LNT/AE-G/1896639
- DC-Divisional Corporate
- Chennai Head Qrs.
- Posted On 15 Oct 2026
- End Date 13 Apr 2027
- Required Experience10 - 20 years
Skills
Knowledge & Posting Location
Artificial Intelligence
Minimum Qualification
Bachelor of Engineering (BE)
Job Description
Job Title: Applied Research Engineer, AI (EPC & Manufacturing) Focus areas : Edge AI, Agentic AI Location: Chennai, Tamil Nadu Job Summary: You'll lead applied research in creating and optimizing small language models (SLMs) and derived models for range of use cases cutting across both structured and unstructured data – for edge AI deployment, powering agentic systems, digital threads, and highly contextual knowledge graphs. Focus on real-world EPC/manufacturing scenarios like autonomous workflow orchestration, connected operations, and aimed at taking digital transformation in these sectors to the next generation of technologies and with breakthrough impact. Key
Responsibilities:
- Design, train, and distill SLMs or derived models (e.g., from Llama/Mistral) for domain-specific tasks in EPC/manufacturing, with deeper context engineering and mature agentic AI workflows, optimizing for low-latency inference on edge devices for site level intelligence and predictability.
- Architect agentic AI frameworks that leverage SLMs for autonomous decision-making, such as multi-agent orchestration for construction sequencing or factory floor optimization.
- Build and integrate digital threads—end-to-end data pipelines linking design, procurement, construction, and operations—using SLMs for natural language querying and automation.
- Develop complex knowledge graphs to model intricate relationships in EPC ecosystems (e.g., asset hierarchies, supplier networks, regulatory compliance), enhanced by SLM-driven reasoning and graph RAG.
- Deploy edge AI solutions for real-time applications, including IoT sensor fusion, on-device anomaly detection, and federated learning in harsh manufacturing environments.
- Prototype and benchmark systems for scalability, collaborating on MLOps pipelines with tools like Kubernetes, TensorRT, and ONNX for edge-cloud hybrid deployments.
- Conduct research on SLM fine-tuning, quantization, and agentic behaviors, documenting findings for internal adoption or publications. Sensitivity: LNT Construction Internal Use Required Qualifications:
- Master's or PhD in AI/ML, Computer Science, or related field (or equivalent experience).
- 4+ years in applied AI, with deep hands-on experience building/training SLMs or derived models (e.g., LoRA/PEFT fine-tuning, model distillation).
- Proven expertise in edge AI deployment (e.g., NVIDIA Jetson, ARM-based inference, quantization techniques like AWQ/GPTQ).
- Strong experience with agentic AI (e.g., LangChain, AutoGen) and Neo4j for complex knowledge graphs (Cypher queries, graph embeddings, graph algorithms).
- Familiarity with digital threads in manufacturing/EPC: PLM integration, BIM data flows, or IIoT protocols.
- Proficiency in PyTorch, Hugging Face Transformers, Neo4j, and edge frameworks (e.g., TensorFlow Lite, OpenVINO). Preferred Skills:
- Experience in EPC/manufacturing domains: procurement-to-pay automation, digital twins, or supply chain graph analytics.
- Knowledge of federated learning, secure multi-party computation, or quantum-safe edge crypto.
- Contributions to open-source SLM/edge AI projects or relevant publications (e.g., ICML, NeurIPS workshops). Sensitivity: LNT Construction Internal Use
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