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- Tasks: Support advanced ML projects and improve performance across real-world workloads.
- Company: Join a forward-thinking team focused on impactful machine learning solutions.
- Benefits: Competitive pay, flexible remote work, and potential for long-term engagement.
- Why this job: Make a difference in the ML field while working on exciting, measurable tasks.
- Qualifications: 0-2 years of ML experience or relevant PhD coursework; strong Python skills required.
- Other info: Part-time role with opportunities for growth and collaboration.
We are hiring Machine Learning Engineers to support advanced benchmarking and performance-improvement projects across real-world ML workloads. This part-time, remote opportunity is ideal for early-career ML engineers or ML-focused PhD candidates who want to work on high-impact, structured tasks with measurable outcomes.
What You’ll Do
- Draft detailed natural-language plans and code implementations for ML tasks
- Convert novel ML problems into agent-executable tasks for RL environments
- Identify failure modes and apply golden patches to LLM-generated trajectories
What You’ll Bring
- 0–2 years of ML engineering experience or a PhD with ML coursework
- Strong skills in Python and ML libraries (TensorFlow, XGBoost, scikit-learn, etc.)
- Experience with data prep, training, and model evaluation
- Bonus: contributions to ML benchmarks
Opportunity Details
- ~20 hours/week
- Remote & asynchronous
- Duration through Dec 22, with potential extension into 2026
- Compensation $80–$120/hour
- Weekly payments via Stripe Connect
- Independent contractor role
How to Apply
Submit your resume, complete a short system design session, and finish the ML screening form.
Machine Learning Engineer in Leicester employer: Work Vista
Contact Detail:
Work Vista Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer in Leicester
✨Tip Number 1
Get your hands dirty with practical projects! Showcase your skills by working on real-world ML problems. This not only boosts your portfolio but also gives you something solid to discuss during interviews.
✨Tip Number 2
Network like a pro! Connect with other ML engineers and professionals in the field. Join online forums, attend webinars, or even local meetups. You never know who might have the inside scoop on job openings!
✨Tip Number 3
Prepare for technical interviews by practising coding challenges and ML concepts. Use platforms like LeetCode or Kaggle to sharpen your skills. The more prepared you are, the more confident you'll feel when it’s time to shine!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who take the initiative to reach out directly!
We think you need these skills to ace Machine Learning Engineer in Leicester
Some tips for your application 🫡
Tailor Your Resume: Make sure your resume highlights your relevant experience in machine learning and Python. We want to see how your skills align with the role, so don’t be shy about showcasing your projects and any contributions to ML benchmarks!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about machine learning and how you can contribute to our team. Keep it concise but engaging – we love a good story!
Showcase Your Technical Skills: When filling out the ML screening form, be specific about your experience with ML libraries like TensorFlow and scikit-learn. We’re looking for details on your data prep, training, and model evaluation processes, so don’t hold back!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the easiest way for us to keep track of your application and ensures you don’t miss any important steps in the process. Plus, we love seeing applications come in through our platform!
How to prepare for a job interview at Work Vista
✨Know Your ML Stuff
Make sure you brush up on your machine learning concepts and the libraries mentioned in the job description, like TensorFlow and scikit-learn. Be ready to discuss your experience with these tools and how you've applied them in real-world scenarios.
✨Prepare for Technical Questions
Expect technical questions that test your understanding of ML algorithms and data preparation techniques. Practise explaining your thought process clearly and concisely, as this will show your problem-solving skills and ability to communicate complex ideas.
✨Showcase Your Projects
Have a couple of projects or experiences ready to discuss that highlight your skills in ML engineering. Whether it's a personal project or coursework from your PhD, be prepared to explain the challenges you faced and how you overcame them.
✨Ask Insightful Questions
At the end of the interview, don’t forget to ask questions! Inquire about the team’s current ML projects or the company’s approach to benchmarking. This shows your genuine interest in the role and helps you gauge if it’s the right fit for you.