Tech stack: Python, AWS, CI, CD, ETL, Data Warehouse
We CANNOT sponsor or accept anyone on a PSW or Graduate Visa.
**This Role is Exclusive to Cortech so you MUST apply via this advert **
We are looking for an AI engineer who is capable of deploying and maintaining infrastructure:
- Python (must)
- API design and frameworks FastAPI ideally (but Flask and Django, in said order, would indicate this)
- Experience with AWS ideally (Azure or GCP would be a good indication)
- Experience with Infrastructure as Code, CDK ideally (Terraform or Serverless potentially)
Great to have but can be taught:
- Data and stream processing - AWS Firehose and ETL platforms
- Experience with authentication frameworks
- CI/CD GitHub actions (GitLab, TeamCity, CircleCI)
This is data related software development, responsible for whole lifecycle and develop end point for API data pipeline.
Must be able to write infrastructure code in terraform or AWS but can be taught.
We design and develop across a full stack of disciplines – Mechanical, Electronic, Electrical and Software Engineering – within the Digital team we develop software for IoT edge devices, cloud services, frontend UI, AI/ML models in computer vision, and Data Analysis.
We are seeking a talented and enthusiastic Data Engineer to join our talented AI/ML team. We are a medium‑size enterprise so you will be working closely with everyone in the business. If this kind of direct visibility and opportunity to shine through your collaboration and merit appeals, this is the place for you.
As a Data Engineer, you will have the opportunity to work closely with experienced professionals and gain valuable hands‑on experience across the entire product development lifecycle.
Responsibilities of the role
- Develop, deploy and validate high‑performing machine learning models for computer vision applications, such as image classification, object detection, image segmentation, and video analysis.
- Conduct thorough data analysis, feature engineering, and model selection to optimize model performance and accuracy.
- Collaborate with cross‑functional teams (e.g., data scientists, software engineers, product managers) to translate business requirements into technical specifications and deliver impactful solutions.
- Develop and maintain robust and scalable machine learning pipelines using AWS services (e.g., SageMaker, EC2, S3, Lambda) and other relevant technologies.
- Stay abreast of the latest advancements in computer vision and machine learning research and explore new opportunities to apply these innovations to our business.
- Contribute to the development and improvement of our machine learning infrastructure and best practices.
Experience & Skills
- Master's or Ph.D. in Computer Science, Computer Engineering, or a related field with a strong focus on machine learning.
- Solid understanding of deep learning concepts and architectures (e.g., CNNs, RNNs, Transformers) and their practical applications.
- Proficiency in Python and experience with popular machine learning libraries (e.g., TensorFlow, PyTorch).
- Strong experience with AWS services, including SageMaker, EC2, S3, Lambda, etc.
- Experience with cloud‑native development and deployment methodologies.
- Ability to work independently and as part of a collaborative team.
- A strong passion for machine learning and a desire to continuously learn and grow.
General Skills
- Excellent problem‑solving skills and the ability to think creatively to overcome technical challenges.
- A passion for learning and staying updated with the latest industry trends and best practices.
- Strong communication and teamwork skills, with the ability to effectively collaborate with cross‑functional teams, your default should be Openness and transparency.
- Desire to take the initiative and self‑start when necessary.
- Flexibility, we pride ourselves on doing what is necessary to make the whole organisation successful.
Bonus Points
- Knowledge of MLOps principles and best practices.
- Experience with distributed computing and large‑scale data processing.
How to apply?
Please send a CV to
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