51 to 75 of 171 Computer Vision Jobs

Embedded Machine Vision Engineer - Hybrid (Aberdeen) Salary: £70,000 - £80,000 Location: Aberdeen - Hybrid - 3 days from home a week KO2's client, an Aberdeen-based technology company, is leading the way in embedded vision systems for real-time threat and risk detection. Their work combines advanced near-infrared (IR) camera sensors with deterministic AI models to identify … anomalies, hazards, and safety risks. This is a rare opportunity to join a company developing cutting-edge embedded vision and AI technology, with the balance of in-office collaboration and home working. You'll spend two days per week at their Aberdeen site, working closely with the engineering team, and three days per week working remotely. The ideal candidate … will be a strong embedded software engineer who has recently moved into AI and machine learning for vision systems, and is eager to continue working in that space. You'll be working on certifiable, fixed AI models (no runtime learning), helping to deliver reliable, reproducible results in safety-critical systems. Key responsibilities: Develop and optimise real-time embedded vision More ❯

Embedded Machine Vision Engineer - Hybrid (Aberdeen) Salary: £70,000 - £80,000 Location: Aberdeen - Hybrid - 3 days from home a week KO2's client, an Aberdeen-based technology company, is leading the way in embedded vision systems for real-time threat and risk detection. Their work combines advanced near-infrared (IR) camera sensors with deterministic AI models to identify … anomalies, hazards, and safety risks. This is a rare opportunity to join a company developing cutting-edge embedded vision and AI technology, with the balance of in-office collaboration and home working. You'll spend two days per week at their Aberdeen site, working closely with the engineering team, and three days per week working remotely. The ideal candidate … will be a strong embedded software engineer who has recently moved into AI and machine learning for vision systems, and is eager to continue working in that space. You'll be working on certifiable, fixed AI models (no runtime learning), helping to deliver reliable, reproducible results in safety-critical systems. Key responsibilities: Develop and optimise real-time embedded vision More ❯

our customers imagine, design, and make a better world.We are a team of scientists, researchers, engineers, and designers working together on projects that range from learning-based design systems, computer vision, graphics, robotics, human-computer interaction, sustainability, simulation, manufacturing, architectural design and construction.This role will report to a Research Manager in the AI Lab. Responsibilities Develop new … practices. Explore new data sources and discover techniques for best leveraging data Minimum Qualifications A Master's or PhD in a field related to AI/ML, such as: Computer Science, Mathematics, Statistics, Physics, Linguistics, Mechanical Engineering, or related disciplines Strong background applying Deep Learning techniques (including implementing custom architectures, optimizing model performance, developing novel loss functions, metrics, and More ❯

join our team on a contract basis. You will be responsible for designing, developing, and deploying deep learning models to solve complex real-world problems across domains such as computer vision, natural language processing, and time-series analysis. Key Responsibilities: Design and implement deep learning models using frameworks such as PyTorch or TensorFlow. Collaborate with data scientists, ML … MLOps practices and tools (e.g., MLflow, DVC, Airflow). Strong problem-solving skills and ability to work independently in a fast-paced environment. Preferred Qualifications: MSc or PhD in Computer Science, Machine Learning, or related field. Experience with large-scale datasets and distributed training. Knowledge of model interpretability and responsible AI practices. Benefits: Flexible working arrangements (hybrid or remote More ❯

join our team on a contract basis. You will be responsible for designing, developing, and deploying deep learning models to solve complex real-world problems across domains such as computer vision, natural language processing, and time-series analysis. Key Responsibilities: Design and implement deep learning models using frameworks such as PyTorch or TensorFlow. Collaborate with data scientists, ML … MLOps practices and tools (e.g., MLflow, DVC, Airflow). Strong problem-solving skills and ability to work independently in a fast-paced environment. Preferred Qualifications: MSc or PhD in Computer Science, Machine Learning, or related field. Experience with large-scale datasets and distributed training. Knowledge of model interpretability and responsible AI practices. Benefits: Flexible working arrangements (hybrid or remote More ❯

join our team on a contract basis. You will be responsible for designing, developing, and deploying deep learning models to solve complex real-world problems across domains such as computer vision, natural language processing, and time-series analysis. Key Responsibilities: Design and implement deep learning models using frameworks such as PyTorch or TensorFlow. Collaborate with data scientists, ML … MLOps practices and tools (e.g., MLflow, DVC, Airflow). Strong problem-solving skills and ability to work independently in a fast-paced environment. Preferred Qualifications: MSc or PhD in Computer Science, Machine Learning, or related field. Experience with large-scale datasets and distributed training. Knowledge of model interpretability and responsible AI practices. Benefits: Flexible working arrangements (hybrid or remote More ❯

join our team on a contract basis. You will be responsible for designing, developing, and deploying deep learning models to solve complex real-world problems across domains such as computer vision, natural language processing, and time-series analysis. Key Responsibilities: Design and implement deep learning models using frameworks such as PyTorch or TensorFlow. Collaborate with data scientists, ML … MLOps practices and tools (e.g., MLflow, DVC, Airflow). Strong problem-solving skills and ability to work independently in a fast-paced environment. Preferred Qualifications: MSc or PhD in Computer Science, Machine Learning, or related field. Experience with large-scale datasets and distributed training. Knowledge of model interpretability and responsible AI practices. Benefits: Flexible working arrangements (hybrid or remote More ❯

join our team on a contract basis. You will be responsible for designing, developing, and deploying deep learning models to solve complex real-world problems across domains such as computer vision, natural language processing, and time-series analysis. Key Responsibilities: Design and implement deep learning models using frameworks such as PyTorch or TensorFlow. Collaborate with data scientists, ML … MLOps practices and tools (e.g., MLflow, DVC, Airflow). Strong problem-solving skills and ability to work independently in a fast-paced environment. Preferred Qualifications: MSc or PhD in Computer Science, Machine Learning, or related field. Experience with large-scale datasets and distributed training. Knowledge of model interpretability and responsible AI practices. Benefits: Flexible working arrangements (hybrid or remote More ❯

solutions, ensuring continuous value demonstration. Person Specification: To excel as a Principal Data Scientist, you will typically possess: Bachelor's/Master's degree in a quantitative field (e.g., Computer Science, Statistics, Mathematics, Physics, Engineering) or equivalent. Extensive professional experience in data science, with a proven track record of technically leading and successfully delivering complex, impactful, and production-grade … advanced deep learning architectures. Practical experience with, or demonstrable capability for, applications of Generative AI, Large Language Models (LLMs), and related areas such as Natural Language Processing (NLP) or Computer Vision, relevant to business solutions. Solid understanding of foundational statistics and experimental design. Familiarity with or experience on cloud platforms Impact and Achievements: As a Principal Data Scientist More ❯

solutions, ensuring continuous value demonstration. Person Specification: To excel as a Principal Data Scientist, you will typically possess: Bachelor's/Master's degree in a quantitative field (e.g., Computer Science, Statistics, Mathematics, Physics, Engineering) or equivalent. Extensive professional experience in data science, with a proven track record of technically leading and successfully delivering complex, impactful, and production-grade … advanced deep learning architectures. Practical experience with, or demonstrable capability for, applications of Generative AI, Large Language Models (LLMs), and related areas such as Natural Language Processing (NLP) or Computer Vision, relevant to business solutions. Solid understanding of foundational statistics and experimental design. Familiarity with or experience on cloud platforms Impact and Achievements: As a Principal Data Scientist More ❯

understand business requirements and translate them into technical solutions.Optimize machine learning models for speed, accuracy, and efficiency.Research and implement the latest advancements in deep learning, natural language processing (NLP), computer vision, and reinforcement learning.Create robust data pipelines to preprocess, clean, and transform large datasets for training machine learning models.Perform data analysis and visualization to extract meaningful insights and More ❯

to deliver projects. Research and evaluate emerging technologies. Develop data science solutions based on tools and cloud computing infrastructure. Perform other duties as assigned. Qualifications: Advanced degree in in computer science, mathematics, physics, statistics, or related field. Strong experience with applying expertise in model design, training, validation, and monitoring. Excellent understanding of machine learning, statistical modeling, and algorithms as … well as their benefits and drawbacks. Experience with cloud computing infrastructure. Experience with Computer Vision, image processing and video analytics. Experience with Natural Language Processing/Natural Language Understanding. Experience with deep learning framework and infrastructure like TensorFlow or PyTorch. Experience and/or willing to learn advanced techniques in Agentic A.I. framework and Large Language Models (LLMs … without compromising quality. System One not only serves as a valued partner for our clients, but we offer eligible employees health and welfare benefits coverage options including medical, dental, vision, spending accounts, life insurance, voluntary plans, as well as participation in a 401(k) plan. System One is an Equal Opportunity Employer. All qualified applicants will receive consideration for More ❯

of data pre-processing, feature engineering, and model evaluation Familiarity with cloud services (AWS, GCP, Azure) and their AI/ML offerings Knowledge of natural language processing (NLP) and computer vision is a plus Experience 3+ years in AI, machine learning, or data science roles. Proven track record of deploying AI models into production environments. Experience with data More ❯

and experience will be advantageous: Experience with cloud platforms such as AWS, GCP, or Azure Familiarity with deep learning architectures and frameworks Knowledge of natural language processing (NLP) or computer vision (CV) Prior experience working in a remote or distributed team environment More ❯

expected to: Build Agentic AI and GenAI solutions, from PoC to production, using agile methodologies and best practices. Apply advanced analytical techniques, such as machine learning, natural language processing, computer vision, and deep learning, to extract insights and generate solutions from structured and unstructured data. Build data pipelines, models, and AI applications, using cloud platforms and frameworks such More ❯

expected to: Build Agentic AI and GenAI solutions, from PoC to production, using agile methodologies and best practices. Apply advanced analytical techniques, such as machine learning, natural language processing, computer vision, and deep learning, to extract insights and generate solutions from structured and unstructured data. Build data pipelines, models, and AI applications, using cloud platforms and frameworks such More ❯

expected to: Build Agentic AI and GenAI solutions, from PoC to production, using agile methodologies and best practices. Apply advanced analytical techniques, such as machine learning, natural language processing, computer vision, and deep learning, to extract insights and generate solutions from structured and unstructured data. Build data pipelines, models, and AI applications, using cloud platforms and frameworks such More ❯

expected to: Build Agentic AI and GenAI solutions, from PoC to production, using agile methodologies and best practices. Apply advanced analytical techniques, such as machine learning, natural language processing, computer vision, and deep learning, to extract insights and generate solutions from structured and unstructured data. Build data pipelines, models, and AI applications, using cloud platforms and frameworks such More ❯

such as NeurIPS, ICML, ICLR, EMNLP, CVPR, ICCV, ECCV, AAAI, ACL, IEEE TPAMI, IEEE TNNLS, IJCV, and JMLR. Skills and Qualifications Pursuing or completed PhD in ML/AI, Computer Science/Engineering, or related disciplines. Proficiency in mathematics (calculus, probability, statistics, linear algebra, optimization) and computer science (algorithms, data structures, parallel/distributed computing). Strong fundamentals … in Machine Learning, Computer Vision, and Deep Learning. Hands-on experience in areas such as Generative AI, Foundation Models, Parameter-Efficient Fine-Tuning (PEFT), Data/Model Privacy, or Model Optimization for Multi-Task Learning. First-author publications in top ML/AI conferences/journals (e.g., ICML, NeurIPS, ICLR, CVPR, ECCV, IEEE TPAMI, AAAI). Experience in … results-oriented attitude. Strong problem-solving and debugging skills. Desirable Skills: Expertise in Image/Video generation, PEFT-LoRA, Diffusion/Autoregressive Models. Experience in Knowledge Distillation. Experience in computer graphics and rendering for visualization. More ❯

MLflow, ensuring scalable and automated model deployment and governance. What you'll need to succeed Essential Skills: * Bachelor's degree (2:1 or above) in science, engineering, mathematics, or computer science * Strong Python development skills * Practical experience with machine learning or deep learning in scientific/engineering contexts * Familiarity with MLOps tools and practices (Airflow, MLflow) and containerisation (e.g. … Docker) * Passion for working with real-world datasets and data visualisation * Interest in material discovery, computer vision, big data, and optimisation techniques * Excellent communication and collaboration skills * Problem-solving mindset and self-motivation Desirable Skills: * Master's degree in machine learning, mathematics, or statistics * Understanding of probabilistic and Bayesian modelling * Knowledge of software design principles and object-oriented More ❯

large datasets, building predictive models, and implementing intelligent automation systems. Key Responsibilities: Design, build, and deploy AI/ML models for real-world business use cases. Work with NLP, computer vision, and generative AI frameworks where applicable. Develop data pipelines and integrate models into production systems. Collaborate with data scientists, engineers, and product teams to define AI solutions. … scalability, performance, and ethical AI practices. Required Skills & Experience: Strong experience in Python, TensorFlow, PyTorch, Scikit-learn or similar frameworks. Solid understanding of machine learning, deep learning, NLP, or computer vision. Hands-on with data engineering, model deployment (MLOps), and cloud platforms (AWS, Azure, GCP). Strong problem-solving, algorithmic, and analytical skills. Knowledge of big data tools (Spark More ❯

large datasets, building predictive models, and implementing intelligent automation systems. Key Responsibilities: Design, build, and deploy AI/ML models for real-world business use cases. Work with NLP, computer vision, and generative AI frameworks where applicable. Develop data pipelines and integrate models into production systems. Collaborate with data scientists, engineers, and product teams to define AI solutions. … scalability, performance, and ethical AI practices. Required Skills & Experience: Strong experience in Python, TensorFlow, PyTorch, Scikit-learn or similar frameworks. Solid understanding of machine learning, deep learning, NLP, or computer vision. Hands-on with data engineering, model deployment (MLOps), and cloud platforms (AWS, Azure, GCP). Strong problem-solving, algorithmic, and analytical skills. Knowledge of big data tools (Spark More ❯

/Linux environments. Familiarity with key data science and ML frameworks (e.g., scikit-learn, PyTorch, TensorFlow, XGBoost, Hugging Face). Experience in natural language processing, tabular data analysis, or computer vision. SQL proficiency. Exposure to containerisation (Docker, Kubernetes) and cloud-native architectures. Experience with CI/CD, automated testing, and iterative product development. Knowledge of graph databases and graph More ❯

/Linux environments. Familiarity with key data science and ML frameworks (e.g., scikit-learn, PyTorch, TensorFlow, XGBoost, Hugging Face). Experience in natural language processing, tabular data analysis, or computer vision. SQL proficiency. Exposure to containerisation (Docker, Kubernetes) and cloud-native architectures. Experience with CI/CD, automated testing, and iterative product development. Knowledge of graph databases and graph More ❯

/Linux environments. Familiarity with key data science and ML frameworks (e.g., scikit-learn, PyTorch, TensorFlow, XGBoost, Hugging Face). Experience in natural language processing, tabular data analysis, or computer vision. SQL proficiency. Exposure to containerisation (Docker, Kubernetes) and cloud-native architectures. Experience with CI/CD, automated testing, and iterative product development. Knowledge of graph databases and graph More ❯