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Meta Software Engineer Jobs in Pennsylvania (NOW HIRING)

... Meta, Varjo, HTC, and others * Perform systems engineering activities to improve data flows and ... Software development proficiency (C#, Python, or Java) * Team-based software development ...

... the Director of Programming orimarily to create social media posts for event promotion and ... Meta Ads Manager) - proficiency with basic design and editing software (e.g. Canva) - must have a ...

... Ads, Meta Ads, Reddit Ads, and other relevant advertising channels * Trafficking advertising ... with software that spans engineering disciplines, industry sectors, and all phases of the ...

... Ads, Meta Ads, Reddit Ads, and other relevant advertising channels * Trafficking advertising ... with software that spans engineering disciplines, industry sectors, and all phases of the ...

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Meta Software Engineer information

See Pennsylvania salary details

$63.7K

$147.9K

$206K

How much do meta software engineer jobs pay per year?

As of Jul 26, 2026, the average yearly pay for meta software engineer in Pennsylvania is $147,878.00, according to ZipRecruiter salary data. Most workers in this role earn between $120,300.00 and $173,400.00 per year, depending on experience, location, and employer.

Is it hard to get hired at Meta?

Getting hired as a Meta Software Engineer can be competitive due to the company's rigorous interview process, which often includes multiple technical rounds, coding challenges, and behavioral assessments. Strong programming skills, experience with data structures and algorithms, and familiarity with tools like React or Python can improve chances of success.

How much do Meta engineers get paid?

Meta Software Engineers typically earn a base salary ranging from $120,000 to $200,000 annually, depending on experience, location, and level. Compensation often includes bonuses, stock options, and benefits, with higher salaries for senior roles and specialized skills in areas like AI and backend development.

How much do software engineers at Meta get paid?

Software engineers at Meta typically earn a base salary ranging from $120,000 to $200,000 annually, depending on experience, location, and level. Total compensation often includes bonuses, stock options, and other benefits, making the overall package competitive within the tech industry.

What are the key skills and qualifications needed to thrive in the Meta Software Engineer position, and why are they important?

To thrive as a Meta Software Engineer, you need strong programming skills in languages such as Python, C++, or Java, a deep understanding of computer science fundamentals, and typically a bachelor's degree in computer science or a related field. Experience with large-scale distributed systems, cloud computing platforms, and familiarity with development tools like Git and debugging frameworks are essential; certifications in cloud services or specialized technologies can be advantageous. Strong problem-solving abilities, collaboration, and effective communication skills distinguish top performers. These capabilities enable engineers to build high-quality, scalable products and seamlessly integrate within fast-paced, innovative technical teams.

What are some typical challenges faced by Meta Software Engineers, and how are they supported in overcoming them?

Meta Software Engineers often work on complex, large-scale systems that serve billions of users, presenting challenges such as optimizing performance, ensuring data privacy, and maintaining reliable uptime. The fast-paced environment requires engineers to stay current with rapidly evolving technologies and to frequently solve unique, open-ended problems. Meta provides robust support through collaborative teams, ongoing training, mentorship programs, and access to extensive internal knowledge resources. This environment helps engineers quickly ramp up, continuously improve their skills, and overcome technical and organizational hurdles efficiently.

What engineer makes $500,000 a year?

Senior software engineers at major tech companies, including roles like Meta Software Engineer, can earn $500,000 or more annually through base salary, bonuses, and stock options. Achieving this level typically requires extensive experience, advanced skills in software development, and often working in high-cost-of-living areas or at companies with competitive compensation packages.

What is a Meta Software Engineer job?

A Meta Software Engineer is responsible for designing, developing, and optimizing software products and infrastructure that support Meta's applications and services. They work on large-scale systems, collaborating with cross-functional teams to build innovative solutions in areas such as AI, virtual reality, and social networking. The role requires strong coding skills, problem-solving abilities, and expertise in languages like Python, Java, or C++.

What cities in Pennsylvania are hiring for Meta Software Engineer jobs? Cities in Pennsylvania with the most Meta Software Engineer job openings:
Infographic showing various Meta Software Engineer job openings in Pennsylvania as of July 2026, with employment types broken down into 91% Full Time, 6% Part Time, and 3% Contract. Highlights an 89% Physical, 4% Hybrid, and 7% Remote job distribution, with an average salary of $147,878 per year, or $71.1 per hour.
Software Developer / Engineer - Philadelphia, PA (Locals Only)

Software Developer / Engineer - Philadelphia, PA (Locals Only)

Apetan Consulting

Philadelphia, PA • On-site

Other

Posted 3 days ago


Job description

Software Developer / Engineer
Location: Philadelphia, PA 
Work Schedule: Hybrid 3 days on site, 2 remote


Position Overview

We are seeking a Software Developer / Engineer to help design and implement an on-premises Large Language Model (LLM) platform with Retrieval-Augmented Generation (RAG) capabilities. This role will focus on deploying open-source AI models, integrating vector databases, and building secure, enterprise-grade AI solutions in a private environment.

This is an excellent opportunity for a developer with hands-on experience in modern AI technologies who enjoys building scalable, high-performance systems.

Responsibilities

  • Deploy and optimize open-source large language models (LLMs) such as Meta Llama 3 and Mistral/Mixtral in on-premises or private environments.
  • Develop Python-based applications for LLM inference, prompt engineering, and model integration.
  • Optimize CPU-based model inference through quantization and performance tuning.
  • Design and implement Retrieval-Augmented Generation (RAG) (RAG) pipelines.
  • Configure and manage open-source vector databases such as Qdrant, Chroma, Milvus, or pgvector.
  • Generate and manage embeddings while implementing metadata filtering strategies.
  • Support enterprise security requirements, including air-gapped deployments, access controls, data privacy, and audit logging.
  • Produce technical documentation, deployment guidance, and knowledge transfer materials for internal teams.
  • Build a working prototype integrating an LLM, vector database, and RAG architecture.

Required Qualifications

  • Professional experience deploying open-source LLMs (e.g., Meta Llama 3, Mistral/Mixtral) in on-premises or private environments.
  • Strong Python development experience.
  • Hands-on experience with LLM inference, prompt engineering, and AI application integration.
  • Experience optimizing CPU-based inference through model quantization and performance tuning.
  • Experience with vector databases such as Qdrant, Chroma, Milvus, or pgvector.
  • Proven experience implementing Retrieval-Augmented Generation (RAG) solutions.
  • Understanding of enterprise security, data privacy, air-gapped environments, access controls, and audit logging.

Preferred Qualifications

  • Experience with LangChain or LlamaIndex.
  • Familiarity with Docker and Kubernetes.
  • Experience with inference frameworks such as vLLM, llama.cpp, or Hugging Face Transformers.
  • Experience with Rust, Go, or C++.
  • Previous experience working in enterprise or regulated environments.

Deliverables

  • Reference architecture and deployment guidance.
  • Working prototype integrating an LLM, vector database, and RAG solution.
  • Technical documentation and knowledge transfer to internal teams.