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Staff AI/ ML Engineer

Company Description

PG Forsta 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:

To elevate the human experiences at the heart of business by offering insights that sharpen understanding of the needs of individuals and populations, and provide guidance on how to meet those needs.  

We partner clients to gather the voice of consumers and the workforce to gain insights that address unmet needs.  Through the use of integrated data, advanced analytics and strategic advisory services, we are helping clients transform their organizations to deliver high quality services and lifetime loyalty. 

Our Values:

Champion the Client

We demonstrate an unwavering passion for delivering high-quality solutions and service. We commit to understanding the goals and needs of our clients. We always look for opportunities to improve and create value. Each of us understands our role in enabling client success.

All Together Better

We are united by the common purpose of our vision and mission. We promote teamwork and a culture of belonging  by building strong relationships and fostering trust. We collaborate to identify and develop innovative solutions.

Embrace Change

We recognize that change is constant and presents opportunities to learn, adapt, and evolve.  We seek creative solutions to challenges and e pursue them with optimism and enthusiasm.

Do the Right Thing

We demonstrate commitment to all our stakeholders, including clients, staff, and partners. We take personal accountability for our responsibilities and actions. We do right by each other by acting with honesty and kindness. We provide meaningful recognition and feedback to others.

 

Job Description

Press Ganey is looking to hire a self-motivated Staff ML Engineer with NLP and GenAI experience. The Senior Machine Learning Engineer will play a crucial role in designing, deploying, and enhancing state-of-the-art large language models (LLMs) and generative AI solutions. This position focuses on creating intelligent, interactive, and scalable systems using agentic frameworks and chat interfaces to deliver a seamless user experience. The ideal candidate will have a strong background in natural language processing, deep learning, and deployment practices, as well as experience building robust machine learning (ML) systems that power conversational AI applications.

Duties & Responsibilities

  • Design and deploy LLMs and GenAI systems, optimizing for scalability, performance, and response quality.
  • Deploy machine learning models into production, ensuring reliability, efficiency, and scalability across cloud or hybrid environments.
  • Build and maintain robust CI/CD pipelines tailored to ML model lifecycle management, ensuring a streamlined and agile deployment process.
  • Monitor model performance, identify potential improvements, and integrate feedback loops for continuous learning and adaptation.
  • Integrate models with chat interfaces and conversational platforms to create responsive, user-centric applications.
  • Investigate and implement agent-based architectures that support conversational intelligence and interaction modeling.
  • Collaborate with cross-functional teams to design AI-driven features that enhance user experience and interaction within chat interfaces.
  • Work closely with data scientists, product managers, and engineers to ensure alignment on project goals, data requirements, and system constraints.
  • Mentor junior engineers and provide guidance on best practices in ML model development, deployment, and maintenance.
  • Create and maintain comprehensive documentation for model architectures, code implementations, data workflows, and deployment procedures to ensure reproducibility, transparency, and ease of collaboration.

Technical Skills

  • Experience with large-scale deployment tools and environments, including Docker, Kubernetes, and cloud platforms like AWS, Azure, or GCP.
  • Experience deploying ML models at scale and optimizing models for low-latency, high-availability environments.
  • Strong programming skills in Python and proficiency in libraries such as NumPy, Pandas, and Scikit-learn.
  • Experience with machine learning frameworks such as TensorFlow, PyTorch, and Hugging Face Transformers.
  •  Familiarity with data pipelines, ETL processes, and experience with distributed data frameworks like Apache Spark or Dask.
  • Knowledge of conversational AI, agent-based systems, and chat interface development.
  • Proven track record in working with LLMs and conversational interfaces in a production setting.
  • Experience with version control (e.g., Git) and CI/CD tools tailored to ML workflows.
  • Experience with MLOps.
  • Familiarity with Databricks is a plus.

 

Qualifications

Minimum Qualifications

  • · 5+ years of experience in machine learning, with a focus on NLP, generative AI, or agentic systems.
  • · Bachelor's degree in Computer Science, Engineering, Data Science, or a related field.

Additional Information

Press Ganey Associates LLC is an Equal Employment Opportunity/Affirmative Action employer and well committed to a diverse workforce. We do not discriminate against any employee or applicant for employment because of race, color, sex, age, national origin, religion, sexual orientation, gender identity, veteran status, and basis of disability or any other federal, state or local protected class. 

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 $200,000 . 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, and, 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.

Our privacy policy can be found here: https://www.pressganey.com/legal-privacy/ 

 

Average salary estimate

$165000 / YEARLY (est.)
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$130000K
$200000K

If an employer mentions a salary or salary range on their job, we display it as an "Employer Estimate". If a job has no salary data, Rise displays an estimate if available.

What You Should Know About Staff AI/ ML Engineer, Press Ganey

At Press Ganey, we're on the lookout for a talented Staff AI/ML Engineer to join our team in Chicago, IL! If you're passionate about natural language processing (NLP) and generative AI, then this is the perfect opportunity for you. In this pivotal role, you'll be responsible for designing and deploying cutting-edge large language models (LLMs) and generative AI solutions. Your creativity and technical expertise will help shape intelligent, interactive, and scalable systems that provide seamless user experiences. With your strong background in machine learning and deployment practices, you will ensure our ML systems power innovative conversational AI applications. As you collaborate with cross-functional teams, you'll lead the way in developing AI-driven features that truly enhance user interactions across chat interfaces. Your role involves mentoring junior engineers, optimizing machine learning models, and creating robust CI/CD pipelines for streamlined deployment. If you're ready to make a meaningful impact with your AI and ML skills while working in a culture that values learning and collaboration, Press Ganey is the place for you!

Frequently Asked Questions (FAQs) for Staff AI/ ML Engineer Role at Press Ganey
What are the responsibilities of a Staff AI/ML Engineer at Press Ganey?

As a Staff AI/ML Engineer at Press Ganey, your responsibilities include designing and deploying large language models (LLMs) and generative AI systems, optimizing performance and scalability, and integrating models with chat interfaces. You'll also monitor model performance, manage ML lifecycle processes, and collaborate with cross-functional teams to advance AI-driven features.

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What qualifications are required for the Staff AI/ML Engineer position at Press Ganey?

To qualify for the Staff AI/ML Engineer position at Press Ganey, candidates should have 5+ years of experience in machine learning, focusing on NLP or generative AI, along with a Bachelor's degree in Computer Science, Engineering, or a related field. Familiarity with ML frameworks, cloud platforms, and deployment practices is essential.

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What technical skills do you need to excel as a Staff AI/ML Engineer at Press Ganey?

The ideal candidate for the Staff AI/ML Engineer role at Press Ganey should possess strong programming skills in Python and be proficient in libraries like NumPy and Pandas. Experience with machine learning frameworks such as TensorFlow or PyTorch, plus knowledge of data pipelines and MLOps, will set you up for success in this position.

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What kind of projects will the Staff AI/ML Engineer work on at Press Ganey?

As a Staff AI/ML Engineer at Press Ganey, you'll work on innovative projects that involve designing and deploying conversational AI applications, enhancing user experiences through intelligent chat interfaces, and investigating agent-based systems. Your insights will drive our mission to improve human experiences in complex industries.

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How does Press Ganey support the professional development of Staff AI/ML Engineers?

Press Ganey is committed to continuous improvement and learning. As a Staff AI/ML Engineer, you'll have opportunities to mentor junior engineers, share best practices, and collaborate across teams, enriching your own development while fostering growth in those around you.

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Common Interview Questions for Staff AI/ ML Engineer
Can you describe your experience with deploying large language models?

In answering this question, provide specific examples of projects where you've deployed LLMs. Discuss the frameworks you used, any challenges you faced, and how you optimized these models for performance and scalability.

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What techniques do you use for monitoring the performance of machine learning models?

Be prepared to discuss various monitoring and evaluation techniques, such as using metrics like precision, recall, and F1 score. Mention any tools you have used to track model performance and how you implement feedback loops for continuous improvement.

Join Rise to see the full answer
How do you approach collaboration with cross-functional teams?

In your response, emphasize the importance of communication and understanding project goals. Share examples of successful collaborations where you worked with data scientists, product managers, or engineers to ensure alignment on objectives and deliverables.

Join Rise to see the full answer
What is your approach to mentoring junior engineers?

Discuss your philosophy on mentorship, such as fostering an open environment for questions and providing constructive feedback. Share any specific techniques or experiences where your mentorship directly led to a junior engineer's growth.

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Describe your experience with CI/CD in ML deployments.

Explain your familiarity with CI/CD pipelines specifically tailored for machine learning workflows. Discuss any tools you've utilized and how you have ensured efficiency and reliability in ML model deployment.

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What are some challenges you've faced while working with conversational AI applications?

When addressing this question, share specific challenges related to NLP, data quality, or user interaction design. Discuss the solutions you implemented and the lessons learned from those experiences.

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How do you stay updated on the latest trends in AI and machine learning?

Mention how you engage with the AI community through attending conferences, participating in online forums, or following influential researchers in the field. Share any forums or resources you utilize to stay informed.

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Can you explain your experience with cloud platforms like AWS or Azure?

Provide specific experiences where you've deployed ML models or applications on cloud platforms. Discuss the advantages of using these platforms and any challenges you overcame during the process.

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What is your preferred programming language for machine learning tasks, and why?

Though Python is often the go-to language, emphasize your proficiency in Python and why it's beneficial for ML tasks. You can also mention any other languages you are comfortable with and how they complement your Python skills.

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Can you share a success story from your previous projects involving NLP or generative AI?

Tell a compelling story from a past project where NLP or generative AI made a significant impact. Focus on your role in the project, the challenges faced, and the tangible outcomes achieved to illustrate your capabilities.

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Full-time, on-site
DATE POSTED
December 14, 2024

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