Senior Data Scientist

Blackbook.ai is seeking a Senior Data Scientist / Machine Learning Consultant to lead the full lifecycle of machine learning projects — from problem framing and data strategy through to model development, deployment, and ongoing performance management.This role sits at the intersection of applied research and production engineering, requiring both deep technical expertise in NLP and LLMs and the ability to translate business problems into scalable AI solutions.KEY RESPONSIBILITIESModel Development & ResearchDesign, fine-tune, and evaluate LLMs and multimodal models (e.g. Qwen, LLaMA) using frameworks such as PyTorch, PEFT/LoRA, ms-swift, and Megatron-LMDevelop and own RAG pipelines, embedding models, and retrieval systems (dense and sparse), including contrastive learning approaches to improve retrieval accuracyLead applied NLP work across tasks including text classification, NER, summarisation, OCR, and code generationConduct rigorous experimentation, benchmarking, and ablation studies; document findings clearly for technical and non-technical audiencesProduction Deployment & MLOpsContainerise and deploy models using vLLM, Triton Inference Server, TensorRT-LLM, ONNX Runtime, and DockerBuild and maintain FastAPI services wrapping model inference endpoints; integrate models into production applicationsOwn CI/CD pipelines for ML components; manage experiment tracking and model versioning (e.g. ClearML, MLflow)Monitor deployed models for drift, latency, and quality; iterate based on real-world feedbackTechnical Leadership & CollaborationAct as a technical authority on LLM and NLP best practices across the data science teamCollaborate closely with software engineers, product managers, and domain experts to scope, deliver, and iterate on AI featuresConduct code reviews, define engineering standards, and contribute to a culture of technical excellenceMentor and guide junior and mid-level data scientists; support skill development through pairing and knowledge-sharing sessionsResearch & InnovationStay current with the latest advances in LLMs, multimodal AI, and NLP; evaluate and introduce new techniques with business relevanceRepresent the organisation's work through publications, conference papers, or technical blog posts where appropriateContribute to the development and maintenance of internal benchmarks, evaluation harnesses, and datasetsQUALIFICATIONS & EXPERIENCERequired4+ years of professional experience in machine learning engineering or applied data science, with a strong NLP focusProven track record fine-tuning and deploying LLMs and transformer-based models in production environmentsDeep proficiency in Python and PyTorch; working knowledge of C++ is an assetHands-on experience with at least two of: vLLM, Triton Inference Server, TensorRT-LLM, ONNX RuntimeExperience designing and evaluating RAG pipelines, including embedding model fine-tuning and vector stores (e.g. Milvus, Faiss, Pinecone)Solid understanding of PEFT methods (LoRA, QLoRA, adapters) and distributed training (Megatron-LM or equivalent)Proficiency with Docker, Git, Linux, and CI/CD practices in an ML contextBachelor's and Master's degree in Computer Science, Data Science, Mathematics, or a related technical fieldPreferredExperience with multimodal models (vision-language, speech-language) and related benchmarksPublications or contributions to peer-reviewed NLP/ML conferences (e.g. ACL, EMNLP, NeurIPS, ICLR)Experience with code generation or domain-specific language (DSL) modelling tasksFamiliarity with speech synthesis pipelines and text normalisation for TTSExperience mentoring junior engineers or delivering ML education in an academic or corporate contextSend your applications to recruitment@blackbook.ai