Senior Machine Learning Engineer

Seattle, WA · Remotefull time

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Remote

senior

$187k–$202k

H1B: no

Possible Finance Senior Machine Learning Engineer at Possible Finance responsible for owning and building ML infrastructure. Key duties include designing a shared feature store, implementing drift monitoring, and consolidating deployment tooling.

Responsibilities

You'll be Possible's first dedicated owner of ML infrastructure — a green-field mandate with real autonomy to shape how we build, deploy, and monitor machine learning models going forward. In your first year, you'll design and roll out a shared feature store, giving our data teams a safe place to experiment with new features without ever touching production, and meaningfully improving how fast our models respond in real time. You'll bring visibility to a part of our systems that's currently a black box, standing up drift monitoring so we catch model degradation before it becomes a customer-facing problem. And you'll consolidate a patchwork of deployment tooling into one clean, reliable pipeline — covering not just the models we ship, but the ones we try and learn from along the way. This is a role for someone who takes ownership seriously: you'll start as a team of one, kickstarting the processes and standards Possible's ML function will run on for years, applying the same scientific rigor to your own infrastructure decisions that our data scientists apply to their models.

Qualification

DeepA track record of solving ambiguousStrong proficiency in PythonA demonstrated drive for resultsA self-starter mindset — energized

Required

Deep, hands-on experience building and operating machine learning infrastructure — feature stores, model serving, and monitoring systems — in a production environment
A track record of solving ambiguous, undefined problems: this role has no existing playbook at Possible, and you'll build one
Strong proficiency in Python, AWS, and Databricks, with genuine engagement with the broader MLOps tooling landscape and the judgment to evaluate and choose the right tools for the job
A demonstrated drive for results, holding yourself accountable to a high, concrete bar for your own work
Comfort working cross-functionally with data scientists and engineers, bringing them along on new tooling rather than mandating it top-down
A self-starter mindset — energized, not daunted, by being the first person in a role and building what it needs from scratch

Benefits

Equity/RSU

Company

Possible Finance

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Source: ashby

Active within the past hour

Remote-friendly

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