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Meta Software Engineer Jobs in Boston, MA (NOW HIRING)

Metalenz

Senior Optical Metrology Engineer

Boston, MA · On-site

$120 - $160/hr

Communicate results and conclusions to design team, fabrication team, software team and senior ... meta-optics and enable the next generation of 3D sensing in consumer electronics, automotive and ...

Intentsify LLC

Audience Manager

Westwood, MA · On-site

Partner closely with the product management, data engineering, and software engineering teams to ... Familiarity with discussing data concepts, understanding the relationships between data, meta-data ...

Metalenz, Inc

Senior Optical Metrology Engineer

Boston, MA · On-site

$110K - $170K/yr

Communicate results and conclusions to design team, fabrication team, software team and senior ... The Company Metalenz is a growing, venture-backed start-up that is the first to commercialize meta ...

Psi

Member of Technical Staff, Infrastructure

Boston, MA · On-site

$180 - $260/hr

Overview Physical Superintelligence is a startup with roots at Google, NVIDIA, Harvard, Meta, MIT ... software engineering. Our mission is to discover and commercialize transformative physics ...

INTERNATIONAL HIGHLIGHT LLC

Web Designer

Boston, MA · Remote

$18 - $22/hr

Meta titles and descriptions * Internal linking * Keyword optimization * Image alt text ... Collaborate with developers, designers, content teams, and management to communicate findings and ...

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Meta Software Engineer information

See Boston, MA salary details

$69K

$160.3K

$223.2K

How much do meta software engineer jobs pay per year?

As of Sep 6, 2026, the average yearly pay for meta software engineer in Boston, MA is $160,261.00, according to ZipRecruiter salary data. Most workers in this role earn between $130,400.00 and $187,900.00 per year, depending on experience, location, and employer.

What is a Meta software engineer?

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 skills and qualifications are needed to be a Meta software engineer?

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 challenges do Meta software engineers face and how are they supported?

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.

Is it hard to get a software engineer job at Meta?

Securing a software engineer position at Meta is competitive, often requiring strong technical skills, relevant experience, and proficiency in programming languages like Python or C++. Candidates typically go through multiple interview rounds assessing coding, system design, and problem-solving abilities. Having a solid portfolio, relevant internships, and knowledge of tools like React or GraphQL can improve chances.

What are popular job titles related to Meta Software Engineer jobs in Boston, MA?

For Meta Software Engineer jobs in Boston, MA, the most frequently searched job titles are:

What job categories do people searching Meta Software Engineer jobs in Boston, MA look for?

The top searched job categories for Meta Software Engineer jobs in Boston, MA are:

Meta Software Engineer jobs near you
Infographic showing various Meta Software Engineer job openings in Boston, MA as of August 2026, with employment types broken down into 87% Full Time, 9% Part Time, and 4% Contract. Highlights an 89% Physical, 3% Hybrid, and 8% Remote job distribution, with an average salary of $160,261 per year, or $77 per hour.

Member of Technical Staff, ML Engineer

Physical Superintelligence

Boston, MA • On-site

$140 - $210/hr

Other

Re-posted 4 days ago

Job description

Overview

Physical Superintelligence is a startup with roots at Google, NVIDIA, Harvard, Meta, MIT, Oxford, Johns Hopkins, Cambridge, and the Perimeter Institute building AI systems to discover new physics at scale.

Our mission is to discover and commercialize transformative physics breakthroughs at scale with artificial superintelligence, safely, verifiably, and for broad public benefit.

The last century's golden age of physics gave us transistors, lasers, and nuclear energy. We believe artificial superintelligence will unlock the next one. We're creating the infrastructure to industrialize scientific discovery and usher in this new era.

We have one product: new physics, at scale.

We are seeking a Member of Technical Staff, ML Engineer to build and run the training and inference systems that turn Core AI's research into things that work at scale, and that the rest of Engineering can build on.

Role and Responsibilities

  • Own the training and inference infrastructure that Core AI depends on: distributed training jobs, GPU scheduling, and model-serving systems (vLLM, SGLang, or comparable) for both proprietary models and self-hosted inference.

  • Build the tools and abstractions AI researchers use to launch training runs, iterate on inference providers, and route workloads across models, so a researcher's time goes into the science instead of the plumbing.

  • Partner with Engineering on the shared platform: capacity planning, observability, and reliability for GPU and inference infrastructure, so training and serving hold up to the same production bar as everything else we ship.

  • Debug and harden the training and inference stack under real load. Egress failures, stalled retries, and routing edge cases are your problem to close, not someone else's ticket.

  • Stay hands-on. You write the code, not just the design doc, and you are the first call when a training job stalls or an inference path breaks.

What We're Looking For

  • Three or more years building and operating ML training or inference infrastructure in production, at a company that trains or serves models at meaningful scale.

  • Hands-on experience with distributed training (multi-GPU or multi-node, using PyTorch, Ray, or comparable) and model-serving systems (vLLM, SGLang, Triton, or comparable).

  • Strong software engineering fundamentals. You can build a service that other engineers and researchers depend on every day, not a script that worked once.

  • Enough ML fluency to work productively with AI researchers: you understand training loops, reward signals, and inference-time behavior well enough to debug them, even without designing the algorithms yourself.

Nice to Have

  • Experience building internal platform tools such as training-as-a-service APIs, inference gateways, or job schedulers.

  • Background in GPU infrastructure, CUDA, or performance engineering for ML workloads.

  • Experience with cloud infrastructure (GCP, AWS) and infrastructure as code (Terraform or comparable).

  • Prior work embedded alongside a research team, turning research code into production systems.

How We Work

We hold a high technical bar and give people full ownership of their work, from spec to ship to on-call. We write contracts before logic, test against real systems instead of mocks, and favor simple designs that ship over clever ones that do not. Our development process is AI-native: we work with agentic coding tools daily, write specs that are legible to humans and agents alike, and lead with leverage.

Location and Compensation

This role is based in Boston. We will consider remote candidates on a case-by-case basis. We offer competitive compensation including salary, benefits, and meaningful early-stage equity. We evaluate on technical breadth, systems thinking, ML infrastructure depth, and shipping velocity. We are an equal opportunity employer and value diverse perspectives in building platforms for AI-driven discovery.

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