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- Tasks: Lead the design and development of cutting-edge ML systems and data pipelines.
- Company: Join a global cloud consultancy working with top household brands.
- Benefits: Competitive salary, mentorship opportunities, and a chance to shape AI technologies.
- Why this job: Make a real impact in the world of Machine Learning and AI.
- Qualifications: Experience in ML system design, ETL pipelines, and cloud environments.
- Other info: Dynamic role with opportunities for career growth and innovation.
The predicted salary is between 43200 - 72000 £ per year.
Principal ML Engineer partnered with a Global Specialist Cloud Consultancy working with various household brands who are on the ramp up to upscale their Machine Learning/MLOps capabilities and looking to build out top tier resources in this area of speciality in a Senior and Principal capacity.
Role Requirements
- Lead architecture and development of scalable, high performance data pipelines and ML systems focusing on ingestion, transformation, quality and enhancement.
- Provide tech leadership and mentorship to various cross-functioning teams of ML Engineers, Data Scientists and infrastructure teams ensuring project alignment, high standards and architectural alignment.
- Drive and integrate Machine Learning and AI technologies including NLP and LLMs enabling automation and creating intelligent data solutions.
- Champion best practices and mentor engineers across teams driving continuous improvement.
- Provide direction and shape technical direction across AI, ML, Data Engineering and distributed systems.
Skills
- Extensive design and leading development of large-scale distributed data and ML backend systems.
- Hands-on experience with ETL pipeline design and optimising for complex datasets.
- Experience building robust APIs and ability to work in modern cloud environments ideally GCP.
- Extensive understanding of NLPs and LLMs alongside a proven track record of end to end ML system design.
- Consulting experience ideally or a strong background delivering in a client facing environment.
If this role aligns with your career aspirations and you would like to know more please share your CV and availability for a call to daniel.neaves@harveynash.com.
ML Engineer Consultant employer: Harvey Nash Group
Contact Detail:
Harvey Nash Group Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land ML Engineer Consultant
✨Tip Number 1
Network like a pro! Reach out to your connections in the industry, especially those who work in ML or consulting. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving data pipelines and ML systems. This gives potential employers a taste of what you can do beyond just a CV.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Be ready to discuss your experience with NLPs and LLMs, and how you’ve led teams in past projects.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace ML Engineer Consultant
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the ML Engineer Consultant role. Highlight your experience with scalable data pipelines, ML systems, and any relevant projects that showcase your skills in NLP and LLMs.
Showcase Your Leadership Skills: Since this role involves tech leadership and mentorship, don’t forget to mention any experience you have in guiding teams or projects. We want to see how you've driven continuous improvement and championed best practices.
Be Clear and Concise: When writing your application, keep it clear and to the point. Use bullet points for key achievements and make sure your passion for AI and ML shines through. We love a good story, but keep it relevant!
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of applications and ensures you’re considered for the role. Plus, it’s super easy!
How to prepare for a job interview at Harvey Nash Group
✨Know Your Tech Inside Out
Make sure you’re well-versed in the latest ML technologies, especially NLP and LLMs. Brush up on your experience with ETL pipeline design and cloud environments like GCP. Being able to discuss specific projects where you've implemented these technologies will show your expertise.
✨Showcase Your Leadership Skills
Since this role involves mentoring and providing tech leadership, be prepared to share examples of how you've led teams or projects in the past. Highlight your ability to align cross-functional teams and maintain high standards in project delivery.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving skills in real-world scenarios. Think about challenges you've faced in ML system design or data pipeline optimisation and how you overcame them. This will demonstrate your practical knowledge and critical thinking.
✨Ask Insightful Questions
At the end of the interview, have a few thoughtful questions ready about the company’s approach to ML and AI. This shows your genuine interest in the role and helps you gauge if the company culture aligns with your values and career goals.
