ML Engineering

We are seeking a highly experienced Senior AI Consultant to serve as a strategic advisor and technical architect for a large‑scale AI transformation program. This role will drive architecture decisions, model strategy, and implementation planning across multiple high‑impact AI use cases within Telecom Operations and enterprise business functions. As a trusted advisor to executive leadership, you will provide thought leadership on AI adoption, guide model selection and cost‑governance strategies, and help define scalable, production‑ready AI architectures. The ideal candidate combines deep hands‑on expertise in Generative AI, NLP, Machine Learning, and LLM/SLM ecosystems with proven experience influencing VP and Senior Director‑level stakeholders in large enterprises. Key Responsibilities Define and advise on AI architectures leveraging SLMs, LLMs, and hybrid AI pipelines for use cases involving classification, information extraction, document processing, RAG, correlation analysis, and reasoning workflows. Evaluate and challenge model selection approaches, benchmarking methodologies, prompt engineering strategies, and fine‑tuning techniques. Lead cost‑versus‑performance assessments across frontier LLMs, fine‑tuned LLMs, instruction‑tuned SLMs, and custom fine‑tuned SLM deployments. Provide recommendations on implementation strategy, team structure, sprint planning, operating models, and make‑versus‑buy decisions. Review data readiness, labeling requirements, evaluation frameworks, and MLOps/LLMOps considerations for enterprise‑scale deployments. Develop executive‑ready business cases covering implementation costs, operational expenses, ROI, latency, accuracy, and scalability trade‑offs. Identify and mitigate risks related to vendor lock‑in, model drift, compliance, governance, security, and regulatory requirements. Partner closely with senior leadership to shape AI strategy, influence key decisions, and establish long‑term AI adoption roadmaps. Required Qualifications 8+ years of experience in Artificial Intelligence and Machine Learning, including 3–4+ years designing and deploying enterprise NLP, LLM, or SLM solutions. Strong hands‑on experience with Small Language Models (SLMs), including fine‑tuning, optimization, and deployment of models such as Phi, Gemma, Llama, Mistral, Qwen , or similar. Deep understanding of frontier LLM platforms including OpenAI, Azure OpenAI, Anthropic , and the ability to determine appropriate model selection based on business requirements. Text Classification Named Entity Recognition (NER) Information Extraction Document Processing Retrieval‑Augmented Generation (RAG) Reasoning and Decision Support Systems Strong capability to translate technical architecture decisions into business outcomes, cost models, and ROI analyses. Experience within at least one of the following domains: Telecommunications Industrial / Manufacturing Operations Preferred Qualifications Experience implementing AI‑driven automation and workflow orchestration solutions in high‑volume operational environments. Strong understanding of LLMOps and SLM deployment best practices, including: Batching Performance and Latency Benchmarking Monitoring and Governance Frameworks Success Criteria The successful candidate will deliver: Clear and defensible AI architecture recommendations for each use case. A standardized evaluation framework and scoring methodology for model benchmarking. Executive‑level comparisons across LLM‑only, SLM‑only, and hybrid AI architectures, including cost, latency, and accuracy metrics. A phased implementation roadmap that enables successful delivery across 4–6 month execution cycles. Practical guidance that balances innovation, scalability, cost efficiency, and operational excellence. Mandatory Skills Artificial Intelligence (AI) Natural Language Processing (NLP) Small Language Models (SLMs) Retrieval‑Augmented Generation (RAG) #J-18808-Ljbffr BrickRed Systems