Machine Learning Engineer
Mercor
Part time
Software Development
Canada
Hiring from: Canada
## About the job
**Compensation:** **$35/hour**
**Location:** **India**
**Commitment:** **30–40 hours/week**
## Role Responsibilities
### Must-Have
- 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
**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.
### 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**.
- 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.
- Upload resume
- AI interview based on your resume
- Submit form
- 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: [email protected]
- PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.*,
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