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
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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.
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Architect agentic AI frameworks that leverage SLMs for autonomous decision-making, such as multi-agent orchestration for construction sequencing or factory floor optimization.
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Build and integrate digital threads—end-to-end data pipelines linking design, procurement, construction, and operations—using SLMs for natural language querying and automation.
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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.
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Deploy edge AI solutions for real-time applications, including IoT sensor fusion, on-device anomaly detection, and federated learning in harsh manufacturing environments.
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Prototype and benchmark systems for scalability, collaborating on MLOps pipelines with tools like
Kubernetes, TensorRT, and ONNX for edge-cloud hybrid deployments.
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Conduct research on SLM fine-tuning, quantization, and agentic behaviors, documenting findings for internal adoption or publications.
Sensitivity: LNT Construction Internal Use
Required Qualifications
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Master's or PhD in AI/ML, Computer Science, or related field (or equivalent experience).
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4+ years in applied AI, with deep hands-on experience building/training SLMs or derived models
(e.g., LoRA/PEFT fine-tuning, model distillation).
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Proven expertise in edge AI deployment (e.g., NVIDIA Jetson, ARM-based inference, quantization techniques like AWQ/GPTQ).
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Strong experience with agentic AI (e.g., LangChain, AutoGen) and Neo4j for complex knowledge graphs (Cypher queries, graph embeddings, graph algorithms).
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Familiarity with digital threads in manufacturing/EPC: PLM integration, BIM data flows, or IIoT protocols.
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Proficiency in PyTorch, Hugging Face Transformers, Neo4j, and edge frameworks (e.g., TensorFlow
Lite, OpenVINO).
Preferred Skills
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Experience in EPC/manufacturing domains: procurement-to-pay automation, digital twins, or supply chain graph analytics.
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Knowledge of federated learning, secure multi-party computation, or quantum-safe edge crypto.
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Contributions to open-source SLM/edge AI projects or relevant publications (e.g., ICML, NeurIPS workshops).
Sensitivity: LNT Construction Internal Use
