Senior Machine Learning Engineer

Responsibilities

• Build and improve machine learning models and data-driven systems that classify, cluster, label, and enrich Internet-observed assets and services.
• Design and develop applied ML workflows that transform raw Internet telemetry into context for internal systems and customer-facing products.
• Partner with engineering, research, security, and product teams to develop models, datasets, and feedback loops that improve coverage and quality.
• Build feature pipelines, training datasets, model evaluation frameworks, confidence-scoring systems, and cloud or on-premises services.

Requirements

• 5+ years of experience in data science, machine learning engineering, or software engineering with applied ML responsibilities.
• Experience building and deploying machine learning or statistical models in production.
• Experience programming in Go or Python and applying software engineering practices to maintainable systems.
• Experience working with large datasets and building pipelines for feature generation, training, or inference.
• Proficiency with supervised and unsupervised learning techniques, including classification, clustering, similarity scoring, or anomaly detection.
• Ability to evaluate models using sound statistics and assess precision, recall, accuracy, and confidence tradeoffs.
• Ability to write understandable, testable, maintainable code.
• Strong communication skills, including explaining technical concepts, model behavior, and tradeoffs to engineering, research, and product audiences.

Nice-to-haves

• Experience building classification, enrichment, or labeling systems for messy or partially labeled data.
• Experience deploying models in containerized environments such as Kubernetes.
• Experience with a cloud provider such as AWS, Azure, or Google Cloud.
• Familiarity with feature stores, model serving, MLOps workflows, or experiment-tracking tools.
• Familiarity with security, Internet measurement, or network-derived datasets.

Compensation

• High cost-of-living locations, including San Francisco Bay, New York City, and Seattle: $174,000 USD–$206,000 USD, plus bonus eligibility and equity.
• All other locations: $151,000 USD–$191,000 USD, plus bonus eligibility and equity.
• Compensation is localized based on employee work location for remote roles, with a factor of 83%–100% of the listed range.
• Benefits include equity, health, dental and vision coverage, retirement contributions, parental leave, mental health and wellness benefits, flexible PTO, professional development support, and an annual bonus plan for eligible non-sales roles.