Software Engineer, Machine Learning

Remote from: USA
Annual salary: Undisclosed
Salary information is not provided for this position. Check our Salary Directory to estimate the average compensation for similar roles.
Department: Software Engineering
Employment type: Full Time,
Job posted: 16 May 2026
Apply before: 16 Jun 2026
Experience level: Senior
Views / Applies: 16 / 5

About company

About Meta

Giving people the power to build community and bring the world closer together

Online Media
2004

Actively Hiring

AI Summary

Meta is seeking a Software Engineer, Machine Learning to join their team in building cutting-edge products that connect billions of people. The role involves collaborating with cross-functional teams, implementing user interfaces, developing reusable software components, and optimizing code for performance. Candidates need a Bachelor's in CS or equivalent, 6+ years of programming experience (or 3+ with PhD), and experience with machine learning at scale. The position requires expertise in scripting languages like Python and PyTorch, as well as C++ and Java, and a focus on responsible AI practices. This is a senior-level role for those who can lead complex technical efforts and drive measurable impact.

Job Complexity

Easy Hard

AI Insight The role requires extensive experience (6+ years), expertise in multiple programming languages and machine learning frameworks, and the ability to lead complex technical efforts at a top-tier company like Meta, making it extremely challenging.

Salary Analysis

AI Insight The offered salary was not specified, but based on market data for a Software Engineer, Machine Learning at Meta (senior level), the median total compensation including stock and bonuses is approximately $200,000 per year. This is highly competitive and reflects the high demand for ML expertise.

Key Skills

Machine Learning PyTorch TensorFlow Python C++ Java Recommendation Systems Scalable Systems AI Ethics Software Engineering

Cover Letter Sample

Dear Hiring Manager,

I am writing to express my strong interest in the Software Engineer, Machine Learning position at Meta. With over 6 years of experience in developing and deploying machine learning models at scale, I am excited about the opportunity to contribute to Meta's mission of connecting the world.

In my previous role at [Company], I led the development of a recommendation system that improved user engagement by 30%. I have deep expertise in Python, PyTorch, and TensorFlow, and I am passionate about building scalable, efficient systems. I also prioritize responsible AI practices, ensuring bias mitigation and fairness in all models I develop.

I am particularly drawn to Meta's collaborative culture and the chance to work on products that impact billions. I am confident that my technical leadership and experience with AI tool integration will allow me to drive significant impact on your team.

Thank you for considering my application. I look forward to the possibility of discussing how I can contribute to Meta's success.

Sincerely,
[Your Name]

Possible Interview Questions

Describe a time you led a complex machine learning project from inception to business impact.

At my previous company, I led the development of a personalized recommendation engine for our e-commerce platform. I started by defining the problem and metrics, then built a team of three engineers. We used collaborative filtering and deep learning models, iterating based on A/B test results. The system increased click-through rates by 25% and revenue by 15% within three months.

How do you ensure the ethical use of AI in your models?

I adhere to responsible AI practices by conducting risk assessments early in the project, identifying potential biases in data, and implementing mitigation strategies like re-sampling or using fairness constraints. I also set up monitoring for model drift and regularly review outputs for quality and accuracy, involving diverse stakeholders in the review process.

Explain a time you optimized a machine learning model for performance and scalability.

I worked on a real-time fraud detection model that needed to process millions of transactions per second. I optimized the model by pruning unnecessary features, using model quantization, and implementing distributed inference with TensorFlow Serving. This reduced latency by 50% and allowed the system to handle 10x the traffic without additional hardware.

How do you stay current with emerging AI technologies?

I regularly read research papers on arXiv, attend conferences like NeurIPS, and participate in online courses. Recently, I completed a course on prompt engineering and have been experimenting with agent orchestration frameworks like LangChain. I also apply new techniques in side projects to build hands-on experience.

Describe your experience with integrating AI tools to optimize workflows.

At my last job, I integrated a code generation AI tool into our development pipeline to automate boilerplate code generation. This reduced development time by 20% and allowed engineers to focus on more complex tasks. I also set up monitoring to measure efficiency gains and ensure code quality was maintained.

Meta is seeking talented engineers to join our teams in building cutting-edge products that connect 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 of industry veterans and working on exciting projects that have a significant impact, we encourage you to apply.ResponsibilitiesCollaborate 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 understandingQualificationsBachelor’s degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience* Track record of setting technical direction for a team, driving consensus and successful cross-functional partnerships* 6+ years of programming experience in a relevant language or 3+ years of experience + PhD* Experience building maintainable and testable code bases, including API design and unit testing techniques Experience building and shipping high quality work and achieving high reliability* Experience improving quality through thoughtful code reviews, appropriate testing, proper rollout, monitoring, and proactive changes* Experience with developing machine learning models at scale from inception to business impact* Exposure to architectural patterns of large scale software applications* Experience with scripting languages such as PyTorch, TensorFlow, Python, JavaScript or Hack* 2+ years of experience in one or more of the following areas: machine learning, recommendation systems, pattern recognition, data mining, artificial intelligence, or a related technical field* Knowledge developing and debugging in C/C++ and Java* 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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