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- Tasks: Lead a team to innovate in GenAI and Computer Vision projects.
- Company: Join a forward-thinking company at the forefront of AI technology.
- Benefits: Enjoy competitive salary, flexible work options, and a collaborative culture.
- Why this job: Make an impact with cutting-edge technology while mentoring a talented team.
- Qualifications: MSc or PhD in STEM/AI, 7+ years in ML Engineering, and Python proficiency required.
- Other info: Hands-on experience in GenAI and Computer Vision is essential.
The predicted salary is between 43200 - 72000 £ per year.
Staff Machine Learning Engineer Lead a global team of ML engineers to drive innovative GenAI and Computer Vision projects alongside classical ML. Role Lead a small team of 3-4, to design and build models across LLMs, GenAI and NLP with some in Computer Vision and more classical ML Perform code reviews and drive best practice Work alongside technical and non-technical stakeholders, creating insights and reports on key findings Required MSc or PhD in STEM/AI related subject 7+ years of ML Engineering/Software Engineering experience Proficiency in Python Hands-on experience in GenAI and Computer Vision is required Experience working with large data sets and a large user base is essential Excellent communication skills with proven experience working with stakeholders Desired Skills and Experience Computer Vision, Deep Learning, GenAI, LLM
Principal Data Scientist employer: Harnham
Contact Detail:
Harnham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Principal Data Scientist
✨Tip Number 1
Make sure to showcase your leadership experience in machine learning projects. Highlight any instances where you've led a team or mentored others, as this role requires you to lead a small team of ML engineers.
✨Tip Number 2
Demonstrate your hands-on experience with GenAI and Computer Vision. Be prepared to discuss specific projects you've worked on, the challenges you faced, and how you overcame them.
✨Tip Number 3
Since this role involves working with both technical and non-technical stakeholders, practice explaining complex concepts in simple terms. This will help you communicate effectively during interviews.
✨Tip Number 4
Familiarize yourself with the latest trends and advancements in LLMs, GenAI, and NLP. Being knowledgeable about current technologies will show your passion for the field and your commitment to staying updated.
We think you need these skills to ace Principal Data Scientist
Some tips for your application 🫡
Highlight Relevant Experience: Make sure to emphasize your 7+ years of experience in ML Engineering or Software Engineering. Detail specific projects where you've worked with GenAI, Computer Vision, and large datasets.
Showcase Technical Skills: Clearly outline your proficiency in Python and any hands-on experience you have with LLMs, GenAI, and Deep Learning. Mention any relevant tools or frameworks you are familiar with.
Demonstrate Leadership Abilities: Since the role involves leading a small team, include examples of your leadership experience. Discuss how you've successfully managed teams or projects in the past.
Communicate Effectively: Given the importance of communication skills in this role, provide examples of how you've effectively collaborated with both technical and non-technical stakeholders. Highlight any reports or insights you've created that influenced decision-making.
How to prepare for a job interview at Harnham
✨Showcase Your Technical Expertise
Be prepared to discuss your experience with GenAI, Computer Vision, and classical ML. Highlight specific projects where you've successfully implemented these technologies, and be ready to dive into the technical details during the interview.
✨Demonstrate Leadership Skills
Since this role involves leading a small team, share examples of how you've effectively managed teams in the past. Discuss your approach to mentoring junior engineers and driving best practices within your team.
✨Communicate Clearly with Stakeholders
Excellent communication skills are crucial for this position. Prepare to explain complex technical concepts in a way that non-technical stakeholders can understand. Practice articulating your insights and findings from previous projects.
✨Prepare for Code Reviews
As part of the role, you'll be performing code reviews. Be ready to discuss your approach to reviewing code, what best practices you follow, and how you provide constructive feedback to your peers.
