Available to hire
Hi, I’m Frederick J Hoffmann, a research-driven AI engineer bridging academia and industry. I design and ship production-ready AI systems for data-rich domains—energy, finance, robotics, and manufacturing—focusing on scalable ML pipelines, imitation and reinforcement learning, and robust monitoring to ensure real-world reliability. I’ve led multi-disciplinary teams on large-scale projects, published in venues such as CVPR, and enjoy turning complex problems into practical, impact-driven solutions.
In fast-moving environments I thrive on translating cutting-edge research into deployable tooling, mentoring colleagues, and sharing knowledge through talks and tutorials. I value collaboration, curiosity, and making technology accessible and useful for users and stakeholders alike.
Skills
Experience Level
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Intermediate
Intermediate
Intermediate
Intermediate
Language
English
Fluent
Work Experience
Lead AI Scientist at Leap Automation
January 1, 2024 - PresentLead AI scientist responsible for developing computer vision and reinforcement learning algorithms for industrial packing robots, reporting directly to the CTO. Developed and deployed imitation learning, reinforcement learning, and vision language action algorithms to control robotic arms packing fresh produce with high accuracy and throughput. Built, trained, and deployed vision language models and active learning decision systems to autonomously evaluate and manage robot performance. Created generative AI vision models based on diffusion for synthetic data generation. Managed deployments using MLOps and CI/CD pipelines. Oversaw Innovate UK funded projects related to the future of robotics research while leading a team of three and mentoring others.
AI Scientist at Shell
January 1, 2024 - September 5, 2025Contributed as an AI Scientist in Shell's AI department working on deep learning for trading and machine vision. Developed and productionized an agentic LLM pipeline for querying internal documents, databases, and trading tools with natural language via a retrieval augmented generation approach optimized by reinforcement learning, saving traders and researchers approximately two days per week in data compilation time. Created agentic AI models using RL to reason about news and future events significantly outperforming humans and developed deep learning-based price forecasting models. Models were widely used across the trading floor by hundreds of traders and managers. Deployed algorithms using MLOps and CI/CD tools.
AI Research Scientist at Tractable
November 1, 2022 - September 5, 2025Worked in the Core Research Team of a unicorn deep learning startup focused on AI visual expertise for car insurance. Responsible for developing research agenda to generate internal impact and publications. Developed computer vision algorithms including object detection, scene graph, neural reasoning, and generative diffusion models for data augmentation. Created a multimodal language vision model that significantly generalized models in production resulting in a 10% performance uplift. Benchmarked across GPUs and TPUs and deployed models on AWS and later GCP to millions of customers worldwide. Published influential papers including a state-of-the-art ImageNet image classifier.
Principal AI Scientist at SSE
November 1, 2020 - September 5, 2025Developed machine learning algorithms for a major energy company including Bayesian deep neural networks for forecasting energy demand and wind farm generation. Developed deep Bayesian reinforcement learning approaches to optimize hydropower plant revenue across Scotland. Created computer vision pipelines for early defect detection on SSE’s transmission network. Deployed all algorithms using MLOps and CI/CD, with productionized algorithms achieving over £30M per annum ROI. Researched causal inference and automatic machine learning applications in energy. Managed team of seven and handled hiring and managerial duties.
Data Scientist at HSBC
November 1, 2018 - September 5, 2025Developed fraud detection algorithms using map-reduce parallel stochastic gradient descent in Scala, Spark, and Fortran to optimize computation speeds. Created visualization tools to analyze and test optimization performance. Worked on large-scale financial data with advanced technologies.
Machine Learning Scientist at Oxbótica
March 1, 2018 - September 5, 2025Worked on planning and perception teams within an autonomous vehicle spin-off to develop decision support and risk management systems for autonomous vehicle control. Applied reinforcement learning with planning to improve decision making, designed temporal deep neural networks for vehicle localization failure forecasting, and used inverse reinforcement learning to quantify overall autonomous vehicle risk.
Data Scientist at Hello Soda
August 31, 2017 - September 5, 2025Solved text analytics problems mining social media for customer insights using supervised and unsupervised deep NLP techniques on large scale social media data. Developed language normalization and disambiguation algorithms for text mining.
Data Scientist at The Floow
August 31, 2017 - September 5, 2025Applied machine learning to data collected from various in-car devices including fixed boxes and mobile apps to create predictive models of insurance risk tied to driving behavior. Integrated large scale online map and vehicle data to enhance predictive insurance risk models. Collaborated closely with major insurers and car manufacturers defining technical roadmaps, hiring, training, and supervision.
AI Engineer at Blend360 (Agentic AI consultancy) / Diego
September 30, 2025 - October 27, 2025Joined a three-month engagement to develop an agent capable of extracting structured transaction information from free-form descriptions and cross-referencing with a master table using vector search. Built a master data table, implemented a vector-search workflow, and scaled processing to millions of records with Spark map-reduce. Prepared production-ready code for imminent Diego deployment. Technologies used included Python, OpenAI, Azure, Databricks, LangChain, and LangGraph; all work was orchestrated within an MLOps/CI–CD framework.
Lead AI Scientist at Leap Automation
May 31, 2025 - October 27, 2025Led end-to-end development of imitation learning and reinforcement learning-based vision-language action systems for industrial packing. Built and deployed an autonomous monitoring and decision system for robot arms, focusing on high accuracy and throughput. Developed and deployed a multimodal language model (VLM) with active learning-based monitoring and decision systems to autonomously evaluate robot performance. Implemented a productionized RL-based reasoning pipeline enabling a robot to reason about news and future events to inform planning; supported by GPU/TPU benchmarks and cloud deployment.
AI Scientist at Shell
November 30, 2022 - October 27, 2025Cross-functional AI role spanning deep learning for trading and machine vision. Built an agnostic LLM pipeline to query Shell internal documents, datasets, and trading tools, incorporating retrieval augmented generation (RAG) and reinforcement learning-driven optimization for internal workflows. Delivered scalable tooling to support hundreds of traders and researchers, with productionized models and extensive documentation.
Principal AI Scientist at SSE (Scottish and Southern Energy), Havant
November 1, 2020 - October 27, 2025Developed Bayesian and deep learning models for forecasting energy demand and wind farm generation. Optimized revenue via reinforcement learning-inspired methods and built computer-vision-based defect detection for infrastructure monitoring on transmission assets. Led benchmarking and productionization of ML workflows for energy systems.
Machine Learning Scientist at Oxbotica
August 1, 2017 - October 27, 2025Worked across the Planning and Perception teams to develop decision-support and risk-management algorithms for autonomous vehicle control systems in the Oxford Robotics Lab environment.
Data Scientist at Hello Soda
August 1, 2017 - October 27, 2025Solved text analytics problems for a social media analytics company, applying supervised and unsupervised ML to large-scale social data, including language normalization and disambiguation algorithms for text mining.
Data Scientist at The Flow
January 1, 2015 - October 27, 2025Built backend ML pipelines for insurance telematics data, applying predictive models for auto insurance risk, integrating large online maps and vehicle datasets.
Data Scientist at HSBC
March 1, 2018 - October 27, 2025Applied machine learning to fraud detection and related analytics within the insurance/finance domain, collaborating with risk and engineering teams to accelerate model deployment.
Data Scientist at SSE (Havant) / Havant
March 1, 2017 - October 27, 2025Early-stage ML work in energy analytics, with a focus on forecasting and optimization of energy assets; contributed to cross-team ML initiatives. (Valued as part of the SSE project history.)
Data Scientist at The Flow / Hello Soda
December 1, 2014 - October 27, 2025Data science work on social data mining and predictive analytics for consumer insight and marketing applications.
Education
DPhil at University of Oxford
January 1, 2011 - January 1, 2015MSc at University of Oxford
January 1, 2010 - January 1, 2011BSc at University of Nottingham
January 1, 2007 - January 1, 2010DPhil in Systems Approaches to Biomedicine at University of Oxford, Doctoral Training Centre
January 1, 2011 - January 1, 2015MSc Mathematical and Computational Finance at University of Oxford
January 1, 2010 - January 1, 2011BSc Mathematics (Specialist in Probability and Statistics) at University of Nottingham
January 1, 2007 - January 1, 2010Qualifications
Industry Experience
Manufacturing, Energy & Utilities, Financial Services, Transportation & Logistics, Software & Internet, Media & Entertainment, Healthcare, Life Sciences, Professional Services, Education, Government, Other
Skills
Experience Level
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Intermediate
Intermediate
Intermediate
Intermediate
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