机器学习软件工程师

Design, train, and deploy machine learning models for large-scale production systems spanning ranking, recommendation, classification, or generative AI applications

Develop and maintain scalable ML pipelines covering data ingestion, feature engineering, model training, evaluation, and serving

Collaborate with data scientists, product managers, and infrastructure engineers to translate ML research into reliable, production-ready systems

Define and instrument metrics, dashboards, and alerting to monitor model health, detect regressions, and drive continuous improvement

Lead technical design of ML components and systems, evaluating trade-offs across model quality, latency, throughput, and infrastructure cost

Design and analyze experiments to validate model improvements, articulate assumptions, and make data-informed decisions that balance short-term gains with long-term product objectives

Identify and resolve performance bottlenecks in model training and inference through profiling, optimization, and architectural improvements

Proactively incorporate privacy, security, and responsible AI principles into ML system design and model development workflows

Mentor other engineers on ML best practices, contribute to team coding standards, and drive adoption of tooling and automation that improves development efficiency

Communicate technical decisions, trade-offs, and experimental outcomes clearly to cross-functional stakeholders across varying levels of technical background

Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience

6+ years of software engineering experience with a focus on machine learning systems, model development, or ML infrastructure

Experience developing and deploying machine learning models at scale, including feature engineering, model training, evaluation, and production serving

Experience designing and analyzing A/B experiments to validate ML model improvements and drive data-informed product decisions

Experience writing production-quality code in Python, C++, or a comparable language, with a track record of building maintainable, well-tested ML systems

Experience owning end-to-end delivery of ML projects, including technical design, cross-functional collaboration, and operational readiness

Experience with large-scale ML frameworks such as PyTorch or TensorFlow, and familiarity with distributed training and model serving infrastructure

Experience applying responsible and ethical AI practices, including bias evaluation, risk assessment, and model quality reviews

Experience in one or more specialized ML domains such as recommendation systems, natural language processing, computer vision, or generative AI

Demonstrated ability to integrate AI-assisted development tools to improve engineering efficiency and code quality

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

Meta builds technologies that help people connect, find communities, and grow businesses.

When Facebook launched in 2004, it changed the way people connect.

Apps like Messenger, Instagram and WhatsApp further empowered billions around the world.

Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology.

People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.

For those who live in or expect to work from California if hired for this position, please click here for additional information.

Individual compensation is determined by skills, qualifications, experience, and location.

Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable.

In addition to base compensation, Meta offers benefits.

Learn more about benefits at Meta.

Meta is proud to be an Equal Employment Opportunity employer.

We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics.

You may view our Equal Employment Opportunity notice here.

Meta is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures.

If you need assistance or an accommodation due to a disability, fill out the Accommodations request form.

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We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics.

You may view our Equal Employment Opportunity notice here.

Meta is committed to providing reasonable support (called accommodations) in our recruiting processes for candidates with disabilities, long term conditions, mental health conditions or sincerely held religious beliefs, or who are neurodivergent or require pregnancy-related support.

If you need assistance or an accommodation due to a disability, fill out the Accommodations request form Notice regarding automated employment decision tools in New York City Learn more about this here.

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Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.

6+ years of software engineering experience with a focus on machine learning systems, model development, or ML infrastructure.