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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