On a typical day, you’ll own features end to end within our ML ecosystem, with growing independence and impact.

Own ML powered features from design through deployment, partnering with product, design, and engineering to scope work and define success metrics.

Understand and share domain knowledge, answering domain specific questions for your product area and documenting what you learn for the team.

Prioritize your work independently, balancing feature development, quality, and maintenance, and communicating tradeoffs clearly.

Proactively seek and offer support to teammates pairing, reviewing, and collaborating to move projects forward.

Understand and troubleshoot our deployment pipelines, including build, test, and release steps for ML services and data pipelines.

Use our monitoring and observability tools to effectively triage alerts and incidents, collaborating with partners to restore service and prevent recurrence, and participate in the team’s on-call rotation and incident response.

Serve as a subject matter expert for the features and services you own, including their data contracts, SLAs, and dependencies.

Be a frequent user of AI Tools and champion of adoption to the rest of the company.

What do we need from you?

4+ years of industry experience in applied Machine Learning or closely related fields (or equivalent combination of education and experience) with a demonstrated track record of shipping and operating ML models in production.

Deep and demonstrated ability to traverse the full spectrum of ML life cycle: exploratory data analysis, feature engineering, data visualization, feature and algorithm selection, model experimentation, model training and validation, model serving, monitoring and retraining

Machine Learning Engineer

Responsibilities

Benefits

Company

Calendly

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