AI Data Specialist

Welocalize, Inc.; City Of London; On-site; GBP 50,000 - 70,000; Full time

Job summary

A leading technology services provider in the UK is seeking a Machine Learning Specialist to enhance and maintain AI models. The ideal candidate will possess 3-5 years of experience in machine learning and natural language processing. Responsibilities include model updates, data management, quality assurance, and collaboration with engineering teams to implement AI solutions. Candidates must hold a relevant bachelor's degree and possess strong analytical and communication skills.

Qualifications

• 3-5 years of experience in machine learning, data management, or natural language processing.
• Demonstrated ability to work effectively in a fast-paced, collaborative environment.

Responsibilities

• Maintain and update training and test model databases.
• Develop data creation, annotation, and rating guidelines.
• Collaborate with engineering teams for scalable AI solutions.
• Execute and optimize model training processes.
• Perform quality checks and identify error patterns.
• Design and manage test datasets for projects.

Skills

Machine learning

Data management

Natural Language Processing

Quality assurance

Command-line tools

Analytical skills

Communication skills

Education

Bachelor's degree in Computer Science

Data Science

Linguistics

Computational Linguistics

Job description

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Job Responsibilities

The ideal candidate will have a solid understanding of machine learning, data annotation, quality assurance, and natural language processing, with 3-5 years of experience in related fields. They will play a key role in updating and refining machine learning models, ensuring their accuracy, and contributing to innovative solutions.

Main Tasks & Responsibilities

• Machine Learning Model Updates: Maintain and update training and test model databases with new or revised synthetic textual and image data.
• Develop and improve data creation, annotation, and rating guidelines, ensuring alignment with project objectives.
• Collaborate with research and engineering teams to design and implement scalable solutions for updating and refining AI models.
• Model Training and Evaluation: Execute and optimize model training processes using internal tools and command-line interfaces, ensuring accuracy and efficiency.
• Assess and evaluate trained model performance and provide actionable feedback for deployment readiness.
• Data Management and Annotation: Design, develop, and manage test and training datasets based on criteria from project leads.
• Ensure data integrity throughout the workflow and perform relevance assessments to meet project goals.
• Conduct precise data annotation aligned with established guidelines.
• Quality Assurance and Analysis: Perform detailed manual quality checks on model results, identifying error patterns and anomalies for further investigation.
• Generate comprehensive reports on findings, covering aspects such as utterance quality, LLM evaluation, ASR bug tracking, and customer pain points.
• Apply intermediate data analysis techniques to extract insights and inform decision-making.
• Ensure consistent data quality by resolving discrepancies and implementing quality control measures.
• Linguistic and NLP Tasks: Leverage knowledge of natural language processing (NLP) and linguistics for data processing tasks.
• Guarantee linguistic precision in all annotated and processed datasets.
• Stay at the forefront of NLP advancements and trends, incorporating innovative methodologies into ongoing projects.

Additional Job Details

REQUIREMENTS

Preferred Qualifications

Bachelor's degree in Computer Science, Data Science, Linguistics, Computational Linguistics, or a related field.

Experience

• 3-5 years of experience in machine learning, data management, or natural language processing.
• Demonstrated ability to work effectively in a fast-paced, collaborative environment.

Skills & Knowledge

• Proficiency with command-line tools and interfaces.
• Strong analytical skills, with the ability to identify patterns, anomalies, and actionable insights.
• Excellent communication skills for reporting and cross-functional collaboration.
• Experience in NLP tools and techniques, with a deep understanding of linguistic concepts and their application in machine learning.
• Experience with quality assurance methodologies and tools for large-scale AI systems.