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- Tasks: Build and maintain data science infrastructure, automating the entire lifecycle from data ingestion to model deployment.
- Company: Join a dynamic data science team in a forward-thinking tech environment.
- Benefits: Competitive salary, inclusive workplace, and opportunities for professional growth.
- Why this job: Make a real impact by transitioning innovative models into production with cutting-edge technology.
- Qualifications: Proficient in Python, Azure, and Databricks; strong software engineering skills required.
- Other info: Collaborative culture with a focus on diversity and inclusion.
The predicted salary is between 60000 - 70000 £ 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.
- You will have 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).
- 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: 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 in Aberford employer: SPG Resourcing
Contact Detail:
SPG Resourcing Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer in Aberford
✨Network Like a Pro
Get out there and connect with folks in the industry! Attend meetups, webinars, or even local tech events. We all know that sometimes it’s not just what you know, but who you know that can help land that dream job.
✨Show Off Your Skills
Create a portfolio showcasing your projects, especially those involving Python, Databricks, and Azure. We recommend sharing your work on platforms like GitHub to demonstrate your coding chops and problem-solving skills to potential employers.
✨Ace the Interview
Prepare for technical interviews by brushing up on your ML concepts and coding challenges. We suggest practicing common interview questions and even doing mock interviews with friends to build confidence and refine your answers.
✨Apply Through Our Website
Don’t forget to apply directly through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who take the initiative to reach out directly.
We think you need these skills to ace Machine Learning Engineer in Aberford
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Python, Databricks, and Azure. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects or achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about machine learning and how you can contribute to our data science team. Keep it engaging and personal – we love to see your personality!
Showcase Your Projects: If you've worked on any cool machine learning projects, make sure to mention them! Whether it's a personal project or something from a previous job, we want to see how you’ve applied your skills in real-world scenarios.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates from our team!
How to prepare for a job interview at SPG Resourcing
✨Know Your Tech Stack
Make sure you’re well-versed in Python, Databricks, and Azure. Brush up on deployment tools like AKS and managed endpoints. Being able to discuss your experience with these technologies confidently will show that you're ready to hit the ground running.
✨Showcase Your Collaboration Skills
Since this role involves working closely with data scientists and cross-functional teams, be prepared to share examples of how you've successfully collaborated in the past. Highlight any projects where teamwork was key to transitioning models from research to production.
✨Demonstrate Your Problem-Solving Abilities
Think of specific challenges you've faced in previous roles related to automating the data science lifecycle or deploying models. Be ready to explain how you approached these problems and what solutions you implemented, showcasing your analytical skills.
✨Prepare Questions About the Role
Interviews are a two-way street! Prepare thoughtful questions about the team dynamics, the data science lifecycle at the company, and how they measure success in this role. This shows your genuine interest and helps you assess if it’s the right fit for you.
