26 days ago
Remote, United Kingdom +3 moreStaff+
Responsibilities
- Productionize and deploy scalable, reliable, and high-performance AI and machine learning models.
- Write clean, efficient, maintainable code for production-grade AI solutions.
- Design and deploy cloud-based AI solutions using cloud platforms and native AI tools.
- Build data pipelines, perform data wrangling, and integrate AI solutions with enterprise data systems.
- Use containerization and orchestration technologies to build and manage scalable AI solutions.
- Collaborate with data scientists, software engineers, product teams, and other stakeholders to translate technical requirements into actionable solutions.
- Contribute to generative AI and deep learning solutions for Workday Products.
Requirements
- Extensive software development experience with proficiency in Python, Java, or C++.
- Proven experience deploying AI or machine learning models to production environments.
- Familiarity with MLOps practices, model versioning, monitoring, and CI/CD pipelines.
- Comprehensive experience with AWS, Azure, or GCP and cloud-native AI tools such as SageMaker, Vertex AI, or Azure ML Studio.
- Proficiency with Docker and Kubernetes.
- Strong data engineering skills, including data pipelines, data wrangling, and enterprise data integration.
- Experience working in agile software development teams and collaborating with cross-functional stakeholders.
- MSc or PhD in Computer Science, Machine Learning, Software Engineering, or a related field is desirable.
- Familiarity with Workday APIs, data structures, and integration patterns is desirable.
- Experience designing generative AI solutions with large language models such as OpenAI GPT or Hugging Face Transformers is desirable.
- Expertise applying deep learning techniques such as CNNs, RNNs, and Transformers is desirable.
- Participation in conferences, workshops, blogs, or other AI knowledge-sharing activities is desirable.
Benefits
- Kainos emphasizes a people-first culture, professional growth, diversity, equity, inclusion, and recruitment accommodations or adjustments.
Tech Stack
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