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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in training and optimizing machine learning models, particularly in adversarial robustness and generative image modeling. Proficient in deploying models under constraints while collaborating with leading AI researchers on impactful projects.
Highest-signal resume keywords
Machine Learning Research ExperienceStrong Experience With PyTorchAdversarial Robustness ExpertiseExperience Training Image ClassifiersGenerative Image Modeling Experience
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Machine LearningModel CompressionAdversarial TrainingSupervised Fine-TuningGenerative Adversarial NetworksVariational AutoencodersDiffusion ModelsRobust-Accuracy EvaluationMultilingual Model TrainingData Augmentation
Tools & Technologies
PyTorchJAXTensorFlow
Industry Keywords
AI SystemsOpen-Weight Language ModelsBehavioral RobustnessCurriculum LearningScaling Laws
Tech Stack
Tools & technologiesPyTorchTensorflow
About the role
Key responsibilities & impact- Train image classifiers and generative image models from scratch
- Fine-tune open-weight language models
- Optimize models within limited data, compute, and model-size budgets
- Improve model robustness against adversarial inputs and adversarial conversations
- Compress models to meet hard size and latency constraints without sacrificing accuracy
- Diagnose and resolve training issues
- Conduct empirical, open-ended machine learning research
- Collaborate with leading AI researchers on high-impact projects
- Work on projects focused on training and enhancing AI systems
Requirements
What you’ll need- 3+ years of machine learning research experience; PhD research counts toward this requirement
- Strong experience with PyTorch, JAX, TensorFlow, or similar ML frameworks
- Degree from a top-100 university, experience at a FAANG or comparable AI company, or an equivalent research track record through publications or impactful open-source contributions
- Strong expertise in one or more of adversarial robustness, efficient computer vision, generative image modeling, LLM post-training and behavioral robustness, or multilingual pre-training
- Experience with adversarial training of image classifiers, robust-accuracy evaluation, and robustness–accuracy trade-offs
- Experience training image classifiers end-to-end, model compression, and deployment under hard size or latency budgets
- Experience training diffusion models, GANs, VAEs, or flow-based generative models from scratch
- Experience with supervised fine-tuning and preference optimisation of open-weight language models
- Experience shaping conversational behavior across multiple turns
- Experience training multilingual or low-resource-language models and tokenizer design across scripts
- Experience balancing unequal per-language data in data-constrained regimes
- Experience in scaling laws, curriculum learning, model evaluation, uncertainty estimation, calibration, data augmentation, or synthetic data is a plus
- Must be able to work as an independent contractor
- Mercor is unable to support H1-B or STEM OPT candidates
Benefits
Comp & perks- Flexible, project-based work
- Competitive compensation
- Fully remote work
- Work on your own schedule
- Weekly payments via Stripe or Wise
- Projects may be extended, shortened, or concluded early depending on needs and performance
- Reasonable accommodations upon request
- Collaboration with leading AI researchers
- Referral payments of up to $480 for each successful referral, subject to limits