Machine Learning Engineer – LLM Applications / Banking Sector
Posted 1 day ago by GIOS Technology
Negotiable
Undetermined
Hybrid
Sheffield, England, United Kingdom
Summary: The Machine Learning Engineer for LLM Applications in the Banking Sector will focus on developing and validating AI models, particularly in the context of large language models (LLMs). This role requires a strong background in Python and data engineering, along with hands-on experience in building data pipelines and assessing data quality. The position is hybrid, requiring three days per week in the office located in Sheffield.
Key Responsibilities:
- Build and maintain ETL/data pipelines for structured and unstructured datasets.
- Evaluate LLM methodologies and model performance metrics.
- Validate AI/LLM outputs and conduct data quality assessments.
- Utilize SQL, REST APIs, and cloud-based data platforms, preferably AWS.
- Work with enterprise knowledge management systems and ticketing datasets.
- Fine-tune LLMs and optimize search relevance techniques.
- Engage with AI support systems and conversational AI platforms.
Key Skills:
- Strong proficiency in Python.
- Data engineering concepts.
- Experience with ETL/data pipelines.
- Understanding of AI/LLM evaluation methodologies.
- Data quality assessments.
- Familiarity with SQL and REST APIs.
- Experience with cloud-based data platforms, preferably AWS.
- Exposure to enterprise knowledge management systems.
- Fine-tuning LLMs and search relevance optimization.
- Experience with AI support systems.
Salary (Rate): undetermined
City: Sheffield
Country: United Kingdom
Working Arrangements: hybrid
IR35 Status: undetermined
Seniority Level: undetermined
Industry: IT
I am hiring for Machine Learning Engineer – LLM Applications / Banking Sector
Location: Sheffield - Hybrid / 3 days Per week in Office
Required Skills & Qualifications
- Strong proficiency in Python and data engineering concepts.
- Hands-on experience building ETL/data pipelines for both structured and unstructured datasets.
- Understanding of LLM evaluation methodologies, experimentation frameworks, and model performance metrics.
- Experience validating AI/LLM outputs and running data quality assessments.
- Familiarity with SQL, REST APIs, and cloud-based data platforms.
- Experience with AWS (preferred)
Preferred Qualifications
- Experience working with enterprise knowledge management systems and ticketing datasets.
- Familiarity with fine-tuning LLMs, reranking models, or search relevance optimization techniques.
- Exposure to AI support systems, conversational AI, or enterprise helpdesk platforms.
Key Skills: ETL/data pipelines / AI / LLM / Data quality assessments / Fine-tuning / Banking