About the job

• Mercor** connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include **Benchmark**, **General Catalyst**, **Peter Thiel**, **Adam D'Angelo**, **Larry Summers**, and **Jack Dorsey**.
• Position:** Machine Learning Engineer

**Type:** **Contract**

**Compensation:** **$35/hour**

**Location:** **India**

**Commitment:** **30–40 hours/week**

Role Responsibilities

• Frame unique **ML problems** to enhance the capabilities of **LLMs**.
• Design, build, and optimize **machine learning models** for classification, prediction, **NLP**, recommendation, or generative tasks.
• Run rapid experimentation cycles, evaluate model performance, and iterate continuously.
• Conduct advanced feature engineering and data preprocessing.
• Implement adversarial testing, model robustness checks, and bias evaluations.
• Fine-tune, evaluate, and deploy transformer-based models where necessary.
• Maintain clear documentation of datasets, experiments, and model decisions.
• Stay updated on the latest **ML research**, tools, and techniques to push modeling capabilities forward.

Qualifications

Must-Have

• At least **2 years** of full-time experience in **machine learning model development**.
• Technical degree in **Computer Science**, **Electrical Engineering**, **Statistics**, **Mathematics**, or a related field.
• Demonstrated competitive **machine learning experience** (Kaggle, DrivenData, or equivalent).
• Evidence of top-tier performance in **ML competitions** (Kaggle medals, finalist placements, leaderboard rankings).
• Strong proficiency in **Python**, **PyTorch/TensorFlow**, and modern **ML/NLP frameworks**.
• Solid understanding of **ML fundamentals**: statistics, optimization, model evaluation, architectures.
• Experience with distributed training, **ML pipelines**, and experiment tracking.
• Strong problem-solving skills and algorithmic thinking.
• Experience working with cloud environments (**AWS/GCP/Azure**).
• Exceptional analytical, communication, and interpersonal skills.
• Ability to clearly explain modeling decisions, tradeoffs, and evaluation results.
• Fluency in **English**.

Preferred

• Kaggle **Grandmaster**, **Master**, or multiple **Gold Medals**.
• Experience creating benchmarks, evaluations, or **ML challenge problems**.
• Background in generative models, **LLMs**, or multimodal learning.
• Experience with large-scale distributed training.
• Prior experience in **AI research**, **ML platforms**, or infrastructure teams.
• Contributions to technical blogs, open-source projects, or research publications.
• Prior mentorship or technical leadership experience.
• Published research papers (conference or journal).
• Experience with **LLM fine-tuning**, vector databases, or generative AI workflows.
• Familiarity with **MLOps tools**: **Weights & Biases**, **MLflow**, **Airflow**, **Docker**, etc.
• Experience optimizing inference performance and deploying models at scale.

Application Process (Takes 20–30 mins to complete)

• Upload resume
• AI interview based on your resume
• Submit form

Resources & Support

• For details about the interview process and platform information, please check: https://talent.docs.mercor.com/welcome/welcome
• For any help or support, reach out to: support@mercor.com
• PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.*,