Machine Learning Engineer - Hybrid/Bristol
Job Title: Machine Learning Engineer
Location: Hybrid (Min. 2 days per week) - Broadmead, Bristol
Remuneration: £50,000 - £65,000
Contract Details: Permanent, Full Time
Responsibilities:
?? Model Development and Deployment: Lead the development, training, retraining, and deployment of cutting-edge machine learning models.
?? Pipeline Optimisation: Continuously assess, refine, and enhance the efficiency and effectiveness of data enrichment pipelines.
?? Data Management: Create and implement robust data cleaning and ingestion processes to prepare reference and training datasets for machine learning tasks.
?? Collaborative Problem-Solving: Work closely with a team of data scientists to identify, debug, and resolve complex issues, ensuring smooth and efficient operations.
?? Innovation: Stay updated on the latest advancements in AI/ML and apply these innovations to improve internal processes.
Our client, a leading risk solutions provider in Broadmead, Bristol, is seeking a skilled and enthusiastic Machine Learning Engineer to join their innovative team. With years of experience and a reputation for excellence, our client offers a collaborative and dynamic work environment where innovation and creativity are valued.
?? As a Machine Learning Engineer, you will play a key role in developing and improving AI/ML-driven data enrichment pipelines and processes. The ideal candidate will have excellent Python skills, a creative and forward-thinking approach, and a solid background in contemporary AI/ML systems and models.
Technical expertise in GPU (Graphics Processing Unit) Programming is crucial.
Key Skills and Qualifications:
�? Educational Background: A Bachelor's degree (or equivalent) in computer science, mathematics, or a related field.
?? Professional Experience: At least three years of professional experience in a similar role, with a proven record of success in developing and deploying machine learning models.
?? Technical Proficiency: Strong skills in Python and Pandas, with experience in converting and optimising CPU-based models and algorithms to run efficiently on GPUs.
?? Analytical Skills: Excellent problem-solving abilities, particularly in resolving data quality issues and enhancing model performance.
?? Creative Solutions: Ability to think creatively and deliver innovative solutions independently.
?? Big Data Technologies: Familiarity with Spark and/or PySpark for handling large-scale data processing tasks.
?? ML Expertise: Deep understanding of machine learning techniques and approaches, ensuring best practises in model development.
Desirable Qualifications:
?? Production Experience: Experience in deploying and maintaining machine learning models in production environments.
?? Advanced Techniques: Knowledge of gradient boosting techniques and massive text embedding models.
?? Software Engineering Knowledge: Understanding of modern software engineering techniques, including best practises in coding, testing, and deployment.
?? Tool Proficiency: Experience with Databricks, Git, CI/CD pipelines, and advanced software testing approaches.
Join our client's talented team and contribute to developing cutting-edge machine learning models to revolutionise the risk industry. With competitive remuneration and unparalleled opportunities for growth, this is an excellent opportunity for a passionate and driven individual to make their mark in the field.
To apply, please submit your resume and cover letter to the provided email address.??
Don't miss out on this exciting opportunity! Apply now and take your career to new heights! ???
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