Siemens | Junior Software Developer – AI/ML

Role Overview
We are seeking a Graduate Trainee Engineer passionate about Natural Language Processing (NLP), Generative AI, and building next-generation AI-driven applications. In this role, you will work with state-of-the-art large language models (LLMs), Retrieval-Augmented Generation (RAG) pipelines, and intelligent agent-based systems to develop scalable, enterprise-grade AI solutions. You’ll collaborate with cross-functional teams to deliver impactful innovations in electrification, energy, and industrial AI domains.

Job Description :-

Key Responsibilities

• Design, develop, and optimize NLP-powered AI solutions using advanced techniques like Named Entity Recognition (NER), embeddings, summarization, and more.
• Build and deploy RAG pipelines and agentic workflows to create intelligent, context-aware applications.
• Fine-tune, prompt-engineer, and operationalize LLMs (e.g., OpenAI, Anthropic, Falcon, LLaMA) for domain-specific applications.
• Collaborate with data scientists, backend developers, and cloud architects to deliver scalable, AI-first systems.
• Evaluate and integrate third-party APIs and open-source libraries for generative AI use cases.
• Implement observability, monitoring, and explainability features to ensure model performance, reliability, and transparency.
• Ensure compliance with enterprise-grade scalability, traceability, and maintainability standards.
• Continuously improve AI models for better latency, accuracy, and efficiency in production environments.

Required Qualifications & Skills

• Bachelor’s or Master’s degree in Computer Science, Machine Learning, AI, or a related field.
• Strong understanding of LLM architectures, embeddings, and fine-tuning methods (LoRA, PEFT).
• Hands-on experience with NLP and Generative AI concepts.
• Proficiency in Python and AI frameworks such as LangChain, Transformers (Hugging Face), LlamaIndex, SmolAgents.
• Knowledge of designing and deploying RAG pipelines and multi-step agent architectures.
• Familiarity with ML observability and explainability tools (e.g., TruEra, Arize, WhyLabs).
• Exposure to cloud-based AI platforms such as AWS SageMaker, AWS Bedrock, Azure OpenAI Service, Azure ML Studio, Azure AI Foundry.
• Understanding of real-time NLP challenges such as streaming data, latency optimization, and multi-turn dialogues.
• Experience with LangGraph, function calling, and orchestration tools for agent-based systems.
• Exposure to Infrastructure-as-Code (Terraform/CDK) and DevOps workflows for AI pipelines.

Preferred Skills

• Domain knowledge in Electrification, Energy, or Industrial AI.
• Experience integrating LLM-based agents into production systems.
• Strong problem-solving, collaboration, and analytical skills.

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Join us and use your AI expertise to shape the future of intelligent, industry-transforming solutions.