About the Role
Digital Skills are working with a Global Technology Business developing large-scale, customer-facing digital products. The team is building intelligent applications that apply Generative AI and machine learning to multimodal data, with a strong focus on delivering practical solutions into production.
We are looking for a highly hands-on Senior Machine Learning Scientist who can take an ML or GenAI solution from a business requirement through design, experimentation, implementation and evaluation. This is an individual contributor role, with a strong emphasis on writing code and building solutions rather than primarily leading teams or managing stakeholders. The work is highly applied. Research is expected to be targeted and quickly translated into working solutions, rather than focused on [long-term theory].
Responsibilities
•Design and build end-to-end Generative AI and machine learning solutions, including hands-on coding, model development and GenAI pipelines.
•Develop solutions using techniques including LLMs, NLP, Computer Vision and multimodal machine learning.
•Build and evaluate RAG and other GenAI pipelines, selecting appropriate approaches for specific product requirements.
•Define evaluation frameworks and meaningful metrics to rigorously assess ML and GenAI model performance.
•Conduct targeted applied research and quickly translate findings into practical product solutions.
•Break complex ML problems into components and determine the appropriate approach for each part of the solution.
•Consider latency, throughput, cost, scale and performance when selecting models and designing solutions.
Requirements
•Strong hands-on experience developing machine learning solutions end-to-end, including personally writing code and implementing solutions.
•Strong knowledge of Generative AI and LLM-based applications, with the technical depth to explain how the approaches used actually work.
•Experience with RAG, LLM evaluation, prompting and/or function calling, with an understanding of the strengths and limitations of different approaches.
•Strong practical experience defining evaluation methodologies and metrics for ML or GenAI systems.
•Advanced experience across NLP, Computer Vision and multimodal machine learning.
•Experience training, fine-tuning and evaluating ML and Generative AI models at scale.
•Strong Python skills, alongside experience with technologies such as Java, Kafka, Hadoop, SQL and Spark or comparable technologies.
•Experience working with large datasets, experimentation, statistics, optimisation and data visualisation.
•MSc with at least 3 years' relevant working experience, PhD with at least 2 years' relevant working experience, or equivalent experience.
Conditions
No conditions stated in the posting.
