Machine Learning Engineer

You will work on a product focused machine learning platform to improve ranking and recommendation systems. You will evaluate cutting edge ML technologies including transformer based models to identify solutions for business problems. You will develop scalable models for ranking and recommendations and apply learning to rank techniques. You will design and run A/B tests to measure performance, analyze experimental data to generate actionable insights, and collaborate with engineers and data scientists to integrate models into the product and maintain reusable libraries and thorough documentation.

Responsibilities

• Evaluate cutting edge ML technologies including transformer based models and large foundational models to identify solutions for business problems.
• Develop and implement scalable ML models focusing on ranking and recommendation systems with expertise in collaborative filtering, content based filtering, and learning to rank.
• Design and conduct A/B tests to assess model performance and monitor results.
• Analyze experimental data to extract actionable insights and validate findings using statistical techniques.
• Collaborate with other engineering teams, data scientists, and marketing to integrate models into the product and communicate results to stakeholders.
• Build reusable libraries for common machine learning practices and maintain comprehensive documentation.

Requirements

• Bachelor’s degree or foreign equivalent in Computer Science or related field with three years of experience in job offered or related occupation.
• Productionisation of ML models with focus on recommendations, ranking, or personalization.
• Model development with classical ML techniques for tabular data.
• Model development with modern ML techniques for sequential data.
• Hands-on experience with architectural frameworks of large, distributed, and high-scale ML applications.
• Produce robust business outcomes through comprehensive AB test and rigorous statistical analysis.
• Proficiency in Python, SQL, XGBoost, Pytorch or Tensorflow to carry out production ready projects; and Spark, Kafka, or Kubernetes.
• Background checks required.

Benefits

• 100% paid health insurance for employees with 90% coverage for dependents.
• Lifestyle wallet a highly flexible benefits spending account for wellness, learning, and more.
• Employer-paid life and disability insurance, fertility benefits, and mental health benefits.
• Time off to recharge including company holidays, paid time off, sick time, parental leave, and more.
• Exceptional office experience with catered meals, events, and comfortable workspaces.
• Bonus opportunities and equity in addition to base pay.