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- Tasks: Develop and implement propensity models and scalable data pipelines.
- Company: Join a boutique company focused on transforming data into actionable insights.
- Benefits: Enjoy a hybrid work model with 3 days in-office each week.
- Why this job: Be part of an innovative team creating bespoke AI solutions that drive growth.
- Qualifications: 3+ years in Data Engineering, strong Python, AWS, SQL skills required.
- Other info: No sponsorship available; apply directly for this exciting opportunity.
The predicted salary is between 48000 - 84000 £ per year.
Senior Consultant | Scaling AI, ML, and Robotics teams in the UK
Role: Machine Learning Engineer
Location: London (Hybrid, 3 days in-office p/w)
I’m working with a really cool, boutique company who love getting their teeth stuck into data to generate actionable insights which translates into growth and efficiency for their customers.
They are looking for a hands-on ML Engineer to do a lot of work around developing and implementing propensity models & scalable data pipelines, as well as contribute heavily to the development of a bespoke AI agent.
Experience required:
- 3+ years experience in a Data Engineering role
- Strong experience with Python, AWS, SQL
- Experience with a pipeline orchestration tool such as Dagster or Airflow etc
- Experience building propensity models
- Experience setting up scalable data pipelines
Unfortunately, my client is unable to offer sponsorship at this time.
Please apply directly to this ad or email
Seniority level
Mid-Senior level
Employment type
Full-time
Job function
Marketing, Engineering, and Information Technology
Industries
Staffing and Recruiting
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Machine Learning Engineer employer: Spinks
Contact Detail:
Spinks Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer
✨Tip Number 1
Make sure to showcase your hands-on experience with Python and AWS in your discussions. Highlight specific projects where you've implemented scalable data pipelines or built propensity models, as this will resonate well with the hiring team.
✨Tip Number 2
Familiarize yourself with pipeline orchestration tools like Dagster or Airflow. Being able to discuss how you've used these tools in past projects can set you apart from other candidates.
✨Tip Number 3
Research the company’s approach to AI and ML. Understanding their specific needs and challenges will allow you to tailor your conversation and demonstrate how you can contribute to their goals.
✨Tip Number 4
Prepare to discuss your experience in a collaborative environment. Since this role involves working closely with teams, sharing examples of successful teamwork in previous roles can highlight your fit for the company culture.
We think you need these skills to ace Machine Learning Engineer
Some tips for your application 🫡
Understand the Role: Take the time to thoroughly read the job description. Understand the key responsibilities and required skills for the Machine Learning Engineer position, especially focusing on experience with Python, AWS, and data pipelines.
Tailor Your CV: Customize your CV to highlight relevant experience in data engineering, particularly your work with propensity models and scalable data pipelines. Use specific examples that demonstrate your hands-on experience and technical skills.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for AI and ML. Mention why you are excited about this boutique company and how your background aligns with their goals of generating actionable insights.
Highlight Relevant Projects: In your application, include specific projects or achievements that relate to the role. Discuss any experience with pipeline orchestration tools like Dagster or Airflow, and how you've contributed to similar projects in the past.
How to prepare for a job interview at Spinks
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python, AWS, and SQL in detail. Bring examples of projects where you've built scalable data pipelines or developed propensity models to demonstrate your hands-on expertise.
✨Understand the Company’s Focus
Research the boutique company’s approach to AI and ML. Familiarize yourself with their past projects and how they generate actionable insights for clients. This will help you align your answers with their goals during the interview.
✨Prepare for Problem-Solving Questions
Expect technical questions that assess your problem-solving skills, especially related to pipeline orchestration tools like Dagster or Airflow. Practice explaining your thought process clearly and concisely.
✨Demonstrate Team Collaboration
Since the role involves working closely with teams, be ready to share examples of how you've collaborated with others in previous roles. Highlight your ability to communicate complex ideas effectively to non-technical stakeholders.
