Staff ML Engineer

About the role

Company Description Press Ganey is the leading experience measurement, data analytics, and insights provider for complex industries-a status we earned over decades of deep partnership with clients to help them understand and meet the needs of their key stakeholders. Our earliest roots are in U.S. healthcare -perhaps the most complex of all industries.

Today we serve clients around the globe in every industry to help them improve the Human Experiences at the heart of their business. We serve our clients through an unparalleled offering that combines technology, data, and expertise to enable them to pinpoint and prioritize opportunities, accelerate improvement efforts and build lifetime loyalty among their customers and employees.

Like all great companies, our success is a function of our people and our culture. Our employees have world-class talent, a collaborative work ethic, and a passion for the work that have earned us trusted advisor status among the world's most recognized brands. As a member of the team, you will help us create value for our clients, you will make us better through your contribution to the work and your voice in the process.

Ours is a path of learning and continuous improvement; team efforts chart the course for corporate success. Our Mission: We empower organizations to deliver the best experiences. With industry expertise and technology, we turn data into insights that drive innovation and action. Our Values: To put Human Experience at the heart of organizations so every person can be seen and understood.

Energize the customer relationship: Our clients are our partners. We make their goals our own, working side by side to turn challenges into solutions. Success starts with me: Personal ownership fuels collective success. We each play our part and empower our teammates to do the same. Commit to learning: Every win is a springboard. Every hurdle is a lesson. We use each experience as an opportunity to grow.

Dare to innovate: We challenge the status quo with creativity and innovation as our true north. Better together: We check our egos at the door. We work together, so we win together. If you need assistance or an accommodation to apply for a position online or for your interviews or assessments, please contact us at Please provide your contact information and the details of your request so we can best assist you.

We are seeking a Staff ML Engineer to lead the design, delivery, and operation of production-grade AI systems. You will build the services and high-throughput pipelines behind our text analytics platform and a growing portfolio of AI products, processing feedback and conversations from every channel our customers use to engage with patients and their customers.

The central challenge is sustaining service reliability and measurable AI quality as models, inputs, and volumes change. As a technical leader, you will guide engineers through design and implementation, contribute directly to the codebase, and lead architectural decisions across teams.

Working primarily with Python and cloud-based data and AI platforms, with a growing emphasis on Databricks, you will shape the shared infrastructure supporting both established products and new AI applications.

What You'll Do

Own technical delivery from prototype through deployment and ongoing production support, partnering with AI Scientists and Product to define requirements, plan implementation, and resolve cross-team dependencies. Evaluate proposed AI solutions for production suitability, identify technical risks, and choose architectures that meet quality, reliability, and cost requirements without unnecessary complexity.

Architect and build high-volume AI services and processing pipelines, including fault tolerance, backpressure, retries, idempotency, and recovery from partial failures. Lead the evolution of our Python services and Databricks-based platform for distributed processing, model serving, and integration of traditional ML and LLM-based components.

Establish production engineering standards for automated testing, CI/CD, model and prompt versioning, load testing, controlled rollouts, and rollback. Build evaluation and monitoring capabilities to detect AI quality regressions and track service reliability, throughput, latency, and inference cost.

• Partner with Product and Responsible AI teams to define release criteria and implement requirements for model validation, data privacy, security, and governance.
• Optimize processing and inference workloads, balancing model quality, throughput, latency, capacity, and cost.
• Mentor engineers and lead architecture and code reviews, maintaining consistent standards for software quality and maintainability.

What You'll Bring

Bachelor's degree in Computer Science, Electrical Engineering, or a related technical discipline, or equivalent practical experience. 8+ years of professional software engineering experience, including at least 3 years owning ML or LLM systems in production and their operational support.

Proven track record of independently leading complex technical initiatives from requirements through production, making architectural decisions and coordinating delivery across stakeholders. Advanced proficiency in Python for production services and data processing, with strong SQL skills.

• Experience designing and operating high-throughput distributed systems, with a 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.

Pay and benefits

Experience with Databricks or comparable cloud-based data and AI platforms for workflow orchestration, scalable processing, model deployment, and evaluation. Experience with NLP, text analytics, or large-scale processing of unstructured data. Experience building shared infrastructure for inference, evaluation, and model lifecycle management.

Familiarity with retrieval-augmented generation, semantic search, and LLM orchestration frameworks. Experience with speech-to-text, speaker diarization, or processing conversational audio data. Experience deploying and operating cloud-native services on AWS or Azure. Experience with healthcare or other regulated environments, including sensitive data handling, auditability, and model governance.

Don't meet every single requirement? Studies have shown that women and people of color are less likely to apply to jobs unless they meet every single qualification. At Press Ganey we are dedicated to building a diverse, inclusive and authentic workplace, so if you're excited about this role but your past experience doesn't align perfectly with every qualification in the job description, we encourage you to apply anyways.

You may be just the right candidate for this or other roles. Pay Transparency Non-Discrimination Notice - Press Ganey will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant.

However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with the contractor's legal duty to furnish information.

The expected base salary for this position ranges from $130,000 to $190,000. It is not typical for offers to be made at or near the top of the range. Salary offers are based on a wide range of factors including relevant skills, training, experience, education,, where applicable, licensure or certifications obtained. Market and organizational factors are also considered.

In addition to base salary and a competitive benefits package, successful candidates are eligible to receive a discretionary bonus or commission tied to achieved results. All your information will be kept confidential according to EEO guidelines.