applinity

Software Engineer Leadership, Machine Learning RecSys

at Meta

Location

Bellevue, WA; Menlo Park, CA; New York, NY

Compensation

$219k–$301k USD

Type

full time

Posted

4 months ago

Remote

Yes

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Market range · company + function + seniority

$208k—$240k—$257k

p25 · target · p75 · n=330

Posted $301k · well above market

Posting health

Aging · 65
  • ·Open 146 days

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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 passionate individuals who can help us advance the way people connect globally. If you're interested in joining a world-class team and working on exciting projects that have a significant impact, we encourage you to apply.

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

  • Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
  • 4+ years of experience in software engineering, or a relevant field. 3+ years of experience if you have a PhD
  • 3+ years of experience in one or more of the following areas: machine learning, recommendation systems, artificial intelligence, or related technical field
  • 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
  • Experience with scripting languages such as Python, Javascript or Hack
  • Experience leading major initiatives successfully, Proven ability to set technical direction and influence product strategy
  • Proven experience designing, building, or deploying recommendation systems (e.g., collaborative filtering, content-based, hybrid approaches, personalization at scale)
  • 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
  • Experience building and shipping high quality work and achieving high reliability
  • Experienced in utilizing data and analysis to explain technical problems and providing detailed feedback and solutions
  • Experience demonstrating technical leadership working with teams, owning projects, defining and setting technical direction for projects Masters degree or PhD in Computer Science or a related technical field
  • Exposure to architectural patterns of large scale software applications
  • Experience with scripting languages such as Pytorch and TF
  • 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 adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
  • Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies

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