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Cloud Engineer
3 months ago
- Client's MODE (Media Operations, Data, and Execution) team is looking for Senior Data & ML Engineer who is curious, driven, and passionate about big data technologies, MLOps, and building a project from scratch.
- This role will require participating in full-cycle big data management, processing, infrastructure and ML system design to build mission critical, high-volume ML/AI applications to optimize delivery of relevant and advertising experiences to customers.
- As a Senior Engineer, you will operate as a mix of hands-on builder and influencer.
- You will work closely with engineers and scientists contributing to the ongoing development and evolution of the underlying machine learning systems and data infrastructures.
- Pairing with product teams, software engineers, data engineers, and scientists to design and develop highly scalable and robust data and ML platforms to serve analytics and productionize AI/ML models for optimizing advertising reach, frequency and return on advertising spend.
- Build scalable and reliable data pipelines that efficiently ingest and process large volume of data from disparate sources and formats and continuous integration with internal and external systems.
- Design and build large scale data repositories as knowledge base for GenAI applications.
- 5+ years of experience as a ML Engineer, Data Engineer, Software Engineer, or in a similar role.
- Familiarity with the full life cycle of software development, from design and implementation to testing and deployment.
- Experience with distributed systems and distributed parallel compute frameworks (e.g., Apache Spark, Apache Ray, Dask, etc.)
- Experience with scaling ML workloads, MLOps, and designing ML systems.
- Experience with data modeling, data warehousing, and designing ETL workflows.
- Proficiency in SQL.
- Proficiency in at least one software programming language of Python, Java, Scala.
- Experience working with cloud services (AWS, Azure, GCP, etc.)
- Experience working with AWS ecosystem, and development with AWS CDK.
- Knowledge of Data Privacy, Security, Risk, and Compliance best practices.
- Experience in machine learning, data mining, information retrieval, statistics or natural language processing.
- Experience with LLM fine tuning, developing, evaluating and deploying LLM for real-world applications.