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- Tasks: Help fix and optimise AI workflows with quick, impactful tasks.
- Company: Join a forward-thinking team focused on AI innovation.
- Benefits: Earn $5 for a quick task with potential for more work.
- Why this job: Make a difference in AI projects while showcasing your skills.
- Qualifications: Strong Python skills and experience with AI/ML technologies.
- Other info: Opportunity for larger projects if you impress!
The predicted salary is between 13 - 16 £ per hour.
I'm looking for an AI/ML engineer to help with a small technical task related to LLMs, embeddings, vector search, or AI agent workflows. This is a quick $5 task to implement a fix, debug an issue, or adjust a part of the pipeline.
Task May Include (One or More):
- Fixing an issue in a RAG pipeline (wrong results, low relevance, chunk issues)
- Adjusting FAISS / Pinecone / Chroma index settings
- Debugging embedding generation or vector mismatches
- Improving similarity search or hybrid search
- Fixing an error in FastAPI or AI endpoints
- Small prompt engineering or structured-output improvement
- Minor optimizations to agent workflow or tool calling
- Reviewing and correcting LLM integration logic
Required Skills:
- Strong Python skills (FastAPI preferred)
- RAG architecture understanding
- Vector DB experience (Pinecone / FAISS / Chroma)
- Embeddings + hybrid retrieval
- LLM API integration (OpenAI, Anthropic, Llama)
- LangChain / LlamaIndex or custom pipelines
- Basic debugging + clean code practices
Deliverables:
- A working fix or adjustment
- Clean, readable code
- A short explanation of what was done
Notes:
- This is a small starter task — I plan to hire for larger work if this goes well.
- Prefer someone who understands real production systems, not just experimentation.
Contract duration of 1 to 3 months.
Need AI Engineer for Quick Fix employer: FreelanceJobs
Contact Detail:
FreelanceJobs Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Need AI Engineer for Quick Fix
✨Tip Number 1
Network like a pro! Reach out to your connections in the AI/ML field and let them know you're on the lookout for opportunities. You never know who might have a lead or can refer you to someone looking for an AI engineer.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects related to LLMs, embeddings, and vector search. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Don’t shy away from small tasks! Apply for quick gigs like the one we have on our website. Completing these can lead to bigger projects and help you build a solid reputation in the industry.
✨Tip Number 4
Prepare for interviews by brushing up on your Python skills and understanding RAG architecture. Be ready to discuss your experience with vector databases and LLM API integration, as these are hot topics right now!
We think you need these skills to ace Need AI Engineer for Quick Fix
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your application for the AI Engineer role. Highlight your experience with Python, RAG architecture, and any relevant vector DBs like Pinecone or FAISS. We want to see how your skills match our needs!
Show Off Your Problem-Solving Skills: Since this is a quick fix task, share examples of how you've tackled similar issues in the past. Whether it’s debugging an embedding generation or adjusting index settings, we love seeing your thought process and solutions!
Keep It Clear and Concise: When writing your application, be straightforward and to the point. We appreciate clean, readable code and clear explanations of what you’ve done in previous projects. This helps us understand your approach better!
Apply Through Our Website: Don’t forget to submit your application through our website! It’s the best way for us to keep track of your application and ensure it gets the attention it deserves. We can’t wait to hear from you!
How to prepare for a job interview at FreelanceJobs
✨Know Your Tech Inside Out
Make sure you brush up on your Python skills, especially with FastAPI, as it's preferred for this role. Familiarise yourself with RAG architecture and vector databases like Pinecone, FAISS, or Chroma. The more confident you are in these areas, the better you'll perform in the interview.
✨Prepare for Practical Scenarios
Since the job involves fixing issues and debugging, be ready to discuss specific examples from your past work. Think about times you've resolved similar problems, like adjusting index settings or improving similarity searches. This will show your practical experience and problem-solving skills.
✨Showcase Clean Code Practices
Be prepared to talk about your coding style and how you ensure your code is clean and readable. You might even want to bring a sample of your work that demonstrates your ability to write maintainable code, as this is crucial for the task at hand.
✨Communicate Clearly
During the interview, explain your thought process clearly when discussing potential fixes or adjustments. Being able to articulate what you've done and why is just as important as the technical skills themselves. A short explanation of your approach can make a big difference!
