Staff ML Engineer

🔥 0 minutes ago

🇺🇸 United States – Remote

💵 $130k - $190k / year

⏰ Full Time

🔴 Lead

🤖 Machine Learning Engineer

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Press Ganey

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 1985

💼 Consulting

📦 Logistics

🏥 Healthcare

Consulting • Logistics • Healthcare

Press Ganey is a leading provider of patient experience measurement, performance analytics, and strategic advisory solutions for healthcare organizations. The company focuses on improving the overall healthcare experience through advanced analytics and human-centered insights, helping clients enhance patient and workforce safety, employee experience, and organizational growth. With a data-driven approach, they provide interactive dashboards, industry benchmarks, and actionable insights to drive measurable impact across the healthcare sector. Press Ganey collaborates with healthcare providers, health plans, and life sciences organizations to transform care delivery and improve human experiences in healthcare.

📋 Description

• Lead the design, delivery, and operation of production-grade AI systems • Build services and high-throughput pipelines for a text analytics platform and AI products • Own technical delivery from prototype through deployment and ongoing production support • Partner with AI Scientists and Product to define requirements, plan implementation, and resolve cross-team dependencies • Evaluate AI solutions for production suitability and identify technical risks • Choose architectures meeting quality, reliability, and cost requirements • Architect and build high-volume AI services and processing pipelines with fault tolerance, backpressure, retries, idempotency, and partial-failure recovery • Lead the evolution of Python services and a Databricks-based platform for distributed processing, model serving, and ML/LLM integration • Establish standards for automated testing, CI/CD, model and prompt versioning, load testing, controlled rollouts, and rollback • Build evaluation and monitoring capabilities for AI quality regressions and service reliability, throughput, latency, and inference cost • Partner with Product and Responsible AI teams on release criteria, model validation, data privacy, security, and governance • Optimize processing and inference workloads for quality, throughput, latency, capacity, and cost • Mentor engineers and lead architecture and code reviews

🎯 Requirements

• Bachelor's degree in Computer Science, Electrical Engineering, or a related technical discipline, or equivalent practical experience • 8+ years of professional software engineering experience • At least 3 years owning ML or LLM systems in production and their operational support • Proven ability to independently lead complex technical initiatives from requirements through production • Advanced proficiency in Python for production services and data processing • Strong SQL skills • Experience designing and operating high-throughput distributed systems • Strong understanding of failure recovery, multi-tenancy, and capacity planning • Hands-on experience deploying and operating LLM-based applications, including evaluation, output validation, observability, and cost management • Strong production engineering practices across automated testing, CI/CD, monitoring, incident response, and root-cause analysis • Demonstrated technical leadership through system design, hands-on implementation, code review, and mentorship • Ability to communicate technical decisions and tradeoffs clearly to engineering, research, product, and governance stakeholders • Preferred: Experience with Databricks or comparable cloud-based data and AI platforms • Preferred: Experience with NLP, text analytics, or large-scale processing of unstructured data • Preferred: Experience building shared infrastructure for inference, evaluation, and model lifecycle management • Preferred: Familiarity with retrieval-augmented generation, semantic search, and LLM orchestration frameworks • Preferred: Experience with speech-to-text, speaker diarization, or conversational audio processing • Preferred: Experience deploying and operating cloud-native services on AWS or Azure • Preferred: Experience with healthcare or other regulated environments, including sensitive data handling, auditability, and model governance

🏖️ Benefits

• Competitive benefits package • Discretionary bonus or commission tied to achieved results • Reasonable accommodations for qualified individuals with disabilities or disabled veterans during the hiring process