Senior Machine Learning Engineer

Posted Yesterday
Seattle, WA, USA
In-Office
186K-255K Annually
Senior level
Software • Big Data Analytics
The Role
Lead and deliver production ML systems end-to-end: design CI/CD and deployment architecture, build real-time and batch feature pipelines, implement automated retraining and monitoring with drift detection, optimize inference latency and costs, establish SLOs and incident response, and collaborate with applied scientists, engineers, and product to produce measurable customer impact while mentoring teammates.
Summary Generated by Built In

At Amperity, we’re an AI-first company helping the world’s leading brands create personalized customer experiences that build loyalty and fuel growth. Our AI-powered Customer Data Cloud,  built on multi-patented technology, enables more than 400 global brands, including Alaska Airlines, Wyndham Hotels & Resorts, and DICK’S Sporting Goods, to turn customer data into a competitive advantage.

We unlock the full value of customer data with simplicity and speed. AI is at the core of our platform and the way we work — from powering advanced identity resolution and predictive analytics to streamlining internal workflows and decision-making. It’s not just a capability; it’s part of our DNA.

Our team thrives on curiosity, collaboration, and transparency, fostering a culture where everyone can contribute, learn, and grow. We welcome talented individuals from diverse backgrounds to help us remove data bottlenecks, accelerate business impact, and push the boundaries of what AI can do for the world’s most innovative companies.

With offices in Seattle, New York City, London, and Melbourne, you’ll join a fast-growing team tackling critical challenges at the intersection of AI, data, and customer experience. Ready to make an impact? Let’s talk.

The Role

At Amperity, ML Engineers work in small, collaborative, and accountable teams. As a Senior ML Engineer, you'll lead complex, ambiguous ML projects within your team's space and own technically deep pieces of its ML architecture. You'll create agreement and simplicity on your team. Being an ambassador for your work, you'll collaborate across team lines. Partnering with Applied Scientists, Software Engineers, and Product Managers, you'll deliver production ML systems that create measurable customer impact. We are an AI-first company. We expect engineers to embrace AI assistance tools like Claude Code as a core part of their daily workflow—using them to accelerate development and improve code quality. We keep our processes lightweight, our experimentation rigorous, and our focus on delivering value to our customers through machine learning products and features.

Interesting Problems

We're solving tough problems at the intersection of large-scale data, AI, and user experience. Some of the challenges you might work on include:

  • Design the CI/CD pipelines and deployment architecture for the ML systems your team owns, making them reliable, repeatable, and easy to operate.
  • Build automated retraining pipelines triggered by performance degradation, and architect monitoring solutions with drift detection and alerting.
  • Design real-time and batch feature pipelines that power identity resolution, customer segmentation, and predictive models at scale.
  • Improve model inference latency to deliver predictions that meet strict Service level agreements while keeping infrastructure costs in check.
  • Establish SLOs and operational standards for your team's production ML. Lead incident response and blameless post-mortems. Evaluate MLOps tooling that raises the bar for the team, including experiment tracking, model registry, and serving.
About You

You're a ML engineer who pairs deep technical judgment with the ability to build and operate production systems end-to-end. You own technically complex pieces of your team's ML architecture. Your teammates seek you out for advice in your space. You ramp quickly in unfamiliar areas—often leaning on AI tools to do it—and you embrace AI-first practices, helping establish how your team works with tools like Claude Code. You value simplicity, mentorship, and well-reasoned decisions.

  • 5+ years building production ML systems, including hands-on experience designing ML pipelines and infrastructure.
  • Experience leading complex or ambiguous ML projects within a team as the directly responsible individual.
  • Expertise in ML deployment patterns, model serving, feature engineering, and monitoring/observability for ML systems.
  • Software engineering skills with experience in Python and familiarity with ML frameworks (e.g. XGBoost, PyTorch, PySpark).
  • Experience with cloud-native ML infrastructure, containerization, and orchestration (Kubernetes, Docker).
  • Enthusiastic about AI-first development practices, with experience using AI coding assistants to accelerate engineering workflows.
  • A habit of mentoring teammates, reviewing others' work, and elevating how your team builds and operates ML systems.
Technologies To Know

We don't expect you to have experience with everything we use—but if you're excited about learning, you'll do great here. You'll influence and learn:

  • Large-scale data engines like Apache Spark, Presto, and Kafka.
  • MLOps tooling including MLflow, feature stores, and model serving frameworks.
  • Cloud-native infrastructure built with Kubernetes and Terraform, deployed across multiple cloud providers.
  • Functional programming languages including Clojure and Python for ML pipelines.
  • Machine learning models for entity resolution, classification, and customer analytics.
  • AI coding assistants (such as Claude Code) as part of our daily development workflow.
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:  $185,600-$255,000. Individual compensation within this range will depend on several factors, including your skills, experience, education/training, geographic location and the level at which you join. We also consider internal equity, market conditions, and overall business needs.

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.

Skills Required

  • 5+ years building production ML systems, including hands-on experience designing ML pipelines and infrastructure.
  • Experience leading complex or ambiguous ML projects within a team as the directly responsible individual.
  • Expertise in ML deployment patterns, model serving, feature engineering, and monitoring/observability for ML systems.
  • Software engineering skills with experience in Python and familiarity with ML frameworks (e.g. XGBoost, PyTorch, PySpark).
  • Experience with cloud-native ML infrastructure, containerization, and orchestration (Kubernetes, Docker).
  • Enthusiastic about AI-first development practices, with experience using AI coding assistants to accelerate engineering workflows.
  • A habit of mentoring teammates, reviewing others' work, and elevating how your team builds and operates ML systems.

Amperity Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Amperity and has not been reviewed or approved by Amperity.

  • Fair & Transparent Compensation Pay is considered market-competitive and structured, with clear processes and pay transparency. Offers are often seen as fair without extensive negotiation.
  • Equity Value & Accessibility Equity is broadly included alongside cash, with new-hire stock options for all employees and eligibility for bonuses. This ownership component is a meaningful part of total compensation.
  • Healthcare Strength Health, dental, and vision coverage is comprehensive with 100% of employee premiums covered and additional wellness programs. Mental health resources, life and pet insurance, and strong coverage are frequently highlighted.

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The Company
HQ: Seattle, WA
276 Employees
Year Founded: 2016

What We Do

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.

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