Senior Ml Engineer
hace 4 meses
**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.
- 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.
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