AI Engineer Mobile Radio Tester
Your tasks
Data Analysis Processing Collect, process, and analyze large datasets from mobile radio testing environments to extract actionable insights
Cloud Infrastructure Development Support the development, automation, and maintenance of robust, scalable cloud-based infrastructures for AI system development and data operations
Traditional ML Deep Learning Apply machine learning and deep learning techniques (eg, classification, regression, feature extraction) to address challenges in mobile radio testing
Implement GenAI Applications Explore, implement, and benchmark AI systems using LLMs and related concepts (eg, RAG, agentic AI workflows, and MCP), evaluating different solutions to enhance product
Help automate DevOps and MLOps workflows, ensuring seamless deployment and integration of AI solutions into our products
Work with technologies such as containerization and cloud platforms
Contribute to end-to-end product development, including app and web-UI design
Collaborate with a multinational, cross-functional team
Your Qualifications
Bachelor/Master/PhD in Computer Science, AI or related field from top university/college
3+ years of professional experience in software development including 1+ years proven experience in AI/ML production environments
Proficiency in Python programming, particularly with libraries for data processing and AI/ML development
Strong understanding of AI/ML fundamentals, including standard architectures (eg, CNN, Transformer), model training, fine-tuning, and benchmarking
Exposure and interest in LLM engineering Prompt engineering, RAG, agentic workflows, MCP and Benchmarking practices with tools such as RAGAS
Interest or exposure to, DevOps/MLOps tools practices
Understanding of containerization (Docker) and experience in cloud engineering (Kubernetes) on platforms such as Azure is a plus
Experience with web frameworks (eg, FastAPI, React, Vercel) is a plus
Ability to work effectively and independently in a diverse, international, and collaborative environment
Excellent communication, analytical, debugging and problem-solving skills
Data Analysis Processing Collect, process, and analyze large datasets from mobile radio testing environments to extract actionable insights
Cloud Infrastructure Development Support the development, automation, and maintenance of robust, scalable cloud-based infrastructures for AI system development and data operations
Traditional ML Deep Learning Apply machine learning and deep learning techniques (eg, classification, regression, feature extraction) to address challenges in mobile radio testing
Implement GenAI Applications Explore, implement, and benchmark AI systems using LLMs and related concepts (eg, RAG, agentic AI workflows, and MCP), evaluating different solutions to enhance product
Help automate DevOps and MLOps workflows, ensuring seamless deployment and integration of AI solutions into our products
Work with technologies such as containerization and cloud platforms
Contribute to end-to-end product development, including app and web-UI design
Collaborate with a multinational, cross-functional team
Your Qualifications
Bachelor/Master/PhD in Computer Science, AI or related field from top university/college
3+ years of professional experience in software development including 1+ years proven experience in AI/ML production environments
Proficiency in Python programming, particularly with libraries for data processing and AI/ML development
Strong understanding of AI/ML fundamentals, including standard architectures (eg, CNN, Transformer), model training, fine-tuning, and benchmarking
Exposure and interest in LLM engineering Prompt engineering, RAG, agentic workflows, MCP and Benchmarking practices with tools such as RAGAS
Interest or exposure to, DevOps/MLOps tools practices
Understanding of containerization (Docker) and experience in cloud engineering (Kubernetes) on platforms such as Azure is a plus
Experience with web frameworks (eg, FastAPI, React, Vercel) is a plus
Ability to work effectively and independently in a diverse, international, and collaborative environment
Excellent communication, analytical, debugging and problem-solving skills
