Founding ML Engineer — Turn Data into Customer Insight

Plutus; Kirkland (WA); On-site; USD 180,000 - 240,000; Full time

Job summary

Plutus is seeking a founding machine learning engineer to scale from v1 to a billion under management by year-end. You will design and deploy data pipelines and models that surface insight to customers, not just internal dashboards.

You will own end-to-end experiments, collaborate with product and engineering, and operate in ambiguity at an early-stage startup. You should have strong ML fundamentals, experience taking models to production, and a passion for turning data into product, with a

Qualifications

• Strong fundamentals in machine learning and applied data science.
• Hands-on experience building and operating data pipelines at scale.
• Strong software engineering fundamentals and maintainable code.
• Extreme ownership in an early-stage startup environment.
• Deep curiosity about the customer and product-driven mindset.
• Genuine belief in our mission and financial motivation as a feature.

Responsibilities

• Turn data into product by designing and building data pipelines and models.
• Focus on outcomes and product goals, not just modeling modality.
• Help drive retention by understanding customer needs and timing.
• Work as an engineer first with strong product sense and shipability.
• Live in the customer's shoes and close gaps between product promises and reality.
• Behave like an owner in a small, fast-moving team.

Skills

ML fundamentals

Data pipelines

Software engineering

Startup ownership

Customer focus

Mission alignment

Job description

Plutus is seeking a founding machine learning engineer to scale from v1 to a billion under management by year-end. You will design and deploy data pipelines and models that surface insight to customers, not just internal dashboards.

You will own end-to-end experiments, collaborate with product and engineering, and operate in ambiguity at an early-stage startup. You should have strong ML fundamentals, experience taking models to production, and a passion for turning data into product, with a