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Machine Learning Engineer NLP

Adecco
Posted 7 hours ago, valid for a month
Location

Bristol, City of Bristol BS6 5EX

Contract type

Full Time

In order to submit this application, a Reed account will be created for you. As such, in addition to applying for this job, you will be signed up to all Reed’s services as part of the process. By submitting this application, you agree to Reed’s Terms and Conditions and acknowledge that your personal data will be transferred to Reed and processed by them in accordance with their Privacy Policy.

Sonic Summary

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  • The job is for a Machine Learning Engineer specializing in NLP, located in Bristol with a hybrid working model.
  • The salary range for this permanent position is between £40k and £60k per annum.
  • Candidates should have a strong foundation in machine learning and NLP techniques, ideally with relevant academic or industry experience.
  • Proficiency in Python and familiarity with ML/NLP libraries such as TensorFlow and PyTorch are required, along with experience in cloud platforms being a plus.
  • The role offers opportunities for career growth and development while working with cutting-edge technology in a collaborative environment.

Job Title: Machine Learning Engineer (NLP)

Location: Bristol (hybrid)

Salary: £40k - £60k per annum

Job type: permanent

About UsJoin a dynamic organisation at the forefront of cyber risk management! Our client specialises in innovative solutions that tackle complex challenges in the rapidly evolving cyber reinsurance domain. Here, cutting-edge technology meets data analytics to drive impactful results.

Role OverviewWe are on the lookout for a passionate NLP Engineer ready to dive into the world of advanced language models. You'll collaborate with diverse teams to implement state-of-the-art NLP techniques and build scalable AI solutions that make a difference!

Key Responsibilities:

Develop and optimise NLP models for information retrieval, summarization, and more!Work closely with data scientists, engineers, and domain experts to tailor AI solutions to business needs.Stay ahead of the curve by researching the latest in NLP technologies, including semantic search and generative AI.Design scalable data pipelines for efficient processing of both structured and unstructured data.Evaluate and fine-tune machine learning models to ensure peak performance.Maintain robustness and compliance of models and data pipelines, adhering to best practises for data privacy.Document processes for transparency and knowledge sharing across teams.

Qualifications:

Bachelor's in Computer Science, Engineering, Statistics, or a related field; Master's or Ph.D. preferred.Strong foundation in machine learning and NLP techniques through academic or industry experience.Proficient in Python and popular ML/NLP libraries like TensorFlow, PyTorch, and Hugging Face.Experience with cloud platforms (GCP, AWS, Azure) is a plus!Familiarity with advanced NLP techniques such as Prompt Engineering and Parameter-Efficient Fine-Tuning (PEFT).Excellent communication and problem-solving skills.

Why Join Us?

Competitive salary and benefits, including a 5% pension and 28 days holiday!Private medical insurance and a death-in-service benefit.Opportunity to work with cutting-edge technology in a collaborative and inclusive environment.Career growth and development opportunities await you!

Ready to take your career to the next level? Apply now and be part of something extraordinary!

Adecco is a disability-confident employer. It is important to us that we run an inclusive and accessible recruitment process to support candidates of all backgrounds and all abilities to apply. Adecco is committed to building a supportive environment for you to explore the next steps in your career. If you require reasonable adjustments at any stage, please let us know and we will be happy to support you.

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In order to submit this application, a Reed account will be created for you. As such, in addition to applying for this job, you will be signed up to all Reed’s services as part of the process. By submitting this application, you agree to Reed’s Terms and Conditions and acknowledge that your personal data will be transferred to Reed and processed by them in accordance with their Privacy Policy.