Artificial Intelligence/Machine Learning Engineer
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Job summary
The role is to lead the team to work to turn business questions into data analysis effectively and provide meaningful recommendations. This is a unique hybrid role that will focus on your knowledge of data infrastructure and your ability to drive insights. The job holder will develop models, train them, and set department objectives.
Min Qualification:
Degree
Experience Level:
Entry level
Experience Length:
2 years
Job descriptions & requirements
Responsibilities:
- Architect, build, maintain, and improve new and existing suites of algorithms and their underlying systems.
- Implement end-to-end solutions for batch and real-time algorithms along with requisite tooling around monitoring, logging, automated testing, performance testing, and A/B testing.
- Utilize your entrepreneurial spirit to identify new opportunities to optimize business processes and improve consumer experiences, and prototype solutions to demonstrate value with a crawl, walk, run mindset.
- Work closely with data scientists and analysts to create and deploy new product features.
- Establish scalable, efficient, automated processes for data analyses, model development, validation, and implementation.
- Write efficient and well-organized software to ship products in an iterative, continual-release environment.
- Contribute to and promote good software engineering practices across the team.
- Knowledge sharing with the team to adopt best practices.
- Actively contribute to and reuse community best practices.
Requirements:
- Minimum of a University or advanced degree in engineering, computer science, mathematics, or a related field.
- Minimum of 2 years of experience developing and deploying machine learning systems into production,
- Strong experience working with a variety of relational SQL and NoSQL databases.
- Strong experience working with big data tools: Hadoop, Spark, Kafka, etc.
- Experience with at least one cloud provider solution (AWS, GCP, Azure).
- Strong experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.
- Ability to work in a Linux environment.
- Industry experience building innovative end-to-end Machine Learning systems.
- Ability to quickly prototype ideas and solve complex problems by adapting creative approaches.
- Experience working with distributed systems, service-oriented architectures, and designing APIs.
- Strong knowledge of data pipeline and workflow management tools.
- Expertise in standard software engineering methodology, e.g. unit testing, test automation, continuous integration, code reviews, and design documentation.
- Relevant working experience with Docker and Kubernetes is a big plus.
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