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For Companies At a Glance
- Tasks: Design and evaluate machine learning models while working independently on exciting projects.
- Company: Join a dynamic freelance community focused on innovative data solutions.
- Benefits: Earn $100 to $120 per hour with flexible remote work options.
- Why this job: Make an impact in the AI field while honing your skills in a research-driven environment.
- Qualifications: Strong experience in machine learning engineering and excellent communication skills.
The predicted salary is between 85 - 130 £ per hour.
This role is for a Machine Learning Engineer on a short‑term, project‑based hourly contract, offering $100 to $120 per hour.
Position Details
- Type: Hourly contract
- Compensation: $100 to $120 per hour
- Location: Remote
- Commitment: Short‑term, project‑based
Role Responsibilities
- Design and write detailed evaluation suites for machine learning engineering tasks.
- Assess AI generated solutions across model training, debugging, optimization, and experimentation.
- Translate real world ML workflows into structured benchmarks for frontier models.
- Apply strong technical judgment to evaluate ML system design choices and tradeoffs.
- Work independently within a research driven, asynchronous project environment.
Requirements
- Strong experience in machine learning engineering or applied ML research.
- Hands‑on experience with model development, experimentation, and evaluation.
- Background in ML research in industry or academic settings preferred.
- Strong written communication skills and high attention to technical detail.
- Ability to work independently and deliver high quality outputs on short timelines.
Application Process (Takes 20 Min)
- Upload resume
- Short assessment
- Submit form
Machine Learning Engineer | Remote in London employer: Data Freelance Hub
Contact Detail:
Data Freelance Hub Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer | Remote in London
✨Tip Number 1
Get your portfolio ready! Showcase your machine learning projects and any relevant research. We want to see what you've done, so make it easy for potential employers to see your skills in action.
✨Tip Number 2
Network like a pro! Connect with other ML engineers and industry professionals on platforms like LinkedIn. We can help you find opportunities through our community, so don’t hesitate to reach out!
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills. We recommend practising common ML problems and being ready to discuss your past projects in detail. Confidence is key!
✨Tip Number 4
Apply directly through our website! It’s quick and easy, and we’re here to support you throughout the process. Don’t miss out on that perfect role just because you didn’t take the leap!
We think you need these skills to ace Machine Learning Engineer | Remote in London
Some tips for your application 🫡
Tailor Your Resume: Make sure your resume highlights your experience in machine learning engineering and applied ML research. We want to see how your background fits the role, so don’t be shy about showcasing relevant projects or achievements!
Show Off Your Skills: In your application, emphasise your hands-on experience with model development and evaluation. We love seeing specific examples of how you've tackled challenges in ML, so include those juicy details that set you apart!
Be Clear and Concise: Strong written communication is key for us. When filling out the application form, keep your answers clear and to the point. This helps us understand your thought process and technical judgement without getting lost in jargon.
Apply Through Our Website: We encourage you to apply directly through our website. It’s quick and easy, plus it ensures your application gets to the right place. Don’t miss out on this opportunity to join our community!
How to prepare for a job interview at Data Freelance Hub
✨Know Your ML Stuff
Make sure you brush up on your machine learning concepts and techniques. Be ready to discuss your hands-on experience with model development and evaluation, as well as any specific projects you've worked on. This will show that you’re not just familiar with the theory but can apply it in real-world scenarios.
✨Prepare for Technical Questions
Expect some technical questions that assess your understanding of ML system design choices and trade-offs. Practise explaining your thought process clearly and concisely. You might even want to prepare a few examples of how you've tackled challenges in previous projects.
✨Showcase Your Communication Skills
Since strong written communication skills are a must, be prepared to articulate your ideas effectively. Think about how you can explain complex concepts in simple terms, as this will demonstrate your ability to communicate with both technical and non-technical stakeholders.
✨Emphasise Independence and Time Management
This role requires working independently within a research-driven environment. Be ready to share examples of how you've successfully managed your time and delivered high-quality outputs under tight deadlines. Highlighting your ability to work autonomously will set you apart from other candidates.
