Python developer állás, munka

• Support the management of user permissions across multiple tools and systems including AWS IAM
• Help maintain and improve security tooling including endpoint protection solutions and infrastructure monitoring tools
• Assist with monitoring security alerts and investigating unusual events

• Designing and developing new machine learning models with a focus on real-time performance
• Integrating cutting-edge ML features into the SkeleTRACK product
• Analysing model performance and identifying areas of improvement
• Mentoring junior engineers and driving technical discussions

• Designing, implementing, testing, and optimizing reliable, efficient, and high-quality data pipelines
• Automating the extraction, loading and transformation of data from a wide variety of sources
• Developing solutions for the automated acquisition of data from source systems

• Design of evaluation framework for scalable LLM-as-a-judge pipelines
• Development of rubrics and curation of high-quality golden datasets
• Optimization of judge prompts for automated scoring
• Full-stack product development contribution
• Integration of automated evaluations into CI/CD pipelines

• Software Development:
• Writing, testing, and maintaining high-quality code for software applications.
• Collaborating with cross-functional teams, including designers, product managers, and other developers, to create software solutions.

• Designing, implementing, testing, and optimizing reliable, efficient, and high-quality data pipelines
• Automating the extraction, loading and transformation of data from a wide variety of sources
• Developing solutions for the automated acquisition of data from source systems

• Design and implement automated test cases for backend, frontend, or API-based systems
• Collaborate with distributed teams across multiple time zones
• Participate in requirement analysis to ensure testability and clarity

• Design of complex and scalable data solutions on the AWS cloud platform
• Development and implementation of complex and scalable data solutions on the AWS cloud platform
• Design and optimization of data pipelines
• Writing clean, efficient and maintainable SQL and Python code

• Work with Android source code and build system
• Develop, customize, and maintain Android BSP components
• Modify and improve Android platform components
• Develop, integrate, and maintain Android HAL components
• Collaborate with hardware teams for platform bring-up and hardware integration

• Architect scalable inference services, APIs, and backend components for model-driven and LLM-powered product features
• Productionize AI and ML workflows with strong MLOps practices
• Define and implement evaluation frameworks for model quality, system reliability, latency, and cost

• Design, build, and ship production retrieval systems
• Own vector store selection and operation including scalability, latency, reliability, cost, and multi-tenant design
• Build and operate indexing and refresh pipelines including chunking, embedding generation, backfills, deletes, and versioned indices

Design and build knowledge tracing and longitudinal learner models that support mastery and progression features surfaced to customers...

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

• Develop and maintain scalable web applications using Angular or React
• Build and optimize RESTful APIs and microservices using Node.js, Python or .NET
• Define and manage cloud infrastructure using Infrastructure as Code, such as Terraform or OpenTofu

• Új technológiák bevezetése
• Termékfejlesztési igények implementálása
• Rendszertervezés
• Tesztelés
• Dokumentálás
• Kapcsolódó alkalmazás- és interfészfejlesztésekben való együttműködés a társszervezőkkel
• Minőségbiztosítási feladatok támogatása

• LLM/GenAI architektúrák és agentek tervezése
• Ügyfelek fejlesztési igényeinek felmérése, átlátása és rendszerezése
• Specifikációk és rendszertervek készítése
• Prototípusok és PoC-ok létrehozása
• AI-megoldások jó gyakorlat szerinti kialakításában való részvétel

• 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
• Provide technical expertise during the pre-sales phase
• Mentor 3-6 person project teams

• Design, develop, and maintain scalable data pipelines in cloud and hybrid environments
• Contribute to the architecture of enterprise data platforms with a system-oriented mindset
• Work with large-scale datasets using SQL, Spark, and cloud-native tools

• Lead the end-to-end implementation of data pipelines and GenAI applications on Databricks
• Design and maintain CI/CD, model serving, monitoring, and evaluation frameworks for AI production reliability
• Tune complex Spark jobs and LLM inference patterns for maximum efficiency and minimum latency