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- Tasks: Lead the development of next-gen GenAI data systems and collaborate across teams.
- Company: Join Meta's innovative Superintelligence Labs and shape the future of AI.
- Benefits: Competitive salary, health benefits, remote work options, and growth opportunities.
- Why this job: Make a real impact on AI data platforms and drive cutting-edge technology.
- Qualifications: Experience in large-scale data infrastructure and strong technical leadership skills.
- Other info: Dynamic environment with mentorship opportunities and a focus on innovation.
The predicted salary is between 36000 - 60000 £ per year.
Meta’s MSL Data team is seeking a Software Engineer to lead the development of next-generation GenAI dataloading and storage systems. The ideal candidate will have experience in designing and scaling data infrastructure for AI/ML applications, with a focus on enabling efficient ingestion, transformation, data loading, and storage of massive datasets powering GenAI models. You will help drive technical direction, collaborate across functions, and shape the future of Meta’s AI data platforms.
Responsibilities
- Serve as a technical leader for the design and architecture of scalable dataloading and storage solutions for GenAI workloads within WS Airstore.
- Drive architectural decisions and set technical direction for high-throughput, low-latency data pipelines supporting large language and multimodal models.
- Develop and optimize data storage formats, access patterns, and caching strategies for GenAI use cases.
- Collaborate with research, infrastructure, and product teams to understand evolving GenAI data requirements and translate them into robust engineering solutions.
- Define use cases, develop methodologies, and establish benchmarks to evaluate and improve data infrastructure approaches.
- Mentor and provide technical guidance to engineers across the organization, fostering best practices in large-scale data engineering and distributed systems.
- Stay abreast of industry and Meta-wide trends in AI data infrastructure, storage technologies, and distributed computing.
Minimum Qualifications
- Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.
- Demonstrated experience as a technical leader in the design and architecture of large-scale data infrastructure or storage systems.
- Experience driving cross-functional engineering efforts and influencing architectural direction without direct management responsibilities.
- Track record of planning and executing technical roadmaps, with shorter-term projects laddering to long-term vision.
- Experience with distributed systems and large-scale data management.
- Experience mentoring and influencing engineers across organizations.
- Specialized experience in one or more of the following domains: Data infrastructure for AI/ML (GenAI, LLMs, multimodal models), Distributed storage systems, data lakes, or cloud object stores, High-performance data pipelines and ETL frameworks, or planet-scale database/data store.
- Proficiency in C/C++, Python, or similar languages for developing data infrastructure.
- Experience developing and optimizing data systems for AI/ML workloads.
Preferred Qualifications
- Familiarity with modern data storage formats (e.g., Parquet, ORC) and data lake architectures.
- Experience with Meta’s internal data infrastructure (Airstore, Scuba, Presto, etc.) is a plus.
Software Engineer - AI SysML, Meta Superintelligence Labs employer: Meta
Contact Detail:
Meta Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Software Engineer - AI SysML, Meta Superintelligence Labs
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at Meta or similar companies. A friendly chat can open doors and give you insights that job descriptions just can't.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repo showcasing your projects related to AI/ML data infrastructure. This is your chance to demonstrate your expertise beyond the CV.
✨Tip Number 3
Prepare for technical interviews by brushing up on your knowledge of data pipelines and storage systems. Practice coding challenges and system design questions to impress the interviewers.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in joining the team.
We think you need these skills to ace Software Engineer - AI SysML, Meta Superintelligence Labs
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Software Engineer role at Meta Superintelligence Labs. Highlight your experience with data infrastructure and AI/ML applications, as this will show us you’re a great fit for the position.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about AI and how your skills align with our mission at Meta. Don’t forget to mention any relevant projects or experiences that showcase your technical leadership.
Showcase Your Technical Skills: When filling out your application, be sure to highlight your proficiency in languages like C/C++ and Python. We want to see how you've developed and optimised data systems for AI/ML workloads, so don’t hold back!
Apply Through Our Website: We encourage you to apply through our website for the best chance of getting noticed. It’s super easy, and you’ll be able to keep track of your application status directly. Let’s get started on this journey together!
How to prepare for a job interview at Meta
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technologies mentioned in the job description, especially around data infrastructure for AI/ML. Brush up on your knowledge of distributed systems, data lakes, and high-performance data pipelines. Being able to discuss these topics confidently will show that you’re a strong candidate.
✨Showcase Your Leadership Skills
Since the role involves being a technical leader, prepare examples from your past experiences where you’ve influenced architectural decisions or led cross-functional teams. Highlight how you’ve mentored others and driven projects forward without direct management responsibilities.
✨Understand Meta’s Vision
Familiarise yourself with Meta’s AI initiatives and how they relate to data infrastructure. Knowing about their internal tools like Airstore and Scuba can give you an edge. This shows that you’re not just interested in the role but also in contributing to the company’s broader goals.
✨Prepare for Technical Questions
Expect to dive deep into technical discussions during your interview. Be ready to solve problems on the spot or discuss your approach to designing scalable data solutions. Practising coding challenges in C/C++ or Python can help you feel more prepared and confident.
