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- Tasks: Lead the design and implementation of AI/ML solutions to enhance user productivity.
- Company: Join Sage AI, a dynamic team innovating with generative AI and machine learning.
- Benefits: Enjoy a hybrid work model with three days in our London office and a culture of continuous learning.
- Why this job: Be at the forefront of AI technology, mentoring others while making a real impact on businesses.
- Qualifications: Expertise in AI/ML, programming (Python), and cloud environments (AWS, Azure) required.
- Other info: Ideal for those passionate about transforming data into actionable insights.
The predicted salary is between 54000 - 84000 £ per year.
Sage AI is a nimble team within Sage, building innovative services and solutions using generative AI and machine learning to turbocharge our users’ productivity. The Sage AI team builds capabilities to help businesses make better decisions through data-powered automation and insights.
We are currently hiring a Principal Machine Learning Engineer to help us build machine learning solutions that will provide insights to empower businesses and help them succeed. As a part of our cross-functional team including data scientists and engineers you will help steer the direction of the entire company’s Artificial Intelligence and Machine Learning initiatives.
This is a hybrid role – three days per week in our London office.
If you share our excitement for applying artificial intelligence and machine learning, value a culture of continuous improvement and learning and are excited about working with cutting edge technologies, apply today!
You will:
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Design and implement product features and services that use AI and ML to augment and simplify our customers’ workflows
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Develop our internal ML platform to support our machine learning systems and our own efficiency
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Monitor and optimize the quality and performance of our models, services, and tools
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Collaborate with our AI Platform team to extend the capabilities of our machine learning platform
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Design and write robust production-quality code to support our machine learning systems
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Build and operate pipelines for accessing and enriching data for machine learning
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Train, tune, and ship models
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Mentor other ML engineers, software engineers, and data scientists in best practices
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Work with product managers and data scientists to translate product/business problems into tractable machine learning solutions
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Keen interest in artificial intelligence and machine learning and extensive practical experience with it
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Expert knowledge and experience with relevant programming languages (incl. Python), frameworks (incl. Pycharm, OpenAI, HuggingFace, Spark, Azure, AWS)
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Extensive experience with cloud environments (AWS, Azure, GCP)
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Ability to write highly performant code working with big data
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Bachelor’s degree, preferably in a field that strongly uses data science / machine learning techniques (e.g. computer science/engineering, statistics, applied math)
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Fluency in data fundamentals: SQL, data manipulation using a procedural language, statistics, experimentation, and predictive modelling
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Strong quantitative and analytical skills with significant experience with data science tools
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Ability to communicate complex ideas in machine learning to non-technical stakeholders
You may have:
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Experience with one or more ML Ops frameworks – MLFlow, Kubeflow, Azure ML, Sagemaker
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Strong theoretical foundations in linear algebra, probability theory, or optimization
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Experience and training in finance and operations domains
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Deep experience with ML approaches: deep learning, generative AI, large language models, logistic regression, gradient descent
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Experience wrangling complex and diverse data to solve real-world problems
Principal Machine Learning Engineer employer: The Sage Group plc
Contact Detail:
The Sage Group plc Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Principal Machine Learning Engineer
✨Tip Number 1
Make sure to showcase your experience with machine learning frameworks and programming languages like Python in your conversations. Highlight specific projects where you've successfully implemented AI solutions, as this will resonate well with the team.
✨Tip Number 2
Familiarize yourself with the latest trends in generative AI and machine learning. Being able to discuss recent advancements or case studies during your interactions can demonstrate your passion and knowledge in the field.
✨Tip Number 3
Prepare to discuss how you approach mentoring and collaboration. Since this role involves guiding other engineers and data scientists, sharing your experiences in fostering a learning environment will be beneficial.
✨Tip Number 4
Since this is a hybrid role, express your flexibility and enthusiasm for working in both remote and office settings. Highlight any previous experiences that demonstrate your ability to thrive in a hybrid work environment.
We think you need these skills to ace Principal Machine Learning Engineer
Some tips for your application 🫡
Understand the Role: Before applying, make sure you fully understand the responsibilities and requirements of the Principal Machine Learning Engineer position. Familiarize yourself with the technologies and methodologies mentioned in the job description.
Tailor Your CV: Customize your CV to highlight relevant experience in AI and machine learning. Emphasize your expertise in programming languages like Python and frameworks such as Pycharm and HuggingFace, as well as your experience with cloud environments.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for AI and machine learning. Discuss specific projects or experiences that demonstrate your ability to design and implement machine learning solutions, and how you can contribute to Sage AI's goals.
Showcase Your Communication Skills: Since the role involves communicating complex ideas to non-technical stakeholders, provide examples in your application of how you've successfully conveyed technical concepts in an understandable way.
How to prepare for a job interview at The Sage Group plc
✨Showcase Your Technical Expertise
Be prepared to discuss your experience with relevant programming languages and frameworks, especially Python, Pycharm, and cloud environments like AWS and Azure. Highlight specific projects where you've successfully implemented machine learning solutions.
✨Demonstrate Collaboration Skills
Since this role involves working closely with data scientists and product managers, be ready to share examples of how you've collaborated in cross-functional teams. Discuss how you translated complex business problems into actionable machine learning solutions.
✨Emphasize Continuous Learning
Express your passion for continuous improvement and learning in the field of AI and machine learning. Share any recent courses, certifications, or personal projects that showcase your commitment to staying updated with cutting-edge technologies.
✨Prepare for Problem-Solving Questions
Expect to face questions that assess your problem-solving abilities, particularly in optimizing model performance and handling big data. Practice articulating your thought process and methodologies for tackling real-world challenges in machine learning.
