דרושים » אלגוריתמים » Machine Learning Engineer בסטארט-אפ בתחום ה-Security

SuperSonic by Unity is seeking a highly skilled Senior Machine Learning Engineer to join our dynamic Data Department. In this role, you'll work with petabyte-scale data to design, develop, and deploy state-of-the-art machine learning pipelines and systems. You'll build robust ML infrastructure using AWS services and orchestrate processes with Apache Airflow. If you're a passionate problem solver with a commitment to excellence and thrive in a collaborative environment, SuperSonic by Unity offers a unique opportunity to make a significant impact. Here, your expertise will drive innovation and help shape the future of machine learning, all while working on groundbreaking projects at a massive scale.

What you'll be doing
End-to-End Project Ownership: Take charge of feature design from concept through to deployment, ensuring robust, scalable solutions in a complex and dynamic environment.
Pipeline & Infrastructure Development: Architect and implement advanced machine learning pipelines that efficiently manage and process massive data volumes.
Collaboration & Teamwork: Embrace a team-first mindset"there is no I in team"actively supporting your peers while continuously learning and striving for excellence.
Problem Solving: Utilize your analytical skills to navigate technical challenges and deliver high-quality results on schedule, all while taking full ownership of your projects.

Meta is embarking on the most transformative change to its business and technology in company history, and our Machine Learning Engineers are at the forefront of this evolution. By leading crucial projects and initiatives that have never been done before, you have an opportunity to help us advance the way people connect around the world.

The ideal candidate will have industry experience working on a range of recommendation, classification, and optimization problems. You will bring the ability to own the whole ML life cycle, define projects and drive excellence across teams. You will work alongside the worlds leading engineers and researchers to solve some of the most exciting and massive social data and prediction problems that exist on the web.
Software Engineer, Machine Learning Responsibilities
Play a critical role in setting the direction and goals for a sizable team, in terms of project impact, ML system design, and ML excellence
Adapt standard machine learning methods to best exploit modern parallel environments (e.g. distributed clusters, multicore SMP, and GPU)
Re-evaluate the tradeoffs of already shipped features/ML systems, and you are able to drive large efforts across multiple teams to reduce technical debt, designing from first principles when appropriate
Leading a team from a technical perspective to develop ML best practices and influence engineering culture
Be a go-to person to escalate the most complex online/production performance and evaluation issues, that require an in depth knowledge of how the machine learning system interacts with systems around it
Develop highly scalable classifiers and tools leveraging machine learning, data regression, and rules based models
Suggest, collect and synthesize requirements and create effective feature roadmap
Code deliverables in tandem with the engineering team

Aura from Unity, a cutting-edge large-scale mobile platform, is seeking a highly skilled and experienced Senior Machine Learning Engineer to join our dynamic AI team. The ideal candidate will have a strong background in machine learning, data engineering, and software engineering, and will be responsible for leading the design, development, and deployment of cutting-edge machine learning pipelines and systems.
What you'll be doing
System Design and Architecture: Develop and maintain robust, scalable, and efficient ML pipelines including data collection, preprocess, and analyze large datasets to facilitate model training, evaluation and monitoring.
Research and Innovation: Stay current with the latest advancements in machine learning and AI, and apply innovative techniques to improve model performance and application.
Mentorship and Leadership: Provide technical guidance and mentorship to junior engineers and data scientists, and lead project teams to successful completion.
Cross-Functional Collaboration: Work closely with data scientists, software engineers, architects and product managers to integrate machine learning solutions into production systems.