Senior Software Engineer designing and operating ML infrastructure for Plaid's AI initiatives. Collaborating with product teams to accelerate AI - powered financial experiences and ensure scalable ML systems.
TC
Hybrid Senior Machine Learning Engineer – Personalization
Posted 2 months ago
About the role
- Machine Learning Engineer developing algorithms for personalization and recommendations in Disney's streaming services. Collaborating across teams to enhance user experience and engagement.
Responsibilities
- Utilize cutting edge machine learning methods to develop algorithms for personalization, recommendation, and other predictive systems; maintain algorithms deployed to production and be the point person in explaining methodologies to technical and non-technical teams
- Develop and maintain ETL pipelines using orchestration tools such as Airflow and Jenkins; deploy scalable streaming and batch data pipelines to support petabyte scale datasets
- Maintain existing and establish new algorithm development, testing, and deployment standards
- Collaborate with product and business stakeholders: Identify and define new personalization opportunities and work with other data teams to improve how we do data collection, experimentation and analysis
Requirements
- 5+ years of experience developing machine learning models, performing large-scale data analysis, and/or data engineering experience
- 5+ years writing production-level, scalable code (Python, SQL)
- 3+ years of experience developing algorithms for deployment to production systems
- In-depth understanding of modern machine learning (e.g. deep learning methods), models, and their mathematical underpinnings
- Experience deploying and maintaining pipelines and in engineering big-data solutions using technologies like Databricks, S3, and Spark
- Ability to gauge the complexity of machine learning problems and a willingness to execute simple approaches for quick, effective solutions as appropriate
- Strong written and verbal communication skills
- MS or PhD in statistics, math, computer science, or related quantitative field (preferred)
- Production experience with developing content recommendation algorithms at scale (preferred)
- Experience building and deploying full stack ML pipelines: data extraction, data mining, model training, feature development, testing, and deployment (preferred)
Benefits
- A bonus and/or long-term incentive units may be provided as part of the compensation package
- Full range of medical, financial, and/or other benefits
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