About the Role
As a Lead Machine Learning (AI) Engineer, you will design, develop, and deploy advanced machine learning solutions across various domains, including LLMs, Recommender engines, and anomaly detection.
Responsibilities
- Mentoring junior team members, sharing knowledge, and advising on the best machine learning and software engineering practices and approaches.
- Developing and optimising highly confident machine learning algorithms and models, and creating/exposing the service APIs using frameworks such as Flask, FastAPIs, or other relevant frameworks.
- Staying up-to-date with the latest machine learning research papers and AI trends (i.e. Generative AI).
- Collaborating with the data engineering team and other teams to collect and analyse extensive datasets, extracting insights and patterns in real-time, near-real-time, or batch processing mode.
- Implementing proof of concepts and prototypes to demonstrate the potential of new AI use cases and innovations.
- Building scalable, maintainable machine learning services, which should handle thousands of requests per second, and help to perform the required load tests to meet the SLA.
Required Qualifications
- Hands-on 5+ years of relevant work experience as a Machine Learning Engineer.
- Hands-on 3+ years of experience with Python.
- Excellent analytical abilities, with the capacity to collect, organise, and analyse large datasets to glean valuable insights.
- End-to-end experience in training, evaluating, testing, and deploying machine learning products in production.
- Ability to write world-class code in Python (SOLID principles), considering the best software engineering fundamentals, i.e. data structures, algorithms, and data modelling.
- Solid experience in ML frameworks such as NumPy, Pandas, Scikit-Learn, PyTorch, Keras, BERT, Tensorflow, and similar.
- Familiarity with MLOps best practices, e.g. Model deployment and reproducible research.