Snap Inc. Logo

Snap Inc.

Software Engineer, ML Infrastructure, Level 4

Posted 51 Minutes Ago
Hybrid
Palo Alto, CA, USA
133K-235K Annually
Junior
Hybrid
Palo Alto, CA, USA
133K-235K Annually
Junior
Design, build, and optimize scalable ML infrastructure for training, evaluation, and high-performance inference. Develop feature generation/serving pipelines, data management and labeling systems, and collaborate with ML engineers to deploy production models while ensuring reliability, scalability, and production-quality code.
The summary above was generated by AI

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 ML Platform Experience team, part of the core ML Platform organization. We are an AI native team which builds the agentic user experience for building, managing, and operating foundational models at Snapchat. We utilize Python as the primary language with Java/Go as supporting languages, we build agents on ADK, langfuse, and frontier LLM models, and are responsible for many other foundational technology such as model lineage, model orchestration, model data quality, and more.

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.

Zone A (CA, WA, NYC):

The base salary range for this position is $157,000-$235,000 annually.


 

Zone B:

The base salary range for this position is $149,000-$223,000 annually.

Zone C:

The base salary range for this position is $133,000-$200,000 annually.

This position is eligible for equity in the form of RSUs.

Snap Inc. Palo Alto, California, USA Office

Palo Alto, CA, United States

Snap Inc. San Francisco, California, USA Office

Snap SF is nestled in SoMa, steps from the Moscone Center and a quick walk from Powell Street BART station.

Similar Jobs at Snap Inc.

16 Hours Ago
Hybrid
2 Locations
100K-176K Annually
Junior
100K-176K Annually
Junior
Artificial Intelligence • Cloud • Machine Learning • Mobile • Software • Virtual Reality • App development
Design, implement, and operate critical, highly-scalable backend services (identity, friend graph, persistence). Collaborate across teams, evaluate trade-offs, test and debug, and ensure availability, scalability, operational excellence, and cost management. Participate in incident response and deliver medium-sized features.
Top Skills: AWSC++GCPJavaKubernetesMemcacheNoSQLPythonRedis
19 Hours Ago
Remote or Hybrid
Palo Alto, CA, USA
133K-235K Annually
Junior
133K-235K Annually
Junior
Artificial Intelligence • Cloud • Machine Learning • Mobile • Software • Virtual Reality • App development
Design, implement, and operate critical, highly scalable backend services (identity, friend graph, persistence). Collaborate across teams, build and test distributed systems, ensure availability and operational excellence, use AI tools to accelerate development, and participate in incident response and debugging.
Top Skills: Ai ToolsAWSC++Distributed SystemsGCPJavaKubernetesMemcacheMicroservicesNoSQLPythonRedis
Yesterday
Hybrid
2 Locations
178K-313K Annually
Senior level
178K-313K Annually
Senior level
Artificial Intelligence • Cloud • Machine Learning • Mobile • Software • Virtual Reality • App development
Define and lead Sponsored AR product strategy across priority advertiser verticals. Partner with engineering, design, data science, sales, and marketing to build, launch, and iterate AR advertising products. Translate market and customer insights into roadmaps, business cases, and success metrics; prioritize opportunities, run experiments, and influence executives to drive adoption and revenue.
Top Skills: AIAugmented RealityComputer VisionGenerative MediaLlmsMultimodal Models

What you need to know about the San Francisco Tech Scene

San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.

Key Facts About San Francisco Tech

  • Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Google, Apple, Salesforce, Meta
  • Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
  • Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
  • Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account