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- Tasks: Lead the development and deployment of impactful ML models in a dynamic team.
- Company: Join a top Telecomms company and be part of their innovative Data Science team.
- Benefits: Enjoy a competitive salary, bonus, car allowance, and remote work flexibility.
- Why this job: Work with cutting-edge tech and mentor juniors while driving best practices in ML.
- Qualifications: MSc or PhD in STEM; strong ML model experience preferred.
- Other info: Opportunity to collaborate closely with Data Scientists and influence client projects.
The predicted salary is between 54000 - 126000 £ per year.
LEAD MLOPs ENGINEER Up to £90,000 + 10% bonus, car allowance and benefits REMOTE (London once a month) This is a chance to join a leading Telecomms company as a part of their Data Science team help build and deploy impactful models and work with cutting-edge technologies. They are looking for a Lead MLE to work end to end, building and deploying models. ROLE: Your day-to-day responsibilities will include: Building, deploying and productionising segmentation, churn, and recommender system-based projects, alongside deep learning and neural networks to support core internal projects Part of a team of 7 reporting to the Head of Data Science Chance to upskill and mentor juniors whilst remaining fully hands-on Focusing on end-to-end data pipelines, for training, evaluating and deploying ML models Working closely with Data Scientists on client partners, advising on best practice ML and MLOps infrastructure Driving best practices in a fast-paced environment, within a well-established company REQUIREMENTS: MSc or PhD level education in STEM subjects. Strong experience in building and deploying ML models Preference for experience in customer modelling but not required Candidates should be looking to work in a fast paced startup feel environment Tech across: Python, SQL, AWS, Databricks, PySpark, AB Testing, MLFlow, APIs If this role looks of interest, please reach out to Joseph Gregory.
Lead Machine learning Engineer employer: Harnham
Contact Detail:
Harnham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Machine learning Engineer
✨Tip Number 1
Make sure to showcase your experience with end-to-end machine learning pipelines. Highlight any specific projects where you've built and deployed models, especially in areas like segmentation or churn prediction.
✨Tip Number 2
Familiarize yourself with the technologies mentioned in the job description, such as Python, SQL, AWS, and Databricks. Being able to discuss your hands-on experience with these tools will set you apart from other candidates.
✨Tip Number 3
Emphasize your ability to mentor and upskill junior team members. This role involves leadership, so demonstrating your experience in guiding others will be a big plus.
✨Tip Number 4
Prepare to discuss best practices in MLOps and how you've implemented them in previous roles. The company is looking for someone who can drive these practices in a fast-paced environment.
We think you need these skills to ace Lead Machine learning Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in building and deploying ML models, especially with technologies like Python, SQL, and AWS. Emphasize any relevant projects that showcase your skills in segmentation, churn, and recommender systems.
Craft a Strong Cover Letter: In your cover letter, express your enthusiasm for the role and the company. Mention your educational background (MSc or PhD) and how it aligns with the requirements. Discuss your hands-on experience and your ability to mentor juniors, as this is a key aspect of the role.
Showcase Relevant Projects: Include specific examples of projects you've worked on that relate to the job description. Highlight your experience with end-to-end data pipelines and any work with deep learning or neural networks. This will demonstrate your capability to handle the responsibilities outlined in the job.
Prepare for Technical Questions: Be ready to discuss your technical expertise during the interview process. Brush up on your knowledge of MLOps infrastructure, best practices in machine learning, and the technologies mentioned in the job description, such as Databricks and MLFlow.
How to prepare for a job interview at Harnham
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python, SQL, and AWS in detail. Highlight specific projects where you've built and deployed ML models, especially those involving segmentation or recommender systems.
✨Demonstrate Leadership and Mentorship
Since the role involves mentoring juniors, share examples of how you've guided less experienced team members in previous positions. Discuss your approach to fostering a collaborative environment.
✨Discuss End-to-End ML Processes
Be ready to explain your understanding of end-to-end data pipelines. Talk about your experience in training, evaluating, and deploying ML models, and how you ensure best practices are followed.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving skills in a fast-paced environment. Think of scenarios where you've had to adapt quickly or drive best practices in a challenging situation.
