Important Information
Experience : +5 years
Job Mode : Full-time
Work Mode : Work from home
Job Summary
As an ML Engineer (11216), you will be responsible for designing, implementing, and deploying advanced machine learning models to drive dynamic pricing strategies and personalized product recommendations. You will collaborate with cross-functional teams to ensure your solutions deliver real-world impact and align with strategic business objectives. Your role will involve developing scalable ML models, maintaining data pipelines, and leveraging user behavior and subscription data to enhance consumer value.
Responsibilities and Duties
- Conceptualize, design, and implement state-of-the-art ML models for dynamic pricing and personalized product recommendations.
- Develop, implement, and deploy ML models that improve consumer value from our products by leveraging user behavior and subscription data.
- Engineer and maintain large-scale consumer behavioral feature stores, 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 alignment with strategic objectives.
- Create algorithms to optimize consumer journeys and increase conversion and monetization.
- Design, analyze, and troubleshoot controlled experiments (e.g., Causal A / B tests, Multivariate tests) to validate and measure the effectiveness of solutions.
- Apply an agile development mindset, focusing on constant iteration and improvement.
- Balance high output quality with business practicality, recognizing the benefit of "having something now" vs. "perfection sometime in the future."
Qualifications and Skills
Bachelor’s degree in Computer Science or related fields. Master’s or Ph.D. in Machine Learning, Statistics, Data Science, or related quantitative fields preferred.5+ years of experience in machine learning engineering, recommendation systems, pattern recognition, data mining, or artificial intelligence.Proficient in Python, SQL, and intermediate data engineering with tools such as MapReduce, Hadoop, Spark, Hive, and Big Data technologies.Experience with ML frameworks such as scikit-learn, Keras, TensorFlow, PyTorch, PySpark, etc.Experience in Databricks is preferred.Strong grasp of the difference between data pipelines and ML pipelines.Experience in building industry-standard recommender systems and pricing models.Experience in MLOps, ML Engineering, and Solution Design.Nice to Have :
Experience working in a consumer or B2C space for a SaaS product / software provider.Experience in developing recommendation systems and deep learning-based models.Ability to solve ambiguous and complex problems, navigating uncertain situations, and breaking down challenges into manageable components.About Encora
Encora is the preferred digital engineering and modernization partner of some of the world’s leading enterprises and digital native companies. With over 9,000 experts in 47+ offices and innovation labs worldwide, Encora’s technology practices include Product Engineering & Development, Cloud Services, Quality Engineering, DevSecOps, Data & Analytics, Digital Experience, Cybersecurity, and AI & LLM Engineering.
At Encora, we hire professionals based solely on their skills and qualifications, and do not discriminate based on age, disability, religion, gender, sexual orientation, socioeconomic status, or nationality.