Remote ML Engineer

Summary

Join our team at Encora as a Machine Learning Engineer to conceptualize, design, and implement state-of-the-art ML models for dynamic pricing strategies and personalized product recommendations. As a key member of our team, you will develop, implement, and deploy machine learning models that leverage user behavior and subscription data to improve consumer value from our products.

Requirements

• Bachelor's degree in Computer Science or related fields
• 5+ years of experience in one or more of the following areas: machine learning engineering (including deep learning), recommendation systems, pattern recognition, data mining or artificial intelligence
• Proficient in Python, SQL, intermediate data engineering skill set with tools, libraries, or frameworks such as MapReduce, Hadoop, Spark, Hive and Big Data technologies, scikit-learn, Keras, TensorFlow, PyTorch, PySpark etc
• Experience in Databricks
• Experience with various ML techniques and frameworks, e.g., data discretization, normalization, sampling, linear regression, decision trees, deep neural networks, etc
• Experience in building industry-standard recommender systems and pricing models
• Experience in MLOps, ML Engineering and Solution Design

Responsibilities

• Ability to attend meetings and discussions during overlapping XXXX Standard Time (XST) hours
• ML acumen to conceptualize, design, and implement state-of-the-art ML models for dynamic pricing strategies and personalized product recommendations
• Strong grasp of understanding difference between data pipelines and ML pipelines
• Develop, implement, and deploy machine learning models that leverage our unique combination of user behavior and subscription data to improve consumer value from our products
• Engineer and maintain large-scale consumer behavioral feature stores while ensuring scalability and performance
• Develop and maintain data pipelines and infrastructure to support efficient and scalable ML model development and deployment
• Collaborate with cross-functional teams (Marketing, Product, Sales) to ensure your solutions align with strategic objectives and deliver real-world impact
• Create algorithms for optimizing consumer journeys and increasing conversion and monetization
• Design, analyze, and troubleshoot controlled experiments (Causal A/B tests, Multivariate tests) to validate your solutions and measure their effectiveness
• Agile development mindset, appreciating the benefit of constant iteration and improvement
• Focus on business practicality and the 80/20 rule; very high bar for output quality, but recognize the business benefit of 'having something now' vs 'perfection sometime in the future

Preferred Qualifications

• Experience working in a consumer or B2C space for a SaaS product/software provider
• Experience in developing recommendation systems and deep learning-based models
• Excell in solving ambiguous and complex problems, being able to navigate through uncertain situations, breaking down complex challenges into manageable components and developing innovative solutions