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- Tasks: Lead AI and machine learning projects while managing a talented team.
- Company: Join a forward-thinking company focused on data-driven solutions.
- Benefits: Enjoy remote work flexibility, competitive salary, bonuses, and perks.
- Why this job: Be a key player in shaping a data culture and driving innovation.
- Qualifications: Experience in AI products, cloud services, and strong leadership skills required.
- Other info: Monthly office visits in London for team collaboration.
The predicted salary is between 43200 - 72000 £ per year.
My Client is looking for a lead machine learning engineer, someone who has experience leading a team working extensively with AI and machine learning. The job is very remote with once a month visit to the office in London, and it offers a great salary with a bonus and package on top. What’s the job Lead the implementation of data science projects and data science approaches to support commercial goals. Develop a highly proficient team of Machine Learning Engineers, establishing collaborative ways of working. Collaborate with tech, product, and data teams to develop the data platforms that allow us to apply data science and embed the use of data science directly in our products and processes. Support diverse teams in translating between business and data in the design of project work, and in the synthesis and communication of recommendations and results. Be a champion and role model for the application of data science across the group. Support the data leadership team in developing a “data culture” and demonstrating the value of data in our decision making. Lead our efforts to develop the data science (and broader customer analytics) “brand” for both internal and external audiences. What you’ll bring Proven experience delivering high-quality AI-based products and productionisation of Machine Learning based products. Proven experience developing cloud-based machine learning services using one or more cloud providers (preferably GCP). Excellent understanding of classical Machine Learning algorithms (e.g., Logistic Regression, Random Forest, XGBoost, etc.) and modern Deep Learning algorithms (e.g., BERT, LSTM, etc.). Strong knowledge of SQL and Python’s ecosystem for data analysis (Jupyter, Pandas, Scikit Learn, Matplotlib). Strong software development skills (Python is the primary language). Proven experience in deploying ML/AI services using Kubernetes & KubeFlow. Strong management and leadership skills – previous experience managing a team. Strong influencing, communication, and stakeholder management skills. #J-18808-Ljbffr
Lead Machine Learning Engineer employer: CV-Library
Contact Detail:
CV-Library 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 leadership experience in machine learning projects. Highlight specific instances where you led a team or collaborated with cross-functional groups, as this is crucial for the role.
✨Tip Number 2
Familiarize yourself with the latest trends and technologies in AI and machine learning, especially those related to cloud-based services like GCP. Being able to discuss these topics confidently can set you apart during interviews.
✨Tip Number 3
Prepare to discuss how you've contributed to building a 'data culture' in previous roles. Think of examples where you demonstrated the value of data in decision-making processes.
✨Tip Number 4
Network with professionals in the field of machine learning and data science. Engaging with communities on platforms like LinkedIn can help you gain insights and potentially get referrals for the position.
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 leading machine learning projects and teams. Emphasize your skills in AI, cloud-based services, and relevant programming languages like Python.
Craft a Compelling Cover Letter: In your cover letter, express your passion for data science and your vision for developing a 'data culture'. Mention specific examples of how you've successfully led teams and delivered AI-based products.
Showcase Relevant Projects: Include details about specific projects where you implemented machine learning solutions. Highlight your role, the technologies used, and the impact these projects had on business goals.
Prepare for Technical Questions: Be ready to discuss your technical expertise in machine learning algorithms and cloud services during interviews. Prepare to explain your approach to deploying ML services and managing teams effectively.
How to prepare for a job interview at CV-Library
✨Showcase Your Leadership Experience
Since the role requires leading a team, be prepared to discuss your previous leadership experiences. Share specific examples of how you've successfully managed teams and projects, highlighting your ability to foster collaboration and drive results.
✨Demonstrate Technical Proficiency
Make sure to highlight your experience with AI and machine learning technologies. Be ready to discuss specific projects where you implemented classical and modern algorithms, and how you utilized cloud services like GCP in your work.
✨Communicate Effectively
Strong communication skills are essential for this role. Practice explaining complex technical concepts in simple terms, as you'll need to translate between business and data teams. Prepare to discuss how you've effectively communicated recommendations and results in past projects.
✨Emphasize Your Data Culture Advocacy
The company values a strong data culture, so be prepared to discuss how you've contributed to fostering a data-driven environment in previous roles. Share your thoughts on the importance of data in decision-making and how you've championed data science initiatives.
