The ML Engineer will conceptualize and implement ML models for dynamic pricing and personalized recommendations, develop large-scale data pipelines, and collaborate with cross-functional teams to deliver impactful solutions. Responsibilities also include creating algorithms for optimizing consumer journeys and conducting controlled experiments to validate effectiveness.
Important Information
Location: PAN India
Experience: 5+ Years
Job Mode: Full-time
Work Mode: Work from home
Responsibilities and Duties
- Ability to attend meetings and discussions during overlapping XXXX Standard Time (XST) hours (must-have).
- 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"
Qualifications and Skills
- Bachelor's degree in Computer Science or related fields. Master or D in Machine Learning, Statistics, Data Science or related quantitative fields preferred.
- 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 is preferred
- 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.
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
- 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
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.
Top Skills
Python
SQL
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