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    Machine Learning Engineer - New York, United States - Ultralytics

    Ultralytics
    Ultralytics New York, United States

    10 hours ago

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    Description

    Who We Are

    At Ultralytics, we commit to relentless innovation in the AI space and seek team members who resonate with our ambition to produce the world's best YOLO AI models. If you're obsessed with AI, eager to make an impact on the world and thrive in dynamic, high-intensity environments, we invite you to apply for a position on our team.

    Location and Legalities

    This full-time position is based in our office in New York, though hybrid-remote work is also available for this position. Applicants must possess legal US work status.

    What You'll Do

    As our lead MLOps Engineer, you will oversee the planning, execution, and management of MLOps across all Ultralytics GitHub repositories. Your role is crucial in ensuring the operational excellence of our machine learning pipelines. You will:

    • Set up and maintain GitHub Actions for CI/CD pipelines.
    • Streamline Docker deployment processes for different environments.
    • Handle the publication of packages to PyPI and Conda repositories.
    • Develop automated checks for broken links, spelling, grammar, and other documentation issues.
    • Manage version control and release cycles for various projects.
    • Design, implement, and oversee automated tests to ensure product quality.
    • Conduct thorough PR reviews, providing constructive feedback and ensuring best practices.
    • Reproduce, triage, and prioritize bug reports for timely fixes.
    • Collaborate closely with ML developers for feature expansions and the development of new models.

    Your strategic vision and technical expertise will be essential in supporting Ultralytics' mission of delivering top-tier machine learning tools and models to the community.

    Skills and Experience

    • 5+ years experience with git, GitHub and open-source.
    • 5+ years experience with Python.
    • Proven experience in MLOps, DevOps, or related field, with a track record of managing machine learning lifecycle.
    • Strong understanding of CI/CD systems, preferably with GitHub Actions.
    • Experience with Docker containerization and orchestration.
    • Familiarity with PyPI and Conda package management and deployment.
    • Ability to write and maintain scripts for build, deployment, maintenance, and related tasks.
    • Proficiency in testing and debugging with a focus on automation.
    • Excellent problem-solving skills and the ability to prioritize and manage multiple tasks.
    • Strong communication skills for collaborating with cross-functional teams and articulating technical concepts.

    Cultural Fit

    WARNING: At Ultralytics, the pace is relentless and the expectations high. Our environment demands dedication beyond typical work hours, with nights and weekends a common part of our rigorous schedule. We prioritize candidates who possess a deep-rooted commitment to AI innovation, a strong proficiency with YOLO models, and an unwavering resolve to thrive under pressure. This role is tailored for the extraordinary—those prepared to invest the utmost effort to propel our ambitious startup. If you're seeking a comfortable routine, look elsewhere. If you're seeking to be at the forefront of AI advancement and ready for the intensity it demands, let's talk.

    Compensation and Benefits

    • Salary: USD 75,000-95,000/yr, depending on experience and qualifications.
    • Time Off: 24 days paid vacation, your birthday off, plus local holidays.
    • Remote Options: Hybrid work available; required in-office presence twice a week.
    • Flexibility: Flexible working hours.
    • Tech: Engage with cutting-edge AI projects.
    • Team: Become part of a supportive and passionate team environment.

    If you're excited about redefining the possibilities of machine learning and making a significant impact through your work, Ultralytics is the perfect place for you.

    Come join us, and let's build something amazing together

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