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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: 3-5 years in ML, Python frameworks, and experience with cloud platforms required.
- Other info: Flexible start date; ideal for self-sufficient and reliable candidates.
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. Be prepared to discuss specific projects where you've applied these skills, as this will demonstrate your practical knowledge.
✨Tip Number 2
Familiarise yourself with the latest trends in ML and LLMs, especially in the context of video processing. Being able to discuss recent advancements or case studies can set you apart and show your passion for the field.
✨Tip Number 3
Network with professionals in the ML and computer vision space. Engaging in relevant online communities 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. Highlight any projects where you've deployed ML models on these platforms, 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 hands-on experience in these areas.
Craft a Compelling Cover Letter: In your cover letter, explain why you are interested in the role and how your skills align with the company's focus on LLM-based video processing. Mention any relevant projects or achievements that showcase your expertise.
Showcase Relevant Projects: If you have worked on projects involving video content classification or NLP, include them in your application. Briefly describe the challenges you faced and how you overcame them using your technical skills.
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 used 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 should 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 that required minimal supervision.
