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- Tasks: Join us to develop cutting-edge ML models for video content analysis.
- Company: We're a forward-thinking tech company revolutionising video processing with AI.
- Benefits: Enjoy fully remote work and a competitive rate of £400 a day.
- Why this job: Be part of an innovative team making a real impact in AI and video technology.
- Qualifications: Looking for mid-level engineers with 3-5 years experience in Python ML frameworks and NLP.
- Other info: Flexible start date and opportunities to work with major cloud platforms.
The predicted salary is between 60000 - 84000 £ per year.
Our Client is building capability in cutting-edge ML, with a focus on LLM-based video processing – aiming to understand and classify video content using advanced models.Looking for talent with hands-on experience in video analysis and natural language understanding.
- Rate: £400 a day/ Including Agency Fee
- Location: Fully Remote
- Start Date: Flexible
Ideal Profile:
- Python
- ML frameworks (e.g. TensorFlow)
- NLP/LLM experience
- Cloud platforms (any major provider: GCP, AWS, Azure)
- Seniority: Mid-level (ideally 3-5 years of experience; up to 8 years acceptable)
- Must be competent, reliable, and self-sufficient
ML/ Computer Vision Engineer employer: Harnham
Contact Detail:
Harnham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land ML/ Computer Vision Engineer
✨Tip Number 1
Make sure to showcase your hands-on experience with video analysis and natural language understanding during any discussions. Prepare specific examples of projects you've worked on that highlight your skills in these areas.
✨Tip Number 2
Familiarise yourself with the latest trends and advancements in ML, particularly in LLM-based video processing. Being able to discuss recent developments will demonstrate your passion and knowledge in the field.
✨Tip Number 3
Network with professionals in the ML and computer vision community. Engaging in relevant forums or attending virtual meetups can help you make connections that might lead to referrals or insider information about the role.
✨Tip Number 4
Prepare to discuss your experience with cloud platforms like GCP, AWS, or Azure. Be ready to explain how you've utilised these services in your previous projects, as this is a key requirement for the role.
We think you need these skills to ace ML/ Computer Vision Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Python ML frameworks, video analysis, and natural language processing. Use specific examples to demonstrate your skills and achievements in these areas.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the role and the company. Mention your hands-on experience with LLM-based video processing and how it aligns with their goals. Be sure to include any relevant projects or accomplishments.
Showcase Relevant Projects: If you have worked on projects involving video content classification or NLP, summarise these in your application. Highlight the technologies used, your role, and the outcomes achieved to demonstrate your expertise.
Highlight Cloud Experience: Since the role requires familiarity with cloud platforms, make sure to mention any experience you have with GCP, AWS, or Azure. Detail how you've utilised these platforms in your previous work, especially in relation to ML and video processing.
How to prepare for a job interview at Harnham
✨Showcase Your Technical Skills
Be prepared to discuss your hands-on experience with Python ML frameworks like TensorFlow. Bring examples of projects where you've implemented video analysis or natural language understanding, as this will demonstrate your capability in the field.
✨Familiarise Yourself with Cloud Platforms
Since the role involves working with cloud platforms, make sure you can talk about your experience with any major provider such as GCP, AWS, or Azure. Highlight specific projects where you utilised these platforms to enhance your ML models.
✨Understand the Company’s Focus
Research the client’s work in LLM-based video processing. Understanding their goals and challenges will allow you to tailor your responses and show how your skills align with their needs.
✨Demonstrate Reliability and Self-Sufficiency
As the ideal candidate is expected to be competent and self-sufficient, prepare to share examples of how you've successfully managed projects independently. This could include overcoming challenges or leading initiatives without much oversight.