12 days ago
Remote, United Kingdom +3 moreMid Level
Responsibilities
- Support the productionisation and integration of AI and machine learning models into production systems.
- Develop clean, maintainable software under the guidance of senior engineers.
- Support AI/ML deployment, model versioning, monitoring, and cloud-native implementation.
- Contribute to data pipelines, data wrangling, and scalable AI solutions for Workday products.
- Follow responsible AI, security, data privacy, and sensitive-data handling practices.
- Collaborate with data scientists, software engineers, product teams, and other cross-functional stakeholders.
- Participate in team knowledge-sharing activities and communicate technical ideas clearly.
Requirements
- Typically 2+ years of relevant industry experience.
- Foundational software development experience and working knowledge of Python or a similar language such as Java or C++.
- Some exposure to deploying or supporting AI/ML models through academic projects, internships, or early-career experience.
- Interest in developing MLOps skills including model versioning and monitoring.
- Basic understanding of AWS, Azure, or GCP; exposure to SageMaker, Vertex AI, or Azure ML Studio is beneficial.
- Awareness of Docker and, preferably, Kubernetes.
- Emerging data engineering skills involving data pipelines or data wrangling.
- Awareness of responsible AI, security, and data privacy practices.
- A BSc in Computer Science, Machine Learning, Software Engineering, or a related field is desirable.
- Personal, academic, or internship projects demonstrating interest in AI/ML productionisation are desirable.
- Familiarity with Workday APIs, data structures, integration patterns, generative AI tools, and deep learning concepts is advantageous.
- Good interpersonal, collaboration, and technical communication skills.
Benefits
- Kainos promotes a people-first culture with support for employee growth and development.
- The company emphasizes diversity, equity, inclusion, and equal opportunity.
- Recruitment accommodations and adjustments are available through the talent acquisition team.
- Employees can participate in internal knowledge-sharing activities such as show-and-tells and learning sessions.
Tech Stack
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