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- Tasks: Lead the end-to-end process of building and deploying ML models.
- 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 in a dynamic environment.
- Qualifications: MSc or PhD in STEM; strong ML model deployment experience required.
- Other info: Opportunity to collaborate closely with Data Scientists and drive best practices.
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 MLops Engineer employer: Harnham
Contact Detail:
Harnham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead MLops Engineer
✨Tip Number 1
Familiarize yourself with the specific technologies mentioned in the job description, such as Python, SQL, AWS, and Databricks. Having hands-on experience or projects that showcase your skills in these areas will make you stand out.
✨Tip Number 2
Highlight any experience you have with end-to-end ML pipelines and productionizing models. Be prepared to discuss specific projects where you've successfully implemented these processes during your interview.
✨Tip Number 3
Since this role involves mentoring juniors, think about examples from your past where you've guided or trained others. This will demonstrate your leadership potential and ability to work collaboratively within a team.
✨Tip Number 4
Stay updated on best practices in MLOps and be ready to share your insights during discussions. Showing that you're proactive about industry trends can set you apart as a candidate who is not only skilled but also passionate about the field.
We think you need these skills to ace Lead MLops 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 MLOps.
Craft a Strong Cover Letter: In your cover letter, express your enthusiasm for the role and the company. Mention specific projects or experiences that align with the responsibilities listed in the job description, such as working with deep learning or mentoring juniors.
Showcase Relevant Skills: Clearly outline your technical skills related to the job, such as experience with Databricks, PySpark, and MLFlow. Provide examples of how you've used these tools in past projects to demonstrate your hands-on experience.
Highlight Team Collaboration: Since the role involves working closely with Data Scientists and mentoring juniors, include examples of your teamwork and leadership experiences. This will show that you can thrive in a collaborative environment.
How to prepare for a job interview at Harnham
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python, SQL, AWS, and other relevant technologies. Highlight specific projects where you built and deployed ML models, especially those involving segmentation, churn, or recommender systems.
✨Demonstrate Leadership and Mentorship
Since this role involves mentoring juniors, share examples of how you've guided team members in the past. Discuss your approach to fostering a collaborative environment and driving best practices in MLOps.
✨Discuss End-to-End Data Pipelines
Prepare to explain your experience with end-to-end data pipelines. Be ready to talk about how you've trained, evaluated, and deployed ML models, and any challenges you faced during these processes.
✨Emphasize Adaptability in Fast-Paced Environments
The company values a startup feel, so illustrate your ability to thrive in fast-paced settings. Share experiences where you adapted quickly to changes or took initiative in dynamic situations.
