2 months ago
Remote, United StatesStaff+
Base Salary
$205k - $230k/yr
Responsibilities
- Partner with the Data Platform team to exchange best practices.
- Create reusable patterns and abstractions across machine learning pipelines to simplify processes and accelerate model development and deployment.
- Develop horizontal solutions that scale machine learning models and processes robustly.
- Build maintainable, high-availability software using object-oriented design patterns and analysis.
- Participate in requirements, design, and code reviews.
- Research and prototype technologies supporting business growth.
- Collaborate with technical teams, data scientists, and applied scientists to improve the platform.
- Identify, troubleshoot, and resolve problems while determining when to escalate issues.
Requirements
- Strong coding experience with Java, C#, or Python.
- At least two years of relevant experience in applied machine learning or machine learning systems/infrastructure, including relevant machine learning engineering or related experience.
- Experience gathering data from multiple sources using big data technologies such as Spark, Hadoop, BigQuery, or Athena.
- Experience building machine learning infrastructure using robust software engineering practices.
- Knowledge of modern software development tools, systems, and practices, including Git, cloud technologies, job schedulers, and software testing.
- Experience with messaging technologies such as Kafka, Google Pub/Sub, Kinesis, or RabbitMQ.
- Experience with Docker and Kubernetes.
- Bachelor’s degree in Computer Science, Electrical Engineering, or a related field; a master’s degree is preferred.
- Experience with Microsoft Office Suite, including Word, Excel, and PowerPoint.
- Strong accuracy, attention to detail, organization, multitasking, judgment, and communication skills.
- Experience with Google Business Suite, including Gmail, Drive, Docs, Sheets, and Forms, is preferred.
Benefits
- The role may be based in an office, warehouse, or from home, with extended hours as required.
- Professional yet casual work environment with a moderate-noise, fast-paced setting.
- Reasonable accommodations are available for individuals with disabilities.
- Equal opportunity employer with protections against discrimination and harassment.
Tech Stack
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