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Machine Learning Engineer
Skills
JavaSQLAmazon Web ServicesApplied Machine LearningCassandraData ScienceElasticsearch
What the job involves
The main requirements, responsibilities and hiring steps.
Requirements
- 3+ years as Data Scientist/Machine Learning Engineer
- Bachelor's or preferred Graduate degree in relevant field
- Experience with big data tools: Spark, Elasticsearch, Hadoop, Kafka, Kinesis
- Proficiency in relational SQL and NoSQL databases: MySQL, Postgres, DynamoDB, Cassandra
- Skilled in AWS: EC2, RDS, EMR, Redshift
- Proficient in functional and scripting languages: Python, Java, Scala
- Experience with various ML models and Deep Learning Neural Networks
- Experience with AWS AI/ML Services and Python coding
- Advanced SQL knowledge and familiarity with different databases
- Experience in building and optimizing big data pipelines, architectures, and datasets
- Strong analytic skills for working with unstructured datasets
- Knowledge of message queuing, stream processing, and scalable big data stores
- Experience in dynamic customer-facing environments
Nice to have
- AWS Machine Learning Specialty
- AWS Solutions Architect - Associate
Day to day
- Support AI/ML projects on AWS, using native services and custom models to deliver insights to customers.
- Assist in cloud migration, optimize databases and data flows, and enrich operational data with AI/ML algorithms.
- Collaborate with solutions architects, project managers, and data scientists to design new systems and migrate or optimize existing ones.
- Build and operate infrastructure for optimal data extraction, transformation, and loading from various sources using SQL and cloud/big data technologies.
- Use Jupyter Notebooks for building and deploying ML models and leverage AWS AI/ML pre-built solutions.
- Ensure data security and compliance with regulations.
- Address technical issues and support data infrastructure and business needs for customers and internal stakeholders.