Staff Machine Learning Engineer

Description

At the company, we create software the world’s best brands use to deliver exceptional frontline experiences, build high-performing teams, and design products people love. Building a category takes grit, determination, and a disdain for convention—but most of all it requires close-knit, high-functioning teams with an unwavering dedication to serving our customers.

When you join one of our teams, you’ll be part of a nimble group that’s empowered to set aggressive goals and move fast to achieve them. Strategic risks are encouraged and complex problems are solved together, by passing the mic and iterating until the best solution comes to light. You won’t have to look to find growth opportunities—ready or not, they’ll find you. From retail to government to healthcare, we’re on a mission to bring humanity, connection, and empathy back to business.

Staff Machine Learning Engineer, Foundation - Seattle

Why We Have This Role

We are looking for an experienced Machine Learning Engineer to bring our Machine Learning and Artificial Intelligence R&D strategy to the next level. Our goal is to personalize the company experience using ML and AI features showcasing the company data as a core value proposition and competitive advantage. We aim to enhance our capabilities in developing and maintaining high-performance systems that can effectively handle large volumes of data and complex algorithms. This role will be pivotal in driving innovation and ensuring our machine learning initiatives support our mission of closing experience gaps across various domains.

How You’ll Find Success

Working in a supportive environment enables individual growth and the achievement of team goals.

Collaborate with your peers, prioritize features, and work with a sense of urgency to deliver value to our customers.

It will be crucial to stay on top of technology trends and educate leadership and stakeholders on trends, and North Star initiatives.

Analyze and enhance ML systems for better performance and efficiency.

Develop creative solutions to improve our ML infrastructure and scalability

How You'll Grow

Expand your expertise in machine learning and software engineering by working on cutting-edge technologies and large-scale systems.

Take on mentorship roles and collaborative projects to refine your leadership skills and guide junior team members.

Gain insights into different areas of the business by collaborating with various teams, enriching your understanding of how technology impacts overall company strategy.

Things You’ll Do

Design and develop robust AI architectures, frameworks, and algorithms that can support large-scale and complex enterprise SaaS AI solutions in alignment with business objectives.

Evaluate and select appropriate AI technologies, tools, and frameworks to achieve desired performance, accuracy, and scalability.

Collaborate across the company to guide the direction of machine learning at the company, spanning teams from research to production.

Communicate with a team of research scientists, product managers, and engineers and lead and document AI architectures, design decisions, and technical specifications for reference and knowledge sharing.

Work closely with research scientists and model engineering teams on developing, and deploying, ML systems in production. Develop a strategy for optimizing models and systems for performance, scalability, efficiency, and cost.

Offer technical supervision and direction to the ML platform teams and lead the creation of future ML platform for deploying and monitoring AI models in production settings while maintaining compliance with the best practices in machine learning and deep learning.

Conduct regular code reviews and provide technical guidance to team members.

Stay up-to-date with the latest advancements in AI technologies, frameworks, and algorithms, and identify opportunities for their application in the organization.

Requirements

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or a related field.
• Proven experience (7+ years) working as a Machine Learning Engineer, or related role.
• Proficiency in programming languages such as Python, Java, or C++, and popular AI libraries and frameworks (e.g. TensorFlow, PyTorch, Keras).
• Solid understanding of cloud computing platforms (e.g., AWS, Azure, Google Cloud) and experience deploying AI models on these platforms.
• Excellent problem-solving and analytical skills, with the ability to break down complex problems into actionable components.
• Strong communication and collaboration skills, with the ability to work effectively within cross-functional teams.
• Ability to stay updated with the latest AI technologies, frameworks, and platform advancements.
• Knowledge of deploying and optimizing LLMS with open-source frameworks like DeepSpeed, Accelerate, FasterTransformer, and Transformers-NeuronX libraries is a plus.
• Knowledge of ethical considerations and responsible AI practices is a plus.
• What You Should Know About This Team
• The Data Intelligence Center of Excellence (DICE) organization provides AI/ML research and development services for all product lines.
• This role will specifically be on the Data Intelligence Platform (DIP) team which works on building services and tools that enable ML and intelligence across multiple products.
• The DIP team's goal is to accelerate the company's ML adoption by enabling every engineering team to experiment, design, build, monitor, and troubleshoot ML-powered applications with a Platform that applies reusable components, patterns, and standards/best practices.
• Our Team’s Favorite Perks and Benefits
• Wellness Reimbursement for $300 per quarter for wellness activities, including gym memberships, spa massages, workout equipment, meditation apps, and much more.
• Amazing QGroup Communities; MOSAIQ, Green Team, the company Pride, Q&Able, the company Salute, and Women’s Leadership Development, which exist as places for support, allyship, and advocacy.
• The company Hybrid Work Model: Our hybrid work model is elegantly simple: we all gather in the office three days a week; Mondays and Thursdays, plus one day selected by your organizational leader. These purposeful in-person days in thoughtfully designed offices help us do our best work and harness the power of collaboration and innovation. For the rest of the week, work where you want, owning the integration of work and life. hybrid
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• Applicants in the United States of America have rights under Federal Employment Laws: Family & Medical Leave Act , Equal Opportunity Employment , Employee Polygraph Protection Act
• Not finding a role that’s the right fit for now? The company Insiders is the one-stop shop for all things the company Life. Sign up for exclusive access to content created with you in mind and get the scoop on what we have going on at the company - upcoming events, behind the scenes stories from the team, interview tips, hot jobs, and more. No spam - we promise! You'll hear from us two times a month max with fresh, totally tailored info - so be sure to stay connected as you explore your best role and company fit.
• AI
• For full-time positions , this pay range is for base per year; however, base pay offered within this range may vary depending on location, job-related knowledge, education, skills, and experience. A sign-on bonus and restricted stock units may be included in an employment offer. Full-time employees are eligible for medical, dental, vision, life and disability, 401(k) with match, paid time off, a wellness reimbursement, and mental health benefits. For a detailed look at our benefits, visit the company US Benefits .
• Washington State Base Annual Pay Transparency Range
• $213,000 - $259,000 USD