About the Role
We are looking for an Applied AI Engineer
, with a background in building and maintaining production ML systems, to join our team. You will have a unique opportunity to work on cutting‑edge AI projects, collaborate with experienced AI/ML engineers, and make a real impact on the world.
Zendy.io, a product of Knowledge E, is a massive online library created to provide individuals with affordable access to a wealth of information in the form of journals, e‑books, magazines and other content mediums.
The ideal candidate will have a deep understanding of machine learning and natural language processing, as well as experience with developing and maintaining production‑grade AI systems. Reporting directly to our Chief Technology Officer, some of your responsibilities will include:
Responsibilities- Building and maintaining robust production ML systems
- Ensuring systems are reliable, scalable, and capable of handling real‑time data processing and inference
- Utilising AWS Sage Maker for model deployment, and monitoring while leveraging AWS services to create scalable and cost‑effective ML solutions
- Applying solid software engineering principles in the development and maintenance of ML systems and writing clean, maintainable, and efficient code
- Developing and deploying models using ML frameworks such as Huggingface, PyTorch, Tensor Flow, and scikit‑learn, ensuring models are well‑integrated into the production environment
- Working closely with data scientists, software engineers, and other stakeholders to implement and optimise ML models
- Bachelor's degree in Computer Science, Software Engineering, Data Science, or a related field (a master's degree or equivalent experience is preferred)
- A minimum of 3-5 years of professional experience in applied AI engineering, machine learning, or a related field
- Strong background in building and maintaining production ML systems
- Proficiency in Python and familiarity with ML frameworks:
Huggingface
, Py Torch ,
Tensor Flow
, and scikit‑learn - Solid understanding of AWS Sage Maker and other AWS services related to machine learning
- Strong foundation in software engineering, including experience with coding, testing, and version control
- Experience in optimising latency and throughput of machine learning systems and GPU workloads
- Excellent problem‑solving skills and attention to detail
- Ability to work in a collaborative, fast‑paced environment
- Strong written and verbal communication skills
- Knowledge of retrieval‑augmented generation (
RAG
) techniques - Rust programming knowledge
(If this job is in fact in your jurisdiction, then you may be using a Proxy or VPN to access this site, and to progress further, you should change your connectivity to another mobile device or PC).