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Software Engineer, ML Infrastructure, Content Signal & Training Data Infrastructure, Level 5 Job Opening In Los Angeles – Now Hiring Snap Inc.

Software Engineer, ML Infrastructure, Content Signal & Training Data Infrastructure, Level 5

    United States Jobs Expertini Expertini United States Jobs Los Angeles Computer Occupations Software Engineer, Ml Infrastructure, Content Signal & Training Data Infrastructure, Level 5

Job description

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’s three core products are , a visual messaging app that enhances your relationships with friends, family, and the world; , an augmented reality platform that powers AR across Snapchat and other services; and its AR glasses, .

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 are at the root of everything we do.

We move fast, with precision, and always execute with privacy at the forefront.

You’ll play a critical role in scaling our Content Signal & Training Data infrastructure, developing new signals for ranking and retrieval, optimizing training data pipelines, and driving innovations that make Snapchat’s ranking and recommendation systems more reliable, efficient, and impactful.

We’re looking for a Software Engineer, Content Signal & Training Data Infrastructure to join Snap Inc!

What you’ll do:

  • Design and optimize systems for large-scale signal generation, indexing, serving, and applications
    Build and maintain content feature lifecycle management, including generation, storage, sourcing, monitoring, and deprecation of unused features

  • Simplify the content feature development process by collaborating with ML data platform teams and improving tooling for generation, storage, and sourcing

  • Optimize and monitor signal pipelines for reliability, latency, and scalability

  • Develop infrastructure for training data pipelines, including logjoin optimization, streaming logjoin, data sampling, data shuffling, and window tuning

  • Build and maintain training data for new applications and ranking models, including experiments on long-term objectives such as user retention and creator affinity

  • Collaborate with ML engineers to improve training workflows (feature engineering, preprocessing, model iterations, evaluation, and inference)

  • Build training data monitoring and analysis tools with Bento and data infra teams, including SQL-based analysis, feature importance, discrepancy detection, and anomaly detection

  • Knowledge, Skills & Abilities:

  • Strong programming skills in Python, Java, Scala, or C++
    Strong problem-solving skills with a focus on system performance, data quality, and scalability

  • Deep understanding of distributed systems, data pipelines, and ML infrastructure

  • Experience with big data processing frameworks such as Spark, Flink, Dataflow, or Ray

  • Familiarity with feature engineering, signal pipelines, and model training workflows
    Proven track record of operating highly available and reliable infrastructure at scale

  • Ability to proactively learn new concepts and apply them in a fast-paced environment

  • Strong collaboration skills with ML engineers, data scientists, and infra teams

  • Minimum Qualifications:

  • Bachelor’s degree in a technical field such as computer science or equivalent experience

  • 6+ years of post-Bachelor’s software development experience; or Master’s degree in a technical field + 5+ years of post-grad software development experience; or PhD in a relevant technical field + 2+ years of post-grad software development experience

  • Experience building large-scale data or ML production systems, distributed systems, or big data processing

  • Preferred Qualifications:

  • Masters/PhD in a technical field such as computer science or equivalent industry experience

  • Experience with feature platforms, logjoin optimization, and training data systems

  • Familiarity with ML frameworks such as TensorFlow, PyTorch, or Spark ML

  • Experience with signal pipelines, feature registries, retrieval systems, and data quality monitoring

  • Hands-on experience with Snap’s internal tech stacks such as Robusta, Hashi, Dataflow, Feature Registry, Mixer, Retrieval Service, logjoin, and dcoll

  • If you have a disability or special need that requires accommodation, please don’t be shy and provide us some .

    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).

    : 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 $209,000-$313,000 annually.

    :

    The base salary range for this position is $199,000-$297,000 annually.

    :

    The base salary range for this position is $178,000-$266,000 annually.

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

    Required Skill Profession

    Computer Occupations


    • Job Details

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    The Work Culture

    An organization's rules and standards set how people should be treated in the office and how different situations should be handled. The work culture at Snap Inc. adheres to the cultural norms as outlined by Expertini.

    The fundamental ethical values are:

    1. Independence

    2. Loyalty

    3. Impartiapty

    4. Integrity

    5. Accountabipty

    6. Respect for human rights

    7. Obeying United States laws and regulations

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    The average salary range for a varies, but the pay scale is rated "Standard" in Los Angeles. Salary levels may vary depending on your industry, experience, and skills. It's essential to research and negotiate effectively. We advise reading the full job specification before proceeding with the application to understand the salary package.

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    Interview Tips for Software Engineer, ML Infrastructure, Content Signal & Training Data Infrastructure, Level 5 Job Success

    Snap Inc. interview tips for Software Engineer, ML Infrastructure, Content Signal & Training Data Infrastructure, Level 5

    Here are some tips to help you prepare for and ace your Software Engineer, ML Infrastructure, Content Signal & Training Data Infrastructure, Level 5 job interview:

    Before the Interview:

    Research: Learn about the Snap Inc.'s mission, values, products, and the specific job requirements and get further information about

    Other Openings

    Practice: Prepare answers to common interview questions and rehearse using the STAR method (Situation, Task, Action, Result) to showcase your skills and experiences.

    Dress Professionally: Choose attire appropriate for the company culture.

    Prepare Questions: Show your interest by having thoughtful questions for the interviewer.

    Plan Your Commute: Allow ample time to arrive on time and avoid feeling rushed.

    During the Interview:

    Be Punctual: Arrive on time to demonstrate professionalism and respect.

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    Follow Up: Send a thank-you email to the interviewer within 24 hours.

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    Be Honest: Don't exaggerate your skills or experience.

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    Body Language: Maintain good posture, avoid fidgeting, and make eye contact.

    Turn Off Phone: Avoid distractions during the interview.

    Final Thought:

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