At a Glance
- Tasks: Design and solve computational STEM problems using Python for AI projects.
- Company: Mindrift connects specialists with exciting AI opportunities in London.
- Benefits: Earn up to $55 per hour, flexible hours, and project-based work.
- Other info: Part-time, non-permanent projects with excellent earning potential.
- Why this job: Make a real impact in AI while working on innovative projects.
- Qualifications: 5+ years in machine learning, expert Python skills, and strong problem-solving abilities.
The predicted salary is between 44000 - 57000 £ per year.
Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation is project-based, not permanent employment.
What This Opportunity Involves
- Design original computational STEM problems that simulate real scientific workflows
- Create problems that require Python programming to solve
- Ensure problems are computationally intensive and cannot be solved manually within reasonable timeframes (days/weeks)
- Develop problems requiring non-trivial reasoning chains and creative problem-solving approaches
- Verify solutions using Python with standard libraries (Numpy, Pandas, Scipy, scikit-learn)
- Document problem statements clearly and provide verified correct answers
What We Look For
- This opportunity is a good fit for ML specialists with experience in Python open to part-time, non-permanent projects. Ideally, contributors will have:
- 5+ years of hands-on machine learning experience with proven business impact
- Portfolio of completed projects and publications showcasing real-world problem-solving
- Expert Python programming for data science (pandas, numpy, scipy, scikit-learn, statsmodels)
- Expert statistical analysis and machine learning – deep understanding of algorithms, methods, and their practical applications
- Expert with SQL and database operations for data manipulation and analysis
- Experience with GenAI technologies (LLMs, RAG, prompt engineering, vector databases)
- Understanding of MLOps practices and model deployment workflows
- Knowledge of modern frameworks (TensorFlow, PyTorch, LangChain)
- Strong written English (C1+)
How It Works
- Apply → Pass qualification(s) → Join a project → Complete tasks → Get paid
Project time expectations
For this project, tasks are estimated to require around 10-20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active.
Compensation
On this project, contributors can earn up to $55 per hour equivalent, depending on their level and pace of contribution. Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements.
Freelance Machine Learning Engineer in London employer: Fossepark
Mindrift is an exceptional employer for freelance Machine Learning Engineers, offering flexible project-based opportunities in the vibrant tech hub of London. With a focus on innovative AI solutions, Mindrift fosters a collaborative work culture that encourages creativity and problem-solving, while providing competitive compensation and the chance to work with leading tech companies. This role not only allows for professional growth through diverse projects but also offers the unique advantage of contributing to cutting-edge advancements in AI technology.
StudySmarter Expert Advice🤫
We think this is how you could land Freelance Machine Learning Engineer in London
✨Tip Number 1
Network like a pro! Reach out to fellow machine learning enthusiasts and professionals on platforms like LinkedIn. Join relevant groups and participate in discussions to get your name out there.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your best projects and problem-solving abilities. Make sure it’s easy to navigate and highlights your expertise in Python and machine learning.
✨Tip Number 3
Don’t just apply, engage! When you find a project that excites you, reach out directly to the company. Ask questions about the role and express your enthusiasm for contributing to their AI initiatives.
✨Tip Number 4
Keep your skills sharp! Stay updated with the latest trends in machine learning and AI. Consider taking online courses or attending workshops to enhance your knowledge and make yourself more appealing to potential clients.
We think you need these skills to ace Freelance Machine Learning Engineer in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to highlight your machine learning experience and Python skills. We want to see how your past projects align with what we’re looking for, so don’t hold back on showcasing your best work!
Show Off Your Portfolio:Include a link to your portfolio or any publications that demonstrate your problem-solving abilities. We love seeing real-world applications of your skills, so make it easy for us to check out your achievements!
Be Clear and Concise:When writing your application, keep it clear and to the point. We appreciate straightforward communication, so avoid jargon and focus on what makes you a great fit for the role.
Apply Through Our Website:Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. We can’t wait to see what you bring to the table!
How to prepare for a job interview at Fossepark
✨Know Your Stuff
Make sure you brush up on your machine learning concepts and Python programming skills. Be ready to discuss your past projects in detail, especially those that showcase your problem-solving abilities and the impact you've made.
✨Showcase Your Portfolio
Bring along a portfolio of your completed projects and publications. This is your chance to demonstrate your expertise and real-world problem-solving skills, so make it easy for them to see what you can do!
✨Prepare for Technical Questions
Expect technical questions related to algorithms, statistical analysis, and MLOps practices. Practise explaining complex concepts in simple terms, as this will show your depth of understanding and communication skills.
✨Ask Insightful Questions
At the end of the interview, don’t forget to ask questions about the projects you'll be working on. This shows your interest and helps you gauge if the role aligns with your skills and career goals.
