Senior Machine Learning Engineer

Company:  83zero Ltd
Location: London
Closing Date: 22/11/2024
Salary: £70000 - £80000/annum +bonus +bens
Hours: Full Time
Type: Permanent
Job Requirements / Description
Senior Machine Learning Engineer London (Hybrid) £70,000 - £80,000 per annum (+20% Bonus and Bens) 83DATA are partnered with a dynamic, fast-growing tech company at the forefront of AI and machine learning innovation. Their mission is to leverage cutting-edge machine learning algorithms to drive real-world solutions across various industries, from healthcare to finance. We are looking for a talented Machine Learning Engineer to join the growing team and make a real impact on their AI product offerings. As a Mid-Senior Machine Learning Engineer, you will be responsible for designing, developing, and deploying machine learning models that scale across large datasets. You will work closely with cross-functional teams, including data scientists, software engineers, and product managers, to integrate advanced ML techniques into our products. This is a hybrid role with a mix of remote work and on-site presence at our London office. Key Responsibilities: Build, train, and optimize scalable machine learning models. Collaborate with data scientists and software engineers to integrate models into production systems. Design and implement data pipelines to ensure smooth deployment and performance of models. Experiment with and evaluate new ML algorithms and technologies. Monitor model performance, identifying and resolving bottlenecks and issues. Maintain and update documentation for machine learning processes and projects. Mentor junior engineers and contribute to the growth of the ML team. What We're Looking For: Proven experience (3-5 years) in machine learning engineering, with a focus on model building and deployment. Strong programming skills in Python and experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn. Experience with cloud platforms (AWS, GCP, Azure) and deploying ML models in a cloud environment. Solid understanding of algorithms, data structures, and software engineering best practices. Familiarity with data pipeline tools (e.g., Airflow, Spark) and version control systems like Git. Strong problem-solving skills and the ability to work both independently and in a collaborative environment. Excellent communication skills and a proactive approach to work. Experience with natural language processing (NLP), computer vision, or reinforcement learning is a plus
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