This position focuses on ensuring the quality and reliability of AI supercomputer hardware systems throughout their lifecycle—from concept to mass production.

Key Responsibilities:

• Develop and implement product quality strategies for next-generation AI hardware.
• Establish New Product Introduction (NPI) quality control processes, defining clear milestones and deliverables.
• Drive internal process improvements across multiple teams and functions.
• Design and execute comprehensive quality assurance plans, testing protocols, and validation processes.
• Utilize advanced data analytics and statistical methods for key quality metrics.
• Lead failure analysis, root cause identification, and corrective actions for system failures.
• Collaborate with suppliers to ensure sub-components meet quality standards and performance specifications.
• Own overall product quality process development of hardware products, including PCBs, PCBA, cabling, connectors, racks, power, and cooling components.
• Develop and manage overall product quality requirements, scope, schedules, and deliverables.
• Communicate effectively with cross-functional teams to ensure successful execution of programs.
• Utilize problem-solving skills to resolve issues and perform risk assessment and change management.
• Manage multiple projects simultaneously and monitor project progress.

Ideal Candidate Profile:

• Proven track record of leading complex projects from concept to production launch.
• Ability to work with cross-functional teams to ensure successful execution of programs.
• Experience in product quality engineering of high-performance computing systems.
• Familiarity with mechanical and electrical Design For Quality (DFQ), Excellence (DFX), Manufacturability (DFM), Test (DFT), and Design for Reliability (DFR).
• Experience driving development timelines for new platform introduction and managing internal review processes.
• Significant experience with multinational JDM/CM vendors.

Compensation:

• Annual Salary Range: $121,000—$181,000 USD

🧪 Research Software Engineer, Data Quality (Post-training)

Location: San Francisco, CA

Role Overview:

This role involves building data pipelines and conducting research explorations related to data quality, focusing on improving the datasets used to train ChatGPT models.

Key Responsibilities:

• Build systems and pipelines for continually processing and filtering large amounts of data.
• Train and run Machine Learning classifiers and embeddings on large amounts of data to sort and categorize by data quality and other attributes.
• Work with researchers on dataset creation and dataset preparation to kick off experiments.
• Lead other research initiatives involving data and data quality.

Ideal Candidate Profile:

• 3+ years of experience working with data-intensive applications or distributed systems.
• 6+ years of any software engineering experience (including data engineering).
• Highly skilled with Python.
• Ability to write, debug, and optimize Spark code.
• Understanding of data orchestration and automation tools (e.g., Airflow).
• Familiarity with Machine Learning, Deep Learning, and Large Language Models and related infrastructure (e.g., PyTorch).
• Bonus: Experience working with embeddings and vector libraries.

Compensation:

• Annual Salary Range: $295,000—$440,000 USD

🧪 QA Automation Engineer

Location: Dallas, TX

Role Overview:

This position involves automating software testing processes to ensure the quality and functionality of applications.

Key Responsibilities:

• Develop and maintain automated test scripts using Java and open-source technologies.
• Perform API testing (SOAP and Microservices).
• Utilize test frameworks like Junit and TestNG.
• Implement Behavior-Driven Development (BDD) practices using tools like Cucumber.
• Integrate testing processes into Continuous Integration and Continuous Deployment pipelines.
• Use version control tools like Git or SVN.
• Write complex SQL queries to validate data.
• Follow Scrum/Agile development methodologies.
• Utilize defect management and test management tools.

Ideal Candidate Profile:

• Bachelors or Masters in Computer Science or related fields.
• 1–3 years of experience in test automation.
• Strong programming skills in Java.
• Experience with test automation frameworks and tools.
• Familiarity with Agile methodologies.

Compensation:

• Position is part of a long-term project.

About company

Teleperformance is a global digital business services company. Our global scale and local presence allow us to be a force of good in supporting our communities, our clients, and the environment. We deliver the most advanced, digitally-powered business services to help the worlds best brands streamline their business in meaningful and sustainable ways.