Lead Machine Learning Engineer
Seattle, WA
Full Time Senior-level / Expert USD 190K - 260K
At Amperity, our AI-powered Customer Data Cloud empowers organizations to delight their customers and create differentiated experiences. Our multi-patented technology helps over 400 leading global brands like Alaska Airlines and DICK'S Sporting Goods drive revenue growth and meaningful customer experiences. We help users unlock the value of all of their customer data with simplicity and speed. Our team thrives on curiosity, collaboration, and transparency, fostering a culture where everyone can contribute and grow. We're looking for talented individuals from diverse backgrounds to help us eliminate data bottlenecks and accelerate business impact for the world's most innovative companies. With offices in Seattle, New York City, London, and Melbourne, you'll be part of a fast-growing team solving critical challenges at the intersection of AI, data, and customer experience. Ready to make an impact? Let's talk.
The Role
Data Science at Amperity identifies, designing, and implementing the algorithms that power core parts of our platform. We focus on two primary domains:
- Identity Resolution: Our proprietary entity resolution system deduplicates and clusters billions of customer records daily. These identity graphs are foundational to our customers' personalized experiences across every touchpoint.
- Predictive Analytics: With unified, enriched customer profiles, we build advanced customer-centric models to predict behaviors and outcomes such as customer lifetime value, churn risk, product recommendations, and event propensity.
Beyond building models, we care about advancing the field of data science. We share our work with the broader community—through peer-reviewed publications, conference talks, and patents centered on our core innovations. You will report to the SVP, Engineering and you will be located in Seattle, WA.
Interesting Problems
We're solving complex challenges at the intersection of large-scale data, machine learning, and user experience. Some of the problems you might work on include:
- Apply the latest advancements in data science and AI to accelerate time-to-value for data engineers, analysts, and marketers.
- Build machine learning and statistical modeling solutions that are tightly integrated into our platform, helping our customers unlock relevant insights from their customer data and grow meaningful engagement.
- Design and deploy scalable systems to process and reason over massive volumes of structured and unstructured customer, product, and event data.
- Rethink how marketing, customer experience, and analytics teams activate and use data to achieve measurable outcomes.
- Bridging the gap between experimentation and production—ensuring the solutions you build are explainable, and deployed to users.
- Contribute to our long-term data science and ML strategy, including evaluating new technologies and shaping Amperity's future in this space
About You
You're an experienced data science engineer who blends deep technical expertise with a product mindset. You excel in environments, care about delivering revenue, and aren't afraid to get models into production. You lead through thoughtful system design, collaboration, and mentorship.
- 12+ years of experience building and evolving complex, high-scale software systems.
- Technical leadership in shipping ML features and data-driven product capabilities.
- 5+ years of experience working with distributed systems, large-scale data pipelines, or cloud-native architectures.
- 8+ years of hands-on coding experience with system design and architecture sensibilities.
- Experience developing data science strategies that directly improve customer or value.
- Experience identifying high-use data opportunities and translating them into usable, customer-facing features.
- Comfortable working across teams and technical concepts to diverse partners—engineering, product, marketing, customer success, and beyond.
- Experience overseeing the full ML lifecycle—from model development to deployment and monitoring in production environments.
Location
Seattle, WA
Our hybrid work model includes three days in the office each week, providing a mix of in-person collaboration and remote flexibility
Compensation
Base Salary: $190,000 - $260,000. Within our pay range, individual salaries are determined by a variety of factors including, but not limited to: business considerations, local market conditions, internal equity, as well as candidate qualifications such as skills, experience, and education/training.
Cash Incentives: Cash incentives are also available.
Stock Options: The opportunity for ownership is an exciting part of Amperity’s total compensation package. Every employee at Amperity receives a new-hire equity grant, commensurate with the scope of their position.
Benefits
We offer all the benefits you'd expect from a great place to work: 100% employee healthcare coverage, transportation subsidies, a comfortable work environment with plenty of snacks, and other employee experience perks like events and activities, both in-person and remote. We also offer self-managed PTO and the flexibility to do your best work in the way that works for you. We provide an inclusive environment where you'll be challenged to find and unlock your full potential, surrounded by a team of world-class people driving for excellence. For more details on our benefits, please see our US Benefits & Perks Guide.
Amperity is proud to be an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, sex (including pregnancy, childbirth, and reproductive health choices), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as someone with a disability, political views or activity, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state, and local law.
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Tags: Architecture CX Data pipelines Distributed Systems Engineering Excel Machine Learning ML models Pipelines Statistical modeling Statistics
Perks/benefits: Career development Equity / stock options Health care Team events Transparency
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