Software Engineer - ML Systems (Technical Leadership)

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Job Overview

The Software Engineer - ML Systems (Technical Leadership) at Meta will be responsible for driving the design, development, and implementation of scalable machine learning systems. This role demands not only expertise in machine learning techniques but also leadership skills to guide cross-functional teams towards innovative solutions. The successful candidate will leverage their technical acumen to tackle complex problems, mentor junior engineers, and contribute to the overall strategy of integrating machine learning into Meta's product ecosystem.

Job Responsibilities

• Architect and develop cutting-edge machine learning systems optimized for performance and scalability.
• Lead technical discussions and provide direction on best practices for implementation of ML solutions.
• Collaborate with data scientists, researchers, and product managers to identify opportunities for ML integration in various projects.
• Oversee code quality through reviews, testing, and debugging to ensure robust and maintainable software.
• Mentor and guide junior engineers to foster their professional development and promote a culture of technical excellence.
• Stay informed about advancements in machine learning and artificial intelligence, and assess their potential applicability to Meta's products.
• Contribute to the open-source community to position Meta as a leader in the field of machine learning.

Qualifications

• Bachelor's or Master's degree in Computer Science, Electrical Engineering, Mathematics, or a related field.
• 5+ years of experience in software development and machine learning, with a strong focus on system design and architecture.
• Proficient in programming languages such as Python, Java, or C++.
• Deep understanding of machine learning algorithms, frameworks (e.g., TensorFlow, PyTorch), and data processing tools (e.g., Spark, Hadoop).
• Experience in leading projects and teams, with demonstrated leadership capabilities.
• Strong problem-solving skills and the ability to work effectively in a fast-paced environment.
• Excellent communication and collaboration skills, with a passion for mentoring and knowledge sharing.

Technologies & Tools

In this position, the Software Engineer will utilize a variety of technologies and tools including cloud platforms such as AWS or Google Cloud, machine learning libraries like TensorFlow and PyTorch, big data frameworks such as Apache Spark, and version control systems like Git. Familiarity with CI/CD pipelines and containerization technologies, such as Docker and Kubernetes, is also essential for deploying machine learning models effectively.

Ideal Candidates

The ideal candidate for this role is a highly motivated individual who thrives in a collaborative environment. They possess a passion for machine learning and its applications, coupled with a strong commitment to innovation and excellence. A successful candidate will demonstrate resilience, curiosity, and the ability to adapt to rapidly changing technologies and methodologies. Additionally, they should embody strong leadership qualities, inspiring and guiding their peers while fostering an inclusive team atmosphere.