Sobre esta vaga de Software Engineer, ML Infrastructure, Content Retrieval Platform, Level 4 na Snap Inc.
Snap Inc is a technology company. We believe the camera presents the greatest opportunity to improve the way people live and communicate. Snap contributes to human progress by empowering people to express themselves, live in the moment, learn about the world, and have fun together.
The Company operates Snapchat, a visual messaging app that enhances your relationships with friends, family, and the world, and Specs Inc., a wholly-owned subsidiary dedicated to making computing more human, in addition to Bitmoji, Saturn, and other digital services.
Snap Engineering teams build fun and technically sophisticated products that reach hundreds of millions of Snapchatters around the world, every day. We’re deeply committed to the well-being of everyone in our global community, which is why our values are at the root of everything we do. We move fast, with precision, and always execute with privacy at the forefront.
We're looking for a Software Engineer to join the Content Retrieval Platform team, part of the Content ML organization. We develop and operates on large scale retrieval system for content recommendation, partner with Applied ML teams for architecture changes and model developments. We utilize Java/Go as the main indexing and serving languages with performant pieces in C++. We are building agentic repo starting from retrieval root and incubating L0.5, generative retrieval, and redesign of inference feature sourcing.
What you’ll do:
Design and optimize infrastructure systems for machine learning workloads at scale and drive reliability and efficiency improvements across Snapchat’s ML Infrastructure
Build and enhance feature generation and serving pipelines that power online inferencing and offline training data generation
Develop high-performance inference systems to ensure fast and efficient AI model serving
Build infrastructure to perform scalable ML model training, evaluation, and inference in the cloud
Develop high-performance inference systems to ensure fast and efficient AI model serving
Build comprehensive data management systems for scalable data collection, labeling, processing, and evaluation
Work closely with ML engineers to deploy cutting-edge models into production
Utilize AI tools and high velocity engineering workflows to design and ship scalable services while upholding rigorous standards for code correctness, security, and production ready quality code
Knowledge, Skills & Abilities:
Strong programming skills in Python, Java
Strong problem-solving skills with a focus on system performance, scalability, and efficiency
Good understanding of distributed systems and the infrastructure components of large-scale ML
Experience with big data processing frameworks such as Spark, Flink, or Ray
Ability to collaborate and work well with others
Proven track record of operating highly-available systems at significant scale
Ability to proactively learn new concepts and apply them at work
Adaptability in learning and applying evolving AI systems and tools to remain at the forefront of engineering trends and modern development practices
Minimum Qualifications:
Bachelor’s degree in a technical field such as computer science or equivalent experience
2+ years of post-Bachelor’s software development experience; or Master’s degree in a technical field + 1+ year of post-grad software development experience; or PhD in a relevant technical field
Experience building large scale production machine learning systems, distributed systems or big data processing
Preferred Qualifications:
Masters/PhD in a technical field such as computer science or equivalent industry experience
Experience working with ML Training platforms or optimizing AI model inference
Familiarity with ML frameworks such as TensorFlow, PyTorch, Caffe2, Spark ML, scikit-learn, or related frameworks
If you have a disability or special need that requires accommodation, please don’t be shy and provide us some information.
"Default Together" Policy at Snap: At Snap Inc. we believe that being together in person helps us build our culture faster, reinforce our values, and serve our community, customers and partners better through dynamic collaboration. To reflect this, we practice a “default together” approach and expect our team members to work in an office 4+ days per week.
At Snap, we believe that having a team of diverse backgrounds and voices working together will enable us to create innovative products that improve the way people live and communicate. Snap is proud to be an equal opportunity employer, and committed to providing employment opportunities regardless of race, religious creed, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, pregnancy, childbirth and breastfeeding, age, sexual orientation, military or veteran status, or any other protected classification, in accordance with applicable federal, state, and local laws. EOE, including disability/vets.
We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, where applicable).
Our Benefits: Snap Inc. is its own community, so we’ve got your back! We do our best to make sure you and your loved ones have everything you need to be happy and healthy, on your own terms. Our benefits are built around your needs and include paid parental leave, comprehensive medical coverage, emotional and mental health support programs, and compensation packages that let you share in Snap’s long-term success!
Compensation
In the United States, work locations are assigned a pay zone which determines the salary range for the position. The successful candidate’s starting pay will be determined based on job-related skills, experience, qualifications, work location, and market conditions. The starting pay may be negotiable within the salary range for the position. These pay zones may be modified in the future.
The base salary range for this position is $157,000-$235,000 annually.
