**ONLY FOR CANDIDATES WHO HAVE WORKED AT TURING.COM**
**Other candidates should apply to different job listing by me**
**RLHF for LLMs**
Type: Part-Time, Remote
Perks: US organisation, can offer competitive compensation to Turing
Compensation: Starting at $15/hour (~Rs. 1200+ per hour)
- if you work an average of 3 hours a day - that could be upwards of Rs 80K per month
- if you choose to work average 8 hours a day - that could be upwards of Rs 2L per month
Minimum Commitment: 10 hours/week
Signing Bonus: $300 for qualified candidates who onboard within the next week and stay for a month
About Us:
We are at forefront of AI and machine learning, and weβre looking for motivated individuals to contribute to the next generation of intelligent models. The ideal candidate will have experience working with Turing.com and a strong background in data annotation, prompt engineering, and model fine-tuning. You will play a critical role in refining AI systems, providing essential human feedback, and enhancing overall model performance.
ππ‘Key Qualifications:
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Experience in RLHF:
- Deep understanding of Reinforcement Learning (especially RLHF) for LLMs and how it applies to improving AI models.
- Hands-on experience in fine-tuning LLMs through iterative human feedback.
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Data Expertise:
- Prior experience in annotating datasets for AI/ML models with a focus on quality control.
- Experience with annotation tools and platforms like Labelbox, Prodigy, or Turingβs proprietary tools.
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Technical Proficiency:
- Familiarity with LLM frameworks like GPT-3/4, BERT, and advanced NLP models.
- Strong command of Python, SQL, or related programming languages for handling data processing tasks.
- Understanding of prompt engineering, and experience with platforms like Hugging Face or LangChain is a plus.
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Turing.com Experience:
- Prior work experience at Turing.com (or similar remote work platforms), with a focus on AI, data annotation, or similar roles.
- Understanding of the remote work dynamic and experience collaborating with distributed teams.
β
Preferred Qualifications:
- Experience in model fine-tuning, prompt engineering, and human-in-the-loop systems.
- Familiarity with cloud platforms (AWS, Azure) and MLOps best practices.
- Previous work on reinforcement learning pipelines in large-scale AI projects.
ππ‘What Youβll Do:
You will play a key role in annotating and curating data for the training and fine-tuning of large language models (LLMs), ensuring annotations are accurate, consistent, and project-aligned. Youβll implement Reinforcement Learning with Human Feedback (RLHF) techniques, providing structured human feedback to guide model outputs and continuously fine-tune models to improve performance.
ππ‘Why You Should Apply:
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Flexible without any restrictions, opportunity β work whenever it fits your schedule!
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Remote β work from anywhere in India!
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Competitive pay β starting from $15/hour based on experience and performance
How to Apply:
β
Fill the GoogleForm
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Wait for shortlisting email
β
Receive offer letter
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Take onboarding seriously
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Ayyush Sharma (Chhotapreneur)
Growth, Strategy & Revenue Operations | A+ track record in scaling startups.
Growth @ Outlier AI