Senior Machine Learning Engineer

About 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.

Responsibilities

• 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.
• Evaluate 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.

Requirements

• 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.

Qualifications

• Technologies To Know: 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.

Skills

• Deep technical judgment paired with the ability to build and operate production systems end-to-end.
• Ownership of technically complex pieces of your team's ML architecture.
• Ability to ramp quickly in unfamiliar areas—often leaning on AI tools to do it.
• Embracing AI-first practices, helping establish how your team works with tools like Claude Code.
• Value placed on simplicity, mentorship, and well-reasoned decisions.

Benefits

• 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.
• 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: 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.
• Paid Time Off: Self-managed PTO and the flexibility to do your best work in the way that works for you.

Pay

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.

Schedule

Our work model operates on four in-office days each week and one designated remote workday on Wednesdays.