At TripActions, “It’s all about the user. All of them.” We’re passionate about providing a seamless one-stop experience for business travelers, no matter how they travel, where they stay, or where they’re going.
TripAction is looking for a Machine Learning Ops/DevOps Engineer to join our growing team. You will be working within our world-class data organization to help modernize and scale our data platform to power our data-driven company and to support our rapidly evolving and growing data needs. You will get an opportunity to improve our existing data infrastructure and to design, build and maintain the ML deployment process and pipeline. The ideal candidate will be extremely curious and will use their data skills and business mindset to make a difference every day. We are looking for people who can operate at a company that grows as fast as ours by dealing with multiple moving pieces while still holding up quality, long-term thinking, and delivering value to our customers. We take great pride in our diversity of backgrounds, cultures, and perspectives and we strongly believe this is helping us to grow as a successful and impactful team.
What You'll Do:
- Continuously improve our data infrastructure to make it more stable, scalable, observable and secure
- Support services running in production (we are looking for true owners)
- Work on design and implementation of the new MLOps architecture
- Work closely with the data science, product, and engineering terms to develop and deploy advanced ML models
- Collaborate with the Data Warehouse and BI team to assist them in automation of their processes
- Develop our internal tooling library used by the data team
- Review and manage user access as well as create documentation to help the team follow the best practices
What We're Looking For:
- BS in Computer Science, Engineering, Mathematics, or related technical field
- 3+ years of relevant work experience in Machine Learning, DevOps, or Data Engineering
- Fluent in Python, SQL, and Shell/Bash scripting
- Proficiency with deploying models via AWS SageMaker or MLFlow
- Experience in AWS and its core offerings (EC2, RDS, S3, Lambda, Gateway API, etc)
- Experience in CI/CD pipeline implementation and tools like GitHub (including Workflows and Actions), Terraform, Docker, Jenkins, Blue Ocean, Circle CI
- Experience with columnar databases like Snowflake, Redshift, or BigQuery and ETL/ELT tools like Fivetran, Stitch, dbt, Airflow, etc
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