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- Tasks: Join a dynamic team to build and maintain data science infrastructure.
- Company: SPG Resourcing is dedicated to diversity and inclusion in the workplace.
- Benefits: Enjoy a competitive salary and opportunities for remote work.
- Why this job: Be part of an innovative team transforming research into real-world applications.
- Qualifications: Proficiency in Python, Databricks, and Azure is essential.
- Other info: We value diverse backgrounds and offer accommodations throughout the hiring process.
The predicted salary is between 42000 - 84000 £ per year.
This position is for an experienced Machine Learning Engineer to join a newly established data science team. The primary focus is on building and maintaining the infrastructure to support the full data science lifecycle from data ingestion to model deployment, monitoring, and upgrades within Azure and Databricks environments. The engineer will work closely with data scientists in a collaborative, cross-functional setting, helping transition models from research into production.
Key Responsibilities:- Own and develop deployment frameworks for data science services.
- Ownership of the deployment framework for all data science services, with oversight of how data will flow into the data science life cycle from the wider business data warehouse.
- Oversight of the automation of the data science life cycle (dataset build, training, evaluation, deployment, monitoring) when moving to production.
- Automate the data science pipeline (data prep to deployment).
- Collaborate with cross-functional teams to ensure smooth productionisation of models.
- Write clean, production-ready Python code.
- Apply software engineering best practices, CI/CD, TDD.
- Proficiency in Python, Databricks, and Azure.
- Experience with deployment tools (e.g., AKS, managed endpoints).
- Strong software engineering background (CI/CD, VCS, TDD).
- Ability to integrate ML into business workflows.
- Background in quantitative disciplines (math, stats, physics).
- Experience in finance, insurance, or ecommerce.
- Familiarity with ML frameworks like TensorFlow, XGBoost, and SKLearn.
If this sounds like something you are interested in, please get in contact: thomas.deakin@spgresourcing.com
SPG Resourcing is an equal opportunities employer and is committed to fostering an inclusive workplace which values and benefits from the diversity of the workforce we hire. We offer reasonable accommodation at every stage of the application and interview process.
Machine Learning Engineer (Leeds) employer: SPG Resourcing
Contact Detail:
SPG Resourcing Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer (Leeds)
✨Tip Number 1
Familiarise yourself with Azure and Databricks, as these are key platforms for the role. Consider taking online courses or tutorials to deepen your understanding of how to deploy machine learning models in these environments.
✨Tip Number 2
Showcase your experience with CI/CD and TDD in your discussions. Be prepared to discuss specific projects where you've implemented these practices, as they are crucial for maintaining high-quality code in production.
✨Tip Number 3
Network with professionals in the data science field, especially those who work with machine learning in production. Attend meetups or webinars to connect with others and gain insights into best practices and industry trends.
✨Tip Number 4
Prepare to discuss how you can integrate machine learning into business workflows. Think of examples from your past experiences where your work has directly impacted business outcomes, as this will demonstrate your value to the team.
We think you need these skills to ace Machine Learning Engineer (Leeds)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Python, Databricks, and Azure. Include specific projects where you've built or maintained deployment frameworks, as this is crucial for the role.
Craft a Strong Cover Letter: In your cover letter, emphasise your collaborative experience with data scientists and your ability to transition models from research to production. Mention any relevant experience in automating data science pipelines.
Showcase Relevant Projects: If you have worked on projects involving CI/CD, TDD, or deployment tools like AKS, make sure to include these in your application. Provide links to your GitHub or portfolio if possible.
Highlight Soft Skills: Since the role involves collaboration with cross-functional teams, mention your communication skills and ability to work in a team. This can set you apart from other candidates.
How to prepare for a job interview at SPG Resourcing
✨Showcase Your Technical Skills
Be prepared to discuss your proficiency in Python, Databricks, and Azure. Bring examples of past projects where you successfully implemented these technologies, especially in deploying machine learning models.
✨Understand the Data Science Lifecycle
Familiarise yourself with the full data science lifecycle, from data ingestion to model deployment. Be ready to explain how you would automate this process and ensure smooth transitions from research to production.
✨Emphasise Collaboration
Highlight your experience working in cross-functional teams. Discuss how you’ve collaborated with data scientists and other stakeholders to ensure successful model productionisation.
✨Prepare for Problem-Solving Questions
Expect technical questions that assess your problem-solving skills. Be ready to demonstrate your understanding of CI/CD, TDD, and how you would apply software engineering best practices in a machine learning context.
