Machine Learning Specialist
2 weeks ago
We are seeking a skilled Machine Learning Specialist to join our dynamic team at Weekday. As a key member of our commerce platform, you will be responsible for developing and deploying machine learning models to enhance our customer experience. Your expertise in Python and popular machine learning libraries such as TensorFlow, PyTorch, and scikit-learn will be essential in driving innovation and growth.
Key Responsibilities:
- Design, test, and deploy machine learning models tailored for our commerce platform.
- Collaborate with cross-functional teams to integrate ML solutions into our products.
- Analyze data to uncover trends and patterns that inform business decisions.
- Continuously enhance model performance and optimize algorithms.
Requirements:
- 25 years of experience in machine learning and related technologies.
- Proficiency in Python and popular machine learning libraries.
- Experience with data preprocessing, feature engineering, and model evaluation.
- Familiarity with deploying machine learning models in production environments.
- Knowledge of algorithms and statistical methods for data analysis.
- Comfortable working with SQL and databases.
- Experience with cloud platforms like AWS, GCP, or Azure is a plus.
- Competitive programming: demonstrated experience in competitive programming is required.
Interview Process:
- Technical Screening: 15 to 30 minutes to evaluate your basic technical skills.
- DSA Round: 1 hour focused on data structures and algorithms.
- DSA and Technical Round: 1 hour combining data structures, algorithms, and technical expertise.
- Culture Round: assessing fit within our team and company culture.
What We Offer:
- Flexible working hours.
- The chance to make a significant impact on innovative projects.
- A competitive salary and benefits package.
Why Weekday:
- We are a dynamic and innovative company.
- We offer a collaborative and supportive work environment.
- We are committed to driving growth and innovation in the commerce platform.
How to Apply:
Please submit your resume and a cover letter outlining your experience and qualifications. We look forward to hearing from you
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