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- Tasks: Lead the design and development of large-scale ML systems for top brands.
- Company: Global Specialist Cloud Consultancy with a focus on innovation.
- Benefits: Competitive salary, flexible working, and opportunities for professional growth.
- Why this job: Join a dynamic team and shape the future of machine learning.
- Qualifications: Extensive experience in ML systems, backend development, and data processing.
- Other info: Collaborative environment with a strong emphasis on staying ahead in tech trends.
The predicted salary is between 54000 - 84000 £ per year.
Partnered with a Global Specialist Cloud Consultancy working with various household brands who are on the ramp up to upscale their Machine Learning & Data Science capabilities and looking to build out top tier resources in this area of speciality in a Senior and Principal capacity.
Role Requirements:
- Extensive experience designing and leading the development of large-scale distributed data and/or ML backend systems.
- Hands-on experience with ETL pipeline design and optimization for complex data sets is a strong advantage.
- Deep familiarity with technologies such as Apache Beam, Pub/Sub, Redis, and other large-scale data processing frameworks.
- Expertise in backend development with Python and Scala; knowledge of Node.js or Golang is a plus.
- Proficient with both SQL and NoSQL databases, and experience with data warehousing solutions.
- Demonstrated experience building robust APIs (REST, GraphQL) and operating in modern cloud environments (GCP preferred), using Kubernetes, Docker, CI/CD, and observability tools.
Skills/Experience:
- Excellent communication and strong level of consulting/client facing experience.
- Comprehensive understanding of Data landscape and proactive nature in staying up to date with latest market trends.
- Business focus and outcome oriented.
- Capable of working independently and as part of a team setting.
If this role aligns with your career aspirations and you’d like to know more please share your CV and availability for a call to ankush.agarwal@harveynash.com
Principal Machine Learning Consultant employer: Harvey Nash
Contact Detail:
Harvey Nash Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Principal Machine Learning Consultant
✨Tip Number 1
Network like a pro! Reach out to your connections in the industry, attend meetups, and engage in online forums. The more people you know, the better your chances of landing that Principal Machine Learning Consultant role.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving large-scale data systems or ML backend development. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and consulting skills. Be ready to discuss your experience with tools like Apache Beam and your approach to building robust APIs. Confidence is key!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we’re always looking for top-tier talent like you to join our team.
We think you need these skills to ace Principal Machine Learning Consultant
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Principal Machine Learning Consultant role. Highlight your experience with large-scale distributed data systems and any hands-on work with ETL pipelines. We want to see how your skills align with what we're looking for!
Showcase Your Tech Skills: Don’t forget to showcase your expertise in Python, Scala, and any other relevant technologies like Apache Beam or Redis. We love seeing candidates who are well-versed in both SQL and NoSQL databases, so make that clear in your application!
Communicate Clearly: Since excellent communication is key for this role, ensure your application reflects your ability to convey complex ideas simply. Use clear language and structure your CV and cover letter well – we appreciate a tidy presentation!
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of applications better and ensures you don’t miss out on any important updates from us. Good luck!
How to prepare for a job interview at Harvey Nash
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technologies mentioned in the job description, like Apache Beam and Redis. Brush up on your Python and Scala skills, and be ready to discuss how you've used these tools in past projects.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific challenges you've faced in designing large-scale ML systems. Use the STAR method (Situation, Task, Action, Result) to structure your answers and highlight your problem-solving abilities.
✨Communicate Clearly and Confidently
Since excellent communication is key for this role, practice explaining complex concepts in simple terms. This will not only demonstrate your expertise but also your ability to consult effectively with clients.
✨Stay Updated on Industry Trends
Research the latest trends in machine learning and data science. Being able to discuss current developments shows your proactive nature and genuine interest in the field, which can set you apart from other candidates.
