About this Chance:
- Core Responsibilities:
- Own the end-to-end design, development, and continuous improvement of the Deep Research Agent
- Design and maintain the RAG pipeline: chunking strategy, embedding models, retrieval, and re-ranking
- Implement and optimize context compression to reduce overhead on long-horizon, multi-hop queries
- Build and operate the model evaluation harness: benchmark design, regression tracking, and A/B testing
- Lead the agent self-improvement loop: prompt proposal pipeline and benchmark-gated merge governance
- Track frontier model research and assess production applicability for the platform intelligence roadmap
- Advise on fine-tuning, prompt optimization, and model selection strategies across model generations
- Core Skills & Experience:
- Deep expertise in LLMs: transformer architecture, fine-tuning (LoRA/QLoRA), RLHF, and alignment techniques
- RAG system design: vector databases (Pinecone, Weaviate, pgvector), embedding models, hybrid search strategies
- ML experimentation tooling:



MLflow, Weights & Biases, Vertex AI Experiments, or equivalent platforms
- Python ML stack: PyTorch or JAX, HuggingFace Transformers, LangChain or equivalent orchestration libraries
- Statistical evaluation methods: benchmark design, significance testing, and evaluation dataset curation
- Context compression and KV cache optimisation techniques, quantisation basics (GPTQ, AWQ)
- Why join Ericsson?At Ericsson, you´ll have an outstanding opportunity. The chance to use your skills and imagination to push the boundaries of what´s possible. To build solutions never seen before to some of the world’s toughest problems. You´ll be challenged, but you won’t be alone. You´ll be joining a team of diverse innovators, all driven to go beyond the status quo to craft what comes next.
- Primary country and city: India (IN) || Noida

Req ID: 787648

📌 Model and Intelligence Engineer (Noida)
🏢 Ericsson
📍 Noida