Staff Machine Learning Engineer
About The Position
Qualtrics is seeking an experienced Machine Learning Engineer to advance its machine learning and artificial intelligence research and development strategy. The role will help personalize the Qualtrics experience through ML and AI features that make Qualtrics data a core value proposition, while developing and maintaining high-performance systems capable of handling large volumes of data and complex algorithms. The position supports the company’s mission of closing experience gaps across domains. The engineer will design and develop AI architectures, frameworks, and algorithms for large-scale enterprise SaaS solutions; evaluate technologies and tools; and guide machine learning direction across teams from research through production. They will work with research scientists, product managers, engineers, and model engineering teams to develop and deploy production ML systems, optimize models and systems for performance, scalability, efficiency, and cost, and direct the development of the ML platform used to deploy and monitor models. This position is on Qualtrics’ Data Intelligence Platform team within the Data Intelligence Center of Excellence. The team builds services and tools that enable ML across multiple products and helps engineering teams experiment, design, build, monitor, and troubleshoot ML-powered applications using reusable components and standards. The role also includes documenting technical decisions, conducting code reviews, providing guidance and technical supervision, and keeping current with AI advances.
Requirements
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, or a related field.
- At least 7 years of experience as a Machine Learning Engineer or in a related role.
- Proficiency in Python, Java, or C++, and AI libraries and frameworks such as TensorFlow, PyTorch, or Keras.
- Solid understanding of cloud computing platforms such as AWS, Azure, or Google Cloud, and experience deploying AI models on those platforms.
- Strong problem-solving and analytical skills, including the ability to break complex problems into actionable components.
- Strong communication and collaboration skills and ability to work effectively in cross-functional teams.
- Ability to stay updated on AI technologies, frameworks, and platform advancements.
Nice To Haves
- Knowledge of deploying and optimizing LLMs with open-source frameworks such as DeepSpeed, Accelerate, FasterTransformer, and Transformers-NeuronX.
- Knowledge of ethical considerations and responsible AI practices.
Responsibilities
- Design and develop robust AI architectures, frameworks, and algorithms for large-scale, complex enterprise SaaS solutions aligned with business objectives.
- Evaluate and select AI technologies, tools, and frameworks to meet performance, accuracy, and scalability needs.
- Collaborate across the company to guide the direction of machine learning at Qualtrics, from research through production.
- Communicate with research scientists, product managers, and engineers, and lead and document AI architectures, design decisions, and technical specifications.
- Work with research scientists and model engineering teams to develop and deploy ML systems in production.
- Develop strategies to optimize models and systems for performance, scalability, efficiency, and cost.
- Provide technical supervision and direction to ML platform teams and lead creation of the platform for deploying and monitoring production AI models.
- Maintain compliance with machine learning and deep learning best practices.
- Conduct code reviews and provide technical guidance to team members.
- Stay current on AI technologies, frameworks, and algorithms and identify opportunities for their application.
- Analyze and enhance ML systems for performance and efficiency, and develop solutions to improve ML infrastructure and scalability.
- Collaborate with peers, prioritize features, and deliver customer value.
Benefits
- Wellness reimbursement of $300 per quarter for wellness activities.
- QGroup communities for support, allyship, and advocacy.
- Hybrid work model with three office days each week and flexibility to work elsewhere for the rest of the week.
- Medical, dental, vision, life, and disability coverage for full-time employees.
- 401(k) with match.
- Paid time off.
- Mental health benefits.
- A sign-on bonus and restricted stock units may be included in an employment offer.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
