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- Tasks: Join us to develop cutting-edge ML models for video content analysis and classification.
- Company: We're a forward-thinking tech company focused on innovative machine learning solutions.
- Benefits: Enjoy fully remote work with a competitive rate of £400 a day.
- Why this job: Be part of a dynamic team shaping the future of video processing technology.
- Qualifications: Mid-level candidates with 3-5 years in Python ML frameworks and NLP/LLM experience are preferred.
- Other info: Flexible start date; ideal for self-sufficient and reliable individuals.
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 space. Engaging with communities or attending relevant webinars can help you make valuable connections and learn about potential opportunities.
✨Tip Number 4
Be prepared to discuss your experience with cloud platforms like GCP, AWS, or Azure. Highlight any projects where you've utilised these services, 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 of projects you've worked on that relate to the job description.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the role and the company. Discuss your hands-on experience with LLM-based video processing and how it aligns with their goals. Be sure to mention your familiarity with cloud platforms like GCP, AWS, or Azure.
Showcase Relevant Projects: If you have any relevant projects or contributions to open-source work, include them in your application. This could be a portfolio link or a brief description of your work that demonstrates your skills in ML and video content classification.
Proofread Your Application: Before submitting, carefully proofread your CV and cover letter for any errors or typos. A polished application reflects your attention to detail and professionalism, which is crucial for a mid-level position.
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 focus on LLM-based video processing. Be ready to discuss how you can contribute to their goals and what innovative ideas you might bring to the table regarding video content classification.
✨Demonstrate Reliability and Self-Sufficiency
As the ideal candidate should be competent and self-sufficient, prepare to share examples from your past work that illustrate your ability to work independently and deliver results without constant supervision.
