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- Tasks: Build and maintain infrastructure for data science lifecycle in a collaborative team.
- Company: Join SPG Resourcing, a company committed to diversity and inclusion.
- Benefits: Enjoy fully remote work and a competitive salary of £70,000.
- Why this job: Be part of an innovative team transforming research into production with cutting-edge technology.
- Qualifications: Proficiency in Python, Databricks, Azure, and experience with ML frameworks required.
- Other info: We provide reasonable accommodation throughout the application 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.
- Own and develop deployment frameworks for data science services.
- Ownership of the deployment framework for all data science services.
- 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 we move to production.
- Automate the data science pipeline (data prep to deployment).
- Write clean, production-ready Python code.
- Apply software engineering best practices, CI/CD, TDD.
- Proficiency in Python, Databricks, and Azure.
- Experience with deployment tools.
- Strong software engineering background (CI/CD, VCS, TDD).
- Ability to integrate ML into business workflows.
- Familiarity with ML frameworks like TensorFlow, XGBoost, and SKLearn.
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 - Fully Remote employer: SPG Resourcing
Contact Detail:
SPG Resourcing Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer - Fully Remote
✨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 community, especially those who work with machine learning deployment. Engaging in relevant forums or attending meetups can provide insights and connections that may help you stand out.
✨Tip Number 4
Prepare to discuss how you've integrated machine learning into business workflows in past roles. Being able to articulate this will demonstrate your ability to bridge the gap between technical and business needs.
We think you need these skills to ace Machine Learning Engineer - Fully Remote
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 data science infrastructure, and emphasise your familiarity with ML frameworks like TensorFlow, XGBoost, and SKLearn.
Craft a Compelling Cover Letter: In your cover letter, explain why you're passionate about machine learning and how your skills align with the role. Mention your experience in automating data science pipelines and your understanding of CI/CD and TDD practices.
Showcase Relevant Projects: If you have a portfolio or GitHub repository, include links to projects that demonstrate your ability to write clean, production-ready code and integrate ML into business workflows. This will give the hiring team insight into your practical skills.
Highlight Collaboration Experience: Since the role involves working closely with data scientists, mention any previous collaborative projects. Describe how you contributed to transitioning models from research to production and how you communicated effectively within cross-functional teams.
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 machine learning models and how you managed the deployment process.
✨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.
✨Demonstrate Collaboration Skills
Since the role involves working closely with data scientists, highlight your experience in collaborative environments. Share examples of how you've effectively communicated and worked with cross-functional teams in the past.
✨Prepare for Problem-Solving Questions
Expect technical questions that assess your problem-solving abilities. Practice explaining your thought process when faced with challenges in deploying machine learning models or automating workflows.
