Machine Learning Engineer for MAGIC AI
Budget: $10 – $400 USD
Job Title: MAGIC AI – Official Model Trainer
Status: Contract (with opportunity for long-term collaboration)
Compensation:
$200 competition prize
$400 official trainer contract
Public credit on MAGIC GitHub & HuggingFace repositories (MAGIC + MageV1)
About MAGIC AI
MAGIC is a new AI architecture currently under active development. We're looking for a dedicated and highly skilled machine learning engineer to serve as the Official MAGIC Trainer, working directly on the training pipelines, performance tuning, and dataset refinement for the MAGIC and MageV1 foundation models.
This role is ideal for someone who enjoys experimental architectures, training large models from scratch, and pushing performance boundaries through iterative improvements to the training loops.
How Selection Works
To be considered for the role, applicants must participate in and win the current competition:
Competition: https://www.freelancer.com/contest/Training-MAGIC-AI-2663043/
Prize: $200
Goal: Train the best-performing MAGIC Base model
The winner of this contest will automatically be offered the official training position.
Position Summary
As MAGIC’s Official Trainer, you will:
Work directly with the developer of MAGIC on model training strategy
Improve and extend the core training script (training_magic.py)
Design, run, and optimize training loops for MAGIC Base and subsequent versions
Handle preprocessing, batching, scaling strategies, checkpoints, and evaluation
Experiment with hyperparameters, optimizers, scheduling, and architecture variants
Provide input on dataset sourcing, creation, and curation
Collaborate on training reproducibility and documentation
Help shape the official MAGIC training standards for future models
Responsibilities
Maintain and enhance MAGIC’s training pipeline
Run training experiments and document performance results
Implement improvements to stability, speed, and model quality
Optimize for GPU/multi-GPU setups
Collaborate on shaping the evolution of MageV1 and future MAGIC versions
Contribute to best practices and training documentation
Ensure reproducible training via versioning and clean code updates
Requirements
Technical Skills:
Strong experience with PyTorch (preferred) or similar deep learning frameworks
Hands-on experience training transformers or other large neural architectures
Strong understanding of training loops, optimization, scheduling, and GPU efficiency
Experience with large-scale data processing and dataset pipelines
Familiarity with multi-GPU, distributed, or accelerated training frameworks
Ability to debug training instabilities, loss issues, and performance bottlenecks
Bonus Skills:
Experience with custom architectures
Prior contributions to ML open-source projects
Ability to profile and optimize CUDA workloads
Research background in LLMs or generative models
Compensation & Recognition
$200 for winning competition
$400 upon completion of MageV1
Public credit as the Official Trainer of MAGIC and MageV1 on:
GitHub
HuggingFace
Documentation
Opportunity for expanded future paid roles as MAGIC evolves
Priority consideration for extended research collaborations
### **How to Apply**
1. Enter the competition:
[https://www.freelancer.com/contest/Training-MAGIC-AI-2663043/](https://www.freelancer.com/contest/Training-MAGIC-AI-2663043/)
2. Train and submit the strongest MAGIC Base model.
3. The winner receives the contract and begins work as MAGIC’s official trainer.
Status: Contract (with opportunity for long-term collaboration)
Compensation:
$200 competition prize
$400 official trainer contract
Public credit on MAGIC GitHub & HuggingFace repositories (MAGIC + MageV1)
About MAGIC AI
MAGIC is a new AI architecture currently under active development. We're looking for a dedicated and highly skilled machine learning engineer to serve as the Official MAGIC Trainer, working directly on the training pipelines, performance tuning, and dataset refinement for the MAGIC and MageV1 foundation models.
This role is ideal for someone who enjoys experimental architectures, training large models from scratch, and pushing performance boundaries through iterative improvements to the training loops.
How Selection Works
To be considered for the role, applicants must participate in and win the current competition:
Competition: https://www.freelancer.com/contest/Training-MAGIC-AI-2663043/
Prize: $200
Goal: Train the best-performing MAGIC Base model
The winner of this contest will automatically be offered the official training position.
Position Summary
As MAGIC’s Official Trainer, you will:
Work directly with the developer of MAGIC on model training strategy
Improve and extend the core training script (training_magic.py)
Design, run, and optimize training loops for MAGIC Base and subsequent versions
Handle preprocessing, batching, scaling strategies, checkpoints, and evaluation
Experiment with hyperparameters, optimizers, scheduling, and architecture variants
Provide input on dataset sourcing, creation, and curation
Collaborate on training reproducibility and documentation
Help shape the official MAGIC training standards for future models
Responsibilities
Maintain and enhance MAGIC’s training pipeline
Run training experiments and document performance results
Implement improvements to stability, speed, and model quality
Optimize for GPU/multi-GPU setups
Collaborate on shaping the evolution of MageV1 and future MAGIC versions
Contribute to best practices and training documentation
Ensure reproducible training via versioning and clean code updates
Requirements
Technical Skills:
Strong experience with PyTorch (preferred) or similar deep learning frameworks
Hands-on experience training transformers or other large neural architectures
Strong understanding of training loops, optimization, scheduling, and GPU efficiency
Experience with large-scale data processing and dataset pipelines
Familiarity with multi-GPU, distributed, or accelerated training frameworks
Ability to debug training instabilities, loss issues, and performance bottlenecks
Bonus Skills:
Experience with custom architectures
Prior contributions to ML open-source projects
Ability to profile and optimize CUDA workloads
Research background in LLMs or generative models
Compensation & Recognition
$200 for winning competition
$400 upon completion of MageV1
Public credit as the Official Trainer of MAGIC and MageV1 on:
GitHub
HuggingFace
Documentation
Opportunity for expanded future paid roles as MAGIC evolves
Priority consideration for extended research collaborations
### **How to Apply**
1. Enter the competition:
[https://www.freelancer.com/contest/Training-MAGIC-AI-2663043/](https://www.freelancer.com/contest/Training-MAGIC-AI-2663043/)
2. Train and submit the strongest MAGIC Base model.
3. The winner receives the contract and begins work as MAGIC’s official trainer.