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Consultant -Senior Databricks / ML & Gen AI

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Description

Job Description: Senior Databricks Consultant / ML & GenAI


Technical Skills and Experience

  • At least 4 years of hands-on Databricks experience and 2+ years working on ML/GenAI workloads.
  • Strong expertise in Databricks-based ML/GenAI architecture, model training, fine-tuning, evaluation, deployment, and monitoring.
  • Hands-on experience with Databricks Mosaic AI Model Training or custom LLM training on Databricks GPU clusters.
  • Proven experience fine-tuning open-source LLMs, preferably Llama-family models, using SFT, LoRA, or QLoRA in real-world projects.
  • Strong understanding of fine-tuning, Retrieval-Augmented Generation (RAG), continued pretraining, and training from scratch, including cost, performance, and quality trade-offs.
  • Experience in large-scale training data preparation, including cleaning, deduplication, labelling, synthetic data generation, and PII removal.
  • Knowledge of LLM evaluation, performance optimisation, production deployment, monitoring, and AI governance, including explainability and model risk management.

Consulting and Client-Facing Skills

  • Ability to translate business requirements into technical architectures and proof-of-concept (PoC) plans.
  • Experience engaging with CTOs, senior engineering leaders, and client stakeholders.
  • Strong communication skills to explain technical solutions, implementation approaches, risks, and trade-offs.
  • Experience reviewing RFP responses, technical proposals, and solution presentations.

Preferred Qualifications

  • Domain experience in financial services, banking, lending, credit, or insurance.
  • Exposure to domain-adapted foundation models and continued pretraining.
  • Databricks Machine Learning Professional and/or Generative AI Engineer Associate certification.
  • Demonstrable project experience through case studies, GitHub repositories, technical notebooks, publications, or conference presentations.

Engagement Details

  • Initial consulting requirement of approximately 18 hours.
  • Expected engagement timeframe: early to mid-November 2026.
  • Remote, client-facing consulting engagement.
  • Potential for further technical guidance or delivery support, subject to the project progressing.

Skills

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