Work Type
Remote
Location
Global
Compensation
Not specified
About this opportunity
Job Description
Turing is hiring experienced Machine Learning Developers to design, build, and deliver advanced machine learning solutions.
This role involves working across the full ML lifecycle—from data preparation and model development to deployment, optimization, and monitoring. You’ll also collaborate with product, engineering, and business teams to translate real-world requirements into scalable machine learning systems.
What You’ll Do
- Own end-to-end data science and machine learning solution development.
- Build data pipelines and design, train, deploy, and monitor ML models.
- Translate business objectives into effective ML architectures and solutions.
- Collaborate with product, engineering, and business stakeholders.
- Define ML problem statements, performance metrics, and success criteria.
- Evaluate and optimize models for accuracy, performance, and scalability.
- Apply modern AI/ML research and techniques to real-world problems.
- Help ensure ML systems are scalable and production-ready.
Requirements
- Bachelor’s or Master’s degree in Computer Science, Machine Learning, Artificial Intelligence, Statistics, or a related quantitative discipline.
- 4+ years of hands-on data science or machine learning development experience.
- Strong proficiency in Python.
- Experience with libraries such as Pandas, NumPy, and Scikit-learn.
- Strong understanding of data preprocessing, feature engineering, model tuning, and evaluation.
- Ability to select and apply appropriate ML models to real-world use cases.
- Experience designing scalable, production-grade ML systems.
- Knowledge across areas such as supervised and unsupervised learning, time-series forecasting, NLP, computer vision, or statistical modeling.
Preferred Qualifications
- Experience with deep learning, including CNNs, RNNs, or Transformers.
- Experience with cloud and data platforms such as AWS or Databricks.
- Hands-on experience with PySpark.
- Experience keeping up with and applying recent machine learning research.
- Competitive ML experience through platforms such as Kaggle or ML benchmarks is a plus.
Evaluation Process
The evaluation takes approximately 75 minutes across two rounds:
- Technical Interview – 60 minutes
- Onboarding & Cultural Discussion – 15 minutes
