Senior Machine Learning Engineer – Remote-USA | Visa + Salary Insights

📍 Location: us

🏷 Type: Not specified

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Job Overview

This role targets a highly experienced Senior Machine Learning Engineer specializing in ML infrastructure, agentic AI systems, and large-scale data platforms. The position sits within Zillow’s Agentic Data Foundations team, where engineers build the backbone for next-generation AI-driven customer experiences. The ideal candidate is a 5+ years experienced engineer with strong production ML expertise, capable of designing distributed systems, enabling AI agents, and translating ambiguous product needs into scalable infrastructure. This is a high-impact role blending machine learning engineering, data architecture, and AI systems design for enterprise-scale deployment.

🌍 Work Eligibility & Location

This is a fully Remote role restricted to candidates located within the United States. While flexibility is high, engineers must align with U.S. operational expectations and collaborate across distributed teams. No explicit visa sponsorship details are provided, so international applicants should assume U.S. eligibility is required unless clarified by hiring.

💰 Salary Intelligence

This compensation package places the role in the top-tier U.S. machine learning engineering market. With equity awards included, total compensation can exceed base salary significantly. The range reflects senior-level expectations in ML infrastructure, distributed systems, and agentic AI engineering, making it highly competitive compared to similar roles at major tech companies.

📊 Role Breakdown

This position focuses on building the core Agentic Data Platform that powers Zillow’s AI systems. Engineers will design and deploy machine learning infrastructure supporting real-time data pipelines, AI agent orchestration, and scalable inference systems. The role demands deep expertise in Python, Spark, Databricks, AWS, and vector databases, along with modern agent frameworks such as LangChain or LangGraph.

Approximately 35% of the role involves architecture design for ML systems, ensuring scalability, reliability, and low-latency performance. Another 30% focuses on building production-grade data pipelines and integrating AI agent workflows with retrieval systems and memory architectures. Around 20% is dedicated to cross-team collaboration, aligning applied AI teams with platform capabilities and resolving infrastructure dependencies.

The remaining 15% involves mentoring engineers, improving CI/CD pipelines, and refining observability and evaluation systems for deployed models. Strong emphasis is placed on bridging agentic AI patterns such as tool use, orchestration, embeddings, and hybrid search with real-world production constraints.

🧩 Required Skills & Fit

📈 Difficulty & Competitiveness

This is a highly competitive role requiring advanced expertise in both machine learning systems and large-scale distributed infrastructure. Candidates must demonstrate production experience with real-world ML deployments and strong architectural decision-making skills. Expect strong competition from senior engineers at top tech firms and AI startups.

🚀 Career Impact

This role offers strong long-term value by positioning engineers at the forefront of agentic AI infrastructure development. It provides exposure to cutting-edge systems powering real-world AI applications at scale. Engineers in this role typically advance into Principal Engineer, AI Architect, or Staff ML Engineer positions across top-tier AI organizations.

📋 Key Responsibilities

The engineer will design and implement machine learning infrastructure supporting Zillow’s AI ecosystem. Responsibilities include building scalable data pipelines using Spark, Databricks, and Airflow, developing AI agent frameworks using Python and LangChain-style systems, and deploying production-grade ML models with high reliability and observability.

A major focus is enabling agentic AI workflows including tool use, memory systems, retrieval-augmented generation, and ranking systems. The role also involves optimizing infrastructure for low latency, high availability, and cost efficiency. Engineers will collaborate closely with applied AI scientists and product teams to align system design with business needs.

Additional responsibilities include mentoring junior engineers, improving CI/CD pipelines, ensuring system observability, and translating ambiguous AI requirements into robust engineering solutions.

🎯 Application Strategy

🧠 Application Optimization (Adaptive)

This section is tailored for senior technical candidates applying to high-scale AI infrastructure roles.

🧠 Fit & Positioning Analysis

Evaluate your match before applying.

📅 Application Signals

This role is highly urgent and competitive due to its focus on agentic AI systems and enterprise-scale ML infrastructure. Candidates with strong production ML experience and distributed systems expertise are prioritized. Given the salary range and brand value, expect strong global competition from senior engineers in AI infrastructure and platform teams.

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✅ Job Source & Verification

This job post is derived from an official Zillow career listing, a highly credible enterprise-level tech employer in the U.S. real estate AI ecosystem. The details reflect the latest available posting, last updated within the recent hiring cycle. Compensation, responsibilities, and requirements are consistent with senior ML engineering roles in large-scale AI platform teams.