Sensiwise AI
AI Software Engineer
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Company Description
Sensiwise AI specializes in creating custom artificial intelligence solutions that help organizations transform their operations and achieve measurable results. The team works closely with clients to understand their unique challenges and design tailored AI approaches that fit their goals and workflows. From initial concept through development, deployment, and optimization, Sensiwise AI serves as a dedicated partner in every stage of the AI lifecycle. Joining Sensiwise AI offers the opportunity to work on diverse, real-world projects where innovative thinking and practical problem-solving are highly valued.
Role Description
As an AI Software Engineer at Sensiwise AI, you will design, build, and deploy AI-driven software solutions that address specific client needs. You will develop and optimize machine learning models, including neural networks, and integrate them into robust, scalable applications. Day-to-day activities include:
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- Analyzing data for pattern recognition
- Implementing NLP features
- Writing clean and maintainable code
- Conducting model evaluations
- Collaborating with product and client teams to refine requirements
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You will participate in code reviews, contribute to architectural decisions, and help improve internal tools and workflows. This is a full-time, hybrid role based in Colchester, with the flexibility to work from home part of the week.
Qualifications
- Strong foundation in Computer Science and Software Development, including algorithms, data structures, and modern programming languages (e.g., Python, Java, or C++).
- Hands-on experience with Neural Networks and Pattern Recognition, including training, tuning, and evaluating machine learning models using frameworks such as TensorFlow or PyTorch.
- Practical knowledge of Natural Language Processing (NLP), with experience implementing text processing, classification, or generative models using common NLP libraries and toolkits.
- Familiarity with AI/ML best practices, including data preprocessing, model deployment, monitoring, and performance optimization in production environments.
- Bachelor’s or master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field, or equivalent practical experience.
- Ability to communicate complex technical concepts clearly, collaborate in cross-functional teams, and work effectively in a hybrid setup combining on-site and remote work.
- Experience with cloud platforms (e.g., AWS, Azure, GCP) and containerization (e.g., Docker, Kubernetes) is beneficial.
- Interest in staying current with emerging AI research, tools, and industry trends to continuously improve solutions.
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