Hire the Best NVIDIA Mental Ray Specialists
in the United Kingdom

Hi, I am a senior AI Engineer specialising in Computer Vision and I hold a PhD in a related field . I have both industry and academic research experience in deep learning and general software development. My services include: ✔️Training neural networks from scratch in any framework you like ✔️AI consultancy ✔️Building more optimal AI models and pipelines ✔️Identifying use cases for AI in your business and implementing it if needed ✔️Any computer vision-related problem solution ✔️Writing academic reports and articles on existing machine learning architecture. ✔️Data Scraping, Web Bot development ✔️Data Labeling

5+ Years of Experience in Data Annotation & AI Model Evaluation | Computer Vision Specialist I help AI/ML teams build accurate, high quality training datasets and evaluate model outputs to improve performance. With over 5 years of hands on experience in data annotation and AI evaluation, I specialize in image and video annotation for computer vision and machine learning projects. WHAT I DO: Image annotation (bounding boxes, polygons, segmentation, keypoints, classification) Video annotation & frame by frame object tracking Data labeling for object detection, image classification, and instance segmentation AI model output evaluation, quality assurance, and accuracy review Ground truth dataset creation for ML/AI training Edge case identification and annotation guideline development Large-scale dataset QA and error correction TOOLS & PLATFORMS: CVAT (Computer Vision Annotation Tool) Labelbox Encord Roboflow Plus additional labeling and QA platforms as projects require WHY WORK WITH ME: Detail-oriented with a strong eye for accuracy and consistency Comfortable following complex annotation guidelines and adapting quickly to new tools Reliable communicator who keeps clients updated on progress Experienced with datasets for computer vision applications including object detection, classification, and tracking Fast turnaround without compromising annotation quality I understand that clean, accurate training data is the foundation of any successful AI model and that careful evaluation is what separates a good model from a great one. I take that responsibility seriously on every project. Let's discuss your dataset or evaluation needs message me and I'll get started right away. Data Annotation, Data Labeling, Image Annotation, Video Annotation, Computer Vision, CVAT, Labelbox, Encord, Roboflow, Bounding Box Annotation, Image Segmentation, AI Training Data, Machine Learning Data, AI Model Evaluation, RLHF, Quality Assurance, Object Detection, Ground Truth Annotation

Skills and strengths: LLMS/ Generative AI, Data engineering/science (statistics degree), Python, C, web AND development. Writing and proofreading as I speak English and Polish at a native level. TL;Dr I have a highly unusual assortment of skills from disparate industries allowing me to see and do things others do not. Currently: Cyber Security Apprentice/Analyst at URSA Inc. Building MVP solution against foreign adversary attacks on open source projects (90% of the worlds online infrastructure is reliant on open source). Doing this under guidance and funding of David Kovar, cybersecurity veteran of 30+ years and a DoD and DARPA contractor Formerly: founder at Lionel, a company/project I founded aged 21. A six-year project developing stuttering treatment via transcranial direct current stimulation. Building world's largest synthetic speech impediment database. Founders are warned to cut their losses quickly or not fall in love with their ideas. I don't fall into either of these categories. I hate and hated working on this every hour that I did. However, when the muses give you an idea which could possibly lessen suffering for some people in the world you do not ignore them. Even if it doesn't scale. Even tho every hour working on this was miserable and PTSD triggering, It was a way for me to teach myself about LLMs, neuroscience, and brain computer interfaces. optimized stuttering neural network fesigned for classification to be applied in for active environments inside a device with microphone and ML activated TDCs. (I know no one will build this so so if you want to know more reach out, I will tell you the secret saue.). In spare time creating world's largest synthetic speech impediment dataset. As lack of data is the biggest bottleneck in this field. At CERN commercial spin outs I: Created synthetic database using Python and NLP classifiers. I learned how to use ML anomaly detection for rogue aircraft, and how to redesign an airspace using Python and Voronoi diagrams. Finally I contributed code to ESG visualization tool suite using Python Matplotlib, Seaborn, Bokeh. For 2 years on the side I was at GluoNNet I received impromptu tutorials on computer science & physics from CERN fellows who worked on engineering of the Atlas detector, particle & quantum physics, and 100+ other interesting things, In a former life I worked as a press officer for one of the mayors of London, NGOs & think tanks working on economic growth. I shall one day return to this space because in the words of Christopher Hitchens “The advice I’ve been giving to people all my life – that you may not be interested in the dialectic but the dialectic is interested in you; you can’t give up politics, it won’t give you up – was the advice I should have been taking myself." I disagree with almost all his arguments and positions, however this quote holds true.

Based in Lincoln UK, I am a Computer Science enthusiast (Ph.D) with a special interest towards Computer Vision and Medical Image Analysis. I can offer project consultancy services as well as I offer complete project development along with formal documentation. I am fluent with MATLAB, OpenCV and Python - based project development. I am very fluent with Machine Learning and can quickly develop customised projects using different ML models for image processing tasks (segmentation, detection, quantification and classification). I have good experience with both 2D (synthetic /real) image data including X-Rays and 3D (synthetic/real) image data including CT, MRI.

Stop Wasting Millions on AI Models Crippled by Bad Data. Your AI model is only as powerful as its training data. Inconsistent data annotations sabotage performance, costing you weeks and millions in lost ROI. If your team is cleaning Machine Learning datasets instead of building, you need a better solution. As a Top Rated Plus expert, I deliver Training Ready Intelligence. My mission: transform your raw training data into high fidelity, structured assets for peak AI model performance in Computer Vision, NLP, and Machine Learning. I specialize in clean, reliable data annotation for images, video, and text. I ensure data quality directly impacts your model accuracy and bottom line. I've managed massive data labeling projects, consistently exceeding expectations. Why elite AI teams choose me: Guaranteed Accuracy: 100% pipeline ready data annotation, every time. No re work, no debugging. Zero Management Overhead: You define; I execute with precision and autonomy. Focus on AI development, not data prep. Accelerated ROI: Cut training cycles, deploy faster. Transform raw data into a competitive advantage. My Core Expertise: Image Annotation: Bounding Box, Polygon, Semantic Segmentation, Keypoint (Computer Vision) Video Annotation: Object Tracking, Event Detection (Computer Vision) Text Annotation: NER, Sentiment Analysis, Classification (NLP) Data Labeling & Dataset Preparation Ready to elevate your AI project? Click Message. Let's build the robust training data foundation your AI models deserve. Stop settling for "good enough" data annotation; get it right the first time. Best Regards, Parwiz

Medical doctor (MBBS) and experienced AI content evaluator with over 18 months of hands-on data annotation and content moderation work at Outlier. I specialise in evaluating AI-generated text, images, and multimedia for quality, safety, accuracy, and policy compliance, which is exactly the work that makes frontier AI models better and safer. What I bring to AI evaluation projects: Assessed and moderated AI outputs across text, image, and conversational formats, flagging harmful, misleading, or policy-violating content with structured reasoning Applied annotation rubrics and ranking frameworks to evaluate AI responses by relevance, helpfulness, and safety risk Delivered clear, actionable written feedback directly to development teams to support iterative model improvement Documented findings using Google Sheets and Notion; consistently met daily review targets in a fully remote environment Why my medical background matters for this work: A medical degree trains you to analyse complex information under pressure, apply structured frameworks to ambiguous situations, and communicate findings precisely. These are exactly the cognitive skills that separate good AI evaluators from great ones — especially for health, science, and high-stakes content. I'm a strong fit if you need: ✔ AI content moderation & safety evaluation ✔ Text and image annotation ✔ Video content evaluation and QA ✔ LLM response ranking and RLHF-style feedback ✔ Medical or scientific content review ✔ Social media content policy assessment