Znaleziono ~344 oferty w 0.323s, strona 7 z 7
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Lead Solutions Architect (UNIQA Insurance Group)​

@UNIQA InsurTech API DevOps Machine Learning AWS Azure Google Cloud Platform German Java AI
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25 200 zł

Test Manager for AI initiatives

@emagine Polska ISTQB QA SAFe SQL Agile qTest YAML Machine Learning Selenium Generative AI
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Senior MLOps Engineer

@Billennium Sagemaker Python Amazon AWS Kubernetes LLM Machine Learning
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Head of Cybersecurity Risk Quantification

@HSBC Service Delivery Spark Databricks Cybersecurity Python Data Engineering MLOps Machine Learning
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21 000 - 27 300 zł

AI Engineer

@INFOPLUS TECHNOLOGIES Python Generative AI NLP AI TensorFlow Machine Learning
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14 000 - 20 000 zł

Backend Engineer (Data & AI)

@Appliscale TypeScript Python AWS Machine Learning AI
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19 000 - 25 000 zł

Senior AI Research Engineer (Responsible AI)

@Tooploox AI Python Clean Code Responsible AI Machine Learning AI models
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33 600 - 42 000 zł

DataBricks Architect

@CRODU Databricks Apache Spark Python AWS Machine Learning AI Azure
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Senior AI & Data Scientist (m/f/d)

@PAYBACK SQL Python GenAI Machine Learning Cloud Storage BigQuery Vertex AI GCP Terraform Cloud Run
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20 000 - 29 000 zł

Senior Data Scientist

@in4ge sp. z o.o. Python Data Science English Cloud Machine Learning Big Data
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Staff Software Engineer

@VISA Java Jenkins CI/CD Docker Maven Kubernetes Spring RESTful API Machine Learning AI
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Senior AI Engineer

@Team Up Python OpenAI rag API/SDK Cloud LLM CI/CD Databases Docker Machine Learning
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28 044 - 46 740 zł

Software Engineer (Rust / Python / Nix / AI)

@Helsing Rust Python Algorithms AI Linux / Unix Distributed systems Embedded Systems Networking Security Machine Learning
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CRM AI IT Developer

@DSV GBS (DSV Global Business Services) Microsoft AI Builder PowerApps Azure SQL JavaScript .Net Microsoft Dynamics 365 Copilot Machine Learning AI
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Senior Machine Learning Data Engineer

@PredictX Python SQL ETL Data Warehousing
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Senior Machine Learning Research Engineer

@Nomagic Deep Learning Computer Vision Robotics Python
34 000 - 48 000 zł

Senior Machine Learning Engineer

@Apollo.io cloud keras machine learning python pytorch scikit learn tensorflow
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Technical Project Manager / Project Engineer

@Luxoft DXC data as a product machine learning cloud systems public transit
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Manager, Deep Learning Algorithms

@NVIDIA AI Machine Learning Algorithms Software Engineering
18 000 - 20 000 zł

Senior ML Engineer

@DataArt Poland ai machine learning python tensorflow
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Business Intelligence Analyst

@PredictX AI Machine Learning Data Analytics ETL
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Data Science/AI Engineer

@N-iX AI Machine Learning Deep Learning Computer Vision
21 840 - 31 920 zł

AI Engineer (Startup)

@DNA Technology ai machine learning natural language processing python RAG
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Python Developer / Data Scientist

@Knowde AI Machine Learning Data Science Natural Language Processing
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Back-End Software Engineer - Python / AI / ML

@Knowde AI Machine Learning Natural Language Processing Langchain
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AI/ML Senior Software Developer

@Epiq Python NLP Machine Learning TensorFlow
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Data Scientist

@Provident Polska S.A. R SQL Machine Learning Data Modeling
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MLOps Engineer

@KRUK azure devops ci/cd machine learning mlflow python r sql
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AI Data Rater - Swedish

@Welocalize Data Annotation Data Rating Machine Learning
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Director/Tech Lead, Acceleration Kernel Developer

@Tenstorrent Kernel Development Tensor Optimization Machine Learning Performance Optimization
26 040 - 28 560 zł

Senior AI Engineer (LLM | Node.js | LangGraph | Vector DBS)

@1dea ai langgraph llm machine learning node.js
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Junior Project Manager (Data Engineering, Big Data & AI)

@ERGO Technology & Services S.A. Big Data Data Engineering Generative AI Machine Learning
20 000 - 26 000 zł

Senior AI Engineer

@Elitmind Python NLP LLM Machine Learning
23 520 - 25 200 zł

AI/ML Engineer

@Connectis azure ci/cd docker machine learning python
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Data Analyst

@SpotOn Python R BI tools Machine Learning
28 000 - 32 000 zł

Senior LLM Automation Engineer

@Volue aws azure cloud gcp machine learning nlp python typescript
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Data Scientist

@Cloudfide azure databricks github machine learning natural language processing pandas pytest python
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Senior Data Scientist (Generative AI)

@SoftServe cloud data science devops machine learning python tensorflow
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Full-stack Developer

@Luxoft DXC ["TypeScript", "CSS", "HTML", "React, Redux, Redux Toolkit, Less CSS, Vite, Java, Groovy, Python, Spring, Hibernate, Apache Camel, Neo4j, Azure Cloud Services, Machine Learning, DevOps, banking"] ["TypeScript", "CSS", "HTML", "React"]
30 000 - 38 000 zł

Senior Data Solution Architect

@Verita HR ai bigdata business intelligence cloud data modeling data warehouse etl it architecture machine learning microservices architecture oracle solution architecture
12 000 - 20 000 zł

Cloud DevOps Engineer

@Reply Polska apache kafka aws azure cloud data analysis devops java kubernetes machine learning python
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DevOps Engineer (Observability Focus)

@KUBO DevOps AWS Prometheus Loki', 'Grafana', 'Tempo', 'Mimir' (LGTM stack) - Note: This is a common grouping but not a single tool, so listed as a descriptive string for clarity within tags if needed, or individual tags if preferred for strictness. For this schema, a descriptive string is used as it represents a suite of tools often used together for observability. If strict adherence to single tools is required, 'Grafana', 'Loki', 'Prometheus', 'Tempo', 'Mimir' would be separate tags. Given the prompt's phrasing, this combined tag reflects the intent. If individual tools are preferred, please specify. For now, using the prompt's phrasing as a tag for context. Let's refine this to individual tags for better machine readability as per typical schema practices. Re-evaluating: The prompt lists 'LGTM stack (Loki, Grafana, Tempo, Mimir)'. It's best to tag the individual components if the schema allows for multiple tags, which it does. So, individual tags are better. Let's list them individually. However, the prompt also mentions Prometheus separately. So, the list should be: Prometheus, Loki, Grafana, Tempo, Mimir, OpenTelemetry, AWS X-Ray, CloudWatch, ADOT. Let's ensure all mentioned technologies are captured. The prompt also mentions IaC tools like Terraform or CloudFormation, and CI/CD tools like GitHub Actions, GitLab CI, or Azure DevOps, Docker, Kubernetes. These should also be included as technology tags. The main focus is Observability, so that's the main_technology. The rest are supporting technologies. Let's compile the full list of relevant technologies from the job description for the tags. Technologies mentioned: Prometheus, LGTM stack (Loki, Grafana, Tempo, Mimir), OpenTelemetry, AWS X-Ray, CloudWatch, ADOT, Terraform, CloudFormation, GitHub Actions, GitLab CI, Azure DevOps, Docker, Kubernetes. The core focus is Observability, so that's the main_technology. The tags should encompass the specific tools and concepts. Let's refine the tags to be specific and actionable. The prompt asks for 'technology_tags'. It's best to list the specific tools and concepts. Let's re-evaluate the 'LGTM stack' part. Since it's a collection, it's better to list the individual components if the schema allows for multiple tags, which it does. So, 'Grafana', 'Loki', 'Tempo', 'Mimir' should be separate tags. Prometheus is also mentioned. OpenTelemetry, AWS X-Ray, CloudWatch, ADOT are also mentioned. IaC tools: Terraform, CloudFormation. CI/CD tools: GitHub Actions, GitLab CI, Azure DevOps. Containerization: Docker, Kubernetes. The main_technology is clearly 'Observability'. The tags should cover the specific technologies. Let's make sure the tags are concise and representative. The prompt mentions
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Specjalista ds. Usług Chmurowych i Telekomunikacji

@PKO BP Finat Microsoft Azure Azure Virtual Machines App Services WAF Terraform Powershell IaaS / PaaS CI/CD Azure DevOps Kubernetes
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28 600 - 32 800 zł

Senior Data Scientist

@Speedapp Python Data science SQL Data warehouse Macine learning models
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