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What You’ll Do
- Productionize machine learning models by building performant data transformations, storage, and pipelines.
- Demonstrate effective, respectful, and honest communication when collaborating with colleagues including a cross-functional team consisting of QA, Operations, and other team members.
- Apply development and testing best practices and demonstrate skilled software craftsmanship to produce maintainable, scalable, and quality solutions.
- Contribute to all phases of product development and delivery from Analysis & Design all the way through to successful Deployment.
- Deliver on company initiatives and projects prioritized for your team and support long term technical vision.
What Experience You Need
- BS degree in a STEM major or equivalent job experience required; Master’s Degree preferred; AI/ML coursework preferred
- 2-5 years of related experience
- Experience with ML models design, development or deployment
- Experience with cloud platforms and distributed computing frameworks
- Cloud Certification Strongly Preferred
- 2+ years experience working with software design and Java, Python and Javascript programming languages
- 2+ years experience with software build management tools like Maven or Gradle
- 2+ years experience with HTML, CSS and frontend/web development
- 2+ years experience with software testing, performance, and quality engineering techniques and strategies
- 2+ years experience with Cloud technology: GCP, AWS, or Azure
- Architect & Develop end-to-end data pipelines (batch & streaming) on GCP using Dataflow, Pub/Sub, Dataproc, BigQuery, and Cloud Storage
- Design & build microservices-based data applications in Java and Python, with clear APIs and containerized deployments
- Integrate AI/ML models into production pipelines and microservices, collaborating with ML teams to deploy Tensorflow/PyTorch models via Vertex AI or AI Platform
What Could Set You Apart
An ability to demonstrate successful performance utilizing our Success Profile skills, including:
- Application Development/Programming - Proficiency in Python; Experience with data processing and machine learning libraries (pandas, numpy, scipy, sklearn, tensorflow, pytorch, etc.)
- Artificial Intelligence - Understand how to deploy machine learning models to production systems, including containerization (Docker) and cloud-based deployment
- Big Data Analytics - Understand big data analysis, including data cleaning, data transformation and data visualization
- Cloud Computing - Understand big data processing frameworks and various database technologies
- Collaboration - Excellent verbal and written communication skills to document and present findings clearly
- Mathematics - Understand advanced statistical concepts and machine learning algorithms (Logistic Regression, Xgboost, Neural Networks, etc.)
- Technical Leadership - Demonstrates an ability to provide guidance to colleagues
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