דרושים » הנדסה » Machine Learning Engineer

Realize your potential by joining the leading performance-driven advertising company!
As a Senior Machine Learning Engineer, youll play a vital role in turning algorithm prototypes into shippable products that will have a significant and immediate impact on the companys revenue
How youll make an impact:
As a Senior Machine Learning Engineer, youll bring value by:
Be responsible for the entire algorithmic lifecycle in the company: data analytics, prototyping of new ideas, implementing algorithms models in a production environment and then monitoring and maintaining them
Turn algorithm prototypes into shippable products that will have a significant and immediate impact on the companys revenue
Work on a daily basis with some of the hottest trends in todays job market: machine/deep learning, big data analytics/engineering and cloud computing
Apply your scientific knowledge and creativity to analyze large volumes of diverse data and develop algorithmic solutions and models to solve complex problems
Influence directly on the way billions of people discover the internet
Work on projects such as Internet Personalization, Content Feed, Real Time Bidding, Video Recommendations and much more.

We seek an experienced Machine Learning Software Engineer to join our ML Team.

In this role, you will develop efficient and scalable code to create and operate ML systems for our production and Infra environments

A day in the life and how youll make an impact:
Productization of algorithms - Optimized for large scale algo serving.
Code ML Infrastructure & Framework for Agile ML Lifecycle, MLOps, and CI/CD.
Continuously explore ways to improve our code and ML Infrastructure.
Collaborate with team members to define future technology and features.

We are seeking a Senior Data Engineer to own and scale data platform infrastructure.

Lead the architecture and implementation of high-throughput, low-latency data pipelines across teams.
Support cutting-edge GenAI and cybersecurity use cases.
Be part of the Data and AI Algorithms group.
Collaborate closely with AI/ML engineers, architects, development teams, and security researchers.
Ensure the availability, reliability, and agility of our data infrastructure.
Help define best practices for data modeling and orchestration at scale.

We are seeking a talented and experienced Machine Learning Engineer who will be responsible for designing and applying new machine learning techniques for computer vision applications.

Role and Responsibilities

Design, integrate, and evaluate new deep learning techniques/Models to improve the accuracy of the core software product
Develop techniques to clean/refine our dataset used for training
Help guide the workflow for collecting and annotating data by our team of data entry specialists
Design and implement algorithmic/Agent logic associated with Computer Vision Models.
Test performance/accuracy of model changes
Customize models via Neural Architecture Search to best fit the application
Implement training code in Python and PyTorch Framework 

Realize your potential by joining the leading performance-driven advertising company!
As a Staff MLOps Engineer on the Infra group, youll play a vital role in develop, enhance and maintain highly scalable Machine-Learning infrastructures and tools.
About Algo platform:
The objective of the algo platform group is to own the existing algo platform (including health, stability, productivity and enablement), to facilitate and be involved in new platform experimentation within the algo craft and lead the platformization of the parts which should graduate into production scale. This includes support of ongoing ML projects while ensuring smooth operations and infrastructure reliability, owning a full set of capabilities, design and planning, implementation and production care.
The group has deep ties with both the algo craft as well as the infra group. The group reports to the infra department and has a dotted line reporting to the algo craft leadership.
The group serves as the professional authority when it comes to ML engineering and ML ops, serves as a focal point in a multidisciplinary team of algorithm researchers, product managers, and engineers and works with the most senior talent within the algo craft in order to achieve ML excellence.
How youll make an impact:
As a Staff MLOps Engineer Engineer, youll bring value by:
Develop, enhance and maintain highly scalable Machine-Learning infrastructures and tools, including CI/CD, monitoring and alerting and more
Have end to end ownership: Design, develop, deploy, measure and maintain our machine learning platform, ensuring high availability, high scalability and efficient resource utilization
Identify and evaluate new technologies to improve performance, maintainability, and reliability of our machine learning systems
Work in tandem with the engineering-focused and algorithm-focused teams in order to improve our platform and optimize performance
Optimize machine learning systems to scale and utilize modern compute environments (e.g. distributed clusters, CPU and GPU) and continuously seek potential optimization opportunities.
Build and maintain tools for automation, deployment, monitoring, and operations.
Troubleshoot issues in our development, production and test environments
Influence directly on the way billions of people discover the internet.

We're looking for talented, versatile and highly independent Machine Learning Engineers to join our winning team. You will be in charge of end-to-end development and you'll have a massive impact on the product and the technical decisions made.
The ML Engineers are part of our infrastructure group, working closely with the exceptional research team, taking trained models and scaling them out to production.
Responsibilities:
Take ownership of the entire machine learning engineering lifecycle - from building scalable training and evaluation pipelines to deploying models in production, with robust monitoring and maintenance systems.
Help in creating scalable solutions by enabling us to continuously increase the accuracy of our algorithms across thousands of clinics.
Designing a secured large-scale system that is suitable for sensitive patient data.
Continue to enhancing our deep learning infrastructure to supports our AI models at scale, including CI/CD, automation, testing and monitoring.
Collaborate with the research, medical and product teams in implementing ML solutions to the digital health space.