Join the innovative, multinational AI team New Delhi, Test & Measurement division, and play a key role in making our industry-leading mobile radio tester, , even more productive and user-friendly.

This is an excellent opportunity for recent university graduates to launch their careers in AI engineering while developing strong skills in software, cloud, and product development - all within a truly diverse, international environment.

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 (e.g., 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 (e.g., 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 (e.g., 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 (e.g., 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