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As a Machine Learning Engineer, you will play a key role in our data science team and the company’s development initiatives. This team supports modeling activities in conjunction with business partners to deliver improved performance of in-market models, granularity in algorithmic decision making, and scalability of solutions across our business as we continue to expand. This role will be responsible for the end-to-end architecture and deployment of data processing, model execution, and data distribution. You will also play a key role in the democratization and integration of cutting-edge technologies that will improve the scalability, flexibility, and effectiveness of how we deal with data.
Typical Duties and Responsibilities
- Contribute to the design and creation of machine learning engineering projects that promote our corporate objectives
- Manage and collaborate on cross-functional technology and data initiatives
- Advance the team’s technical expertise and serve as a subject matter expert to help the team solve problems in accordance with our overarching business vision
- Mentor and guide junior teammates and coworkers
- Support central infrastructure, libraries, and documentation
- Serve as an integrator for cross-functional communication, team culture, and development paradigms
Education
- Bachelor’s degree in computer science, mathematics, or a related field
Required Skills and Experience
- Experience building and automating scalable machine learning pipelines in cloud ecosystems (Azure, AWS, GCP)
- Experience with real-time machine learning systems
- Knowledge of the development tools and procedures used in data science and machine learning (TensorFlow, PyTorch, scikit-learn, MLFlow, etc.)
- Knowledge of cloud data solutions, including data lakes or managed services like Snowflake or Databricks, as well as data warehousing systems, data systems integration, and cloud data solutions
- SQL proficiency across a range of platforms
- Knowledge of popular programming languages such as Python or Java/Scala
- Working knowledge of Linux environments, including how to maintain packages and software versions
- Familiarity with basic development tools like git and docker
- Knowledge of scalable data processing technologies such as Hadoop/Hive and Spark
- Knowledge of statistical analysis
- Strong interpersonal and project management skills, including the ability to provide concise documentation and manage business partners across audiences with various levels of technical expertise
- Self-starter who is detail-oriented and able to develop solutions that are technically sound and cross-functional