Join our retail team and help create an outstanding customer experience by understanding each customer's needs, recommending the right products and services, and guiding them through available purchase options. Key Responsibilities Deliver exceptional customer service by identifying customer needs and providing personalized recommendations. Build strong product knowledge and stay up to date with the latest products, services, and sales processes. Educate customers about available products, services, accessories, and purchasing options. Support teammates by sharing knowledge and contributing to a collaborative store environment. Maintain accuracy in transactions, inventory handling, and store procedures. Assist in different areas of the store whenever needed to ensure smooth daily operations. Create a welcoming and inclusive environment where every customer and colleague feels respected. Demonstrate professionalism, integrity, and a commitment to diversity and inclusion in all interactions. Minimum Qualifications Availability to work flexible schedules based on business needs, including evenings, weekends, and public holidays. Reliable attendance and punctuality. Excellent customer service and communication skills. Ability to work in accordance with company policies and local regulations. Preferred Qualifications The ideal candidate is able to: Demonstrate strong knowledge of consumer technology products and digital services. Recommend personalized solutions based on customer needs. Communicate clearly and confidently with customers from diverse backgrounds. Thrive in a fast-paced retail environment while assisting multiple customers. Collaborate effectively as part of a team and share responsibility for store success. Continuously learn new products, services, and industry trends. Handle sensitive or confidential information with professionalism and discretion. Adapt quickly to changing priorities and business needs. Compensation & Benefits We offer a competitive compensation package based on experience, qualifications, skills, and location. Eligible employees may receive: Competitive base salary Performance-based bonuses or commission opportunities (where applicable) Employee stock purchase and ownership programs Comprehensive medical, dental, and vision insurance Retirement savings plans Employee discounts on products and services Paid time off and company holidays Professional development and career growth opportunities Education assistance and tuition reimbursement for eligible programs Relocation assistance for qualifying positions Benefits and compensation may vary depending on location, employment status, and eligibility requirements. Equal Opportunity Employer We are committed to creating an inclusive workplace where everyone has the opportunity to succeed. Employment decisions are made based on qualifications, merit, and business needs without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected characteristic under applicable law. Accessibility We are dedicated to providing an accessible workplace and recruitment process for all applicants. Reasonable accommodations are available for qualified individuals throughout the hiring process and employment, in accordance with applicable laws.

Software Engineer, Machine Learning RecSys
Job description
Meta is seeking talented Machine Learning engineers to join our teams in building cutting-edge products, with the mission of connecting billions of people around the world. As a member of our team, you will have the opportunity to work on complex technical problems, build new features, and improve existing products across various platforms, including mobile devices and web applications. Our teams are constantly pushing the boundaries of user experience, and we're looking for engineers who can help us advance the way people connect globally. If you're interested in joining a team and working on exciting projects that have a significant impact, we encourage you to apply.
Software Engineer, Machine Learning RecSys Responsibilities
Collaborate with cross-functional teams (product, design, operations, infrastructure) to build innovative application experiences
Implement custom user interfaces using latest programming techniques and technologies
Develop reusable software components for interfacing with back-end platforms
Analyze and optimize code for quality, efficiency, and performance
Lead complex technical or product efforts and provide technical guidance to peers
Architect efficient and scalable systems that drive complex applications
Identify and resolve performance and scalability issues
Work on a variety of coding languages and technologies
Establish ownership of components, features, or systems with expert end-to-end understanding
Minimum Qualifications
3+ years of experience in software engineering or a relevant field. 2+ years of experience if you have a PhD
2+ years of experience in one or more of the following areas: machine learning, recommendation systems, artificial intelligence, or a related technical field
Experience with scripting languages such as Python, Javascript or Hack
Experience with developing machine learning models at scale from inception to business impact
Knowledge developing and debugging in C/C++ and Java, or experience with scripting languages such as Python, Perl, PHP, and/or shell scripts
Track record of setting technical direction for a team, driving consensus and successful cross-functional partnerships
Proven experience designing, building, or deploying recommendation systems (e.g., collaborative filtering, content-based, hybrid approaches, personalization at scale)
Experience building and shipping high quality work and achieving high reliability
Experience improving quality through thoughtful code reviews, appropriate testing, proper rollout, monitoring, and proactive changes
Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
Preferred Qualifications
Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
Publications in top-tier conferences/journals, patents, or open-source contributions in the recommendations or LLM space
Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
Experience with scripting languages such as Pytorch and TensorFlow
Exposure to architectural patterns of large scale software applications
Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
Hands-on experience working with large language models (LLMs), such as BERT, GPT, or similar architectures, including fine-tuning, integration, or application in production environments
Master's degree or PhD in Computer Science or another ML-related field
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Software Engineer, Machine Learning RecSys, United States
About Meta
Meta's mission is to build the future of human connection and the technology that makes it possible. Our technologies help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. To help create a safe and respectful online space, we encourage constructive conversations on this page. Please note the following: • Start with an open mind. Whether you agree or disagree, engage with empathy. • Comments violating our Community Standards will be removed or hidden. Please treat everybody with respect. • Keep it constructive. Use your interactions here to learn about and grow your understanding of others. • Our moderators are here to uphold these guidelines for the benefit of everyone, every day. • If you are seeking support for issues related to your Facebook account, please reference our Help Center (https://www.facebook.com/help) or Help Community (https://www.facebook.com/help/community). For a full listing of our jobs, visit https://www.metacareers.com
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