows

• The CloudOps Engineer is responsible for availability for cloud platforms
• Respond, troubleshoot and resolve production alarms
• Communicate and troubleshoot operational issues supporting a complex environment
• Respond to cloud service outages and manage incident tickets

• Research, develop, implement, and test 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

• Shaping AWS-based cloud architectures and technical decisions for SaaS, PaaS, web application, and enterprise cloud environments
• Design and implementation of Infrastructure as Code solutions using Terraform, AWS CloudFormation, or Pulumi

• Design and implement data fabric architecture across heterogeneous data sources and platforms
• Develop scalable ETL/ELT pipelines for batch and real-time data integration
• Integrate structured and unstructured data from databases, APIs, SaaS applications, data lakes, and enterprise systems

• Design and update of data architecture to ensure a managed and automated process for data flows
• Optimization of data platforms (PostgreSQL) to ensure stable and timely data streams
• Building and continuous optimization of data ETL (Extract, Transform, Load) processes

• 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