- Title: Senior Machine Learning Engineer (Remote)
- Engagement: Hourly contract (independent contractor)
- Rate: USD 30-40/hour
- Location: Remote candidates based in the United States, United Kingdom, Canada, Europe, Singapore, Dubai, or Australia who are legally able to work as independent contractors in their jurisdiction.
About the Role
We are hiring for one of our clients collaborating with a leading AI research lab to advance machine learning evaluation and task creation for large language models (LLMs). This role involves designing, implementing, and curating high-quality ML datasets, tasks, and evaluation workflows to support the training and benchmarking of advanced AI systems.
Responsibilities
- Frame and design ML problems to evaluate and improve LLM capabilities.
- Build and optimize ML models for classification, prediction, NLP, recommendation, or generative tasks.
- Conduct data preprocessing, feature engineering, and robust model evaluation.
- Implement adversarial testing, bias evaluations, and model robustness checks.
- Fine-tune and deploy transformer-based models where applicable.
- Maintain clear documentation of datasets, experiments, and model decisions.
- Collaborate with researchers and engineers to ensure high-quality, reproducible ML workflows.
- Stay updated on current ML research, tools, and techniques.
Required Skills & Experience
- Minimum 2 years of professional experience in machine learning model development.
- Technical degree in Computer Science, Electrical Engineering, Statistics, Mathematics, or related field.
- Experience in competitive ML or data science projects (e.g., Kaggle, DrivenData) is a plus.
- Proficiency in Python, PyTorch/TensorFlow, and modern ML/NLP frameworks.
- Solid understanding of ML fundamentals: statistics, optimization, evaluation metrics, and architectures.
- Experience with distributed training, ML pipelines, and experiment tracking.
- Strong analytical, problem-solving, and communication skills.
- Ability to clearly explain modeling decisions, tradeoffs, and evaluation results.
- Legally authorized to work in India.
Preferred Experience
- Advanced achievements in ML competitions (Kaggle Grandmaster/Master, top leaderboard rankings).
- Experience creating ML benchmarks, evaluation tasks, or challenge problems.
- Background in generative AI, LLMs, or multimodal learning.
- Experience with large-scale distributed training, cloud environments (AWS/GCP/Azure), and MLOps tools (MLflow, Weights & Biases, Airflow, Docker).
- Prior research publications, open-source contributions, or technical leadership experience.
Application Process
- Submit a resume highlighting relevant ML experience.
- Participate in a brief interview (2030 minutes).
- Reasonable accommodations provided upon request.
Contract & Payment
- Independent contractor, fully remote, flexible schedule.
- Paid weekly via Stripe or Wise.
- Work does not require access to confidential information from prior employers or clients.
- Applicants must be legally authorized to work in India.
