דרושים » תוכנה » Deep Learning Engineer

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 are looking for an exceptional MLOps Team Lead to own, build, and scale the infrastructure and automation that powers state-of-the-art Large Language Models (LLMs) and AI systems.
This is a technical leadership role that blends hands-on engineering with strategic vision. You will define MLOps best practices, build high-performance ML infrastructure, and lead a world-class team working at the intersection of AI research and production-grade ML systems.
You will work closely with LLM Algorithm Researchers, ML Engineers, and Data Scientists to enable fast, scalable, and reliable ML workflows covering everything from distributed training to real-time inference optimization.
If you have deep technical expertise, thrive in high-scale AI environments, and want to lead the next generation of MLOps, we want to hear from you.

Realize your potential by joining the leading performance-driven advertising company!
As a Senior 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 Senior 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.

our company has been at the forefront of the deep learning revolution, pioneering innovations that have transformed the entire field. As the leading provider of GPUs and AI computing platforms, our cpmpany has empowered researchers and engineers worldwide to accelerate breakthroughs in artificial intelligence.
We seek a versatile Senior Software Engineer who is passionate about performance optimization and generative AI. Our team builds software solutions that enable efficient inference on the latest and greatest generative AI models. We tackle problems on all levels of the stackfrom server-level request batching to GPU kernel fusionand collaborate with teams across diverse disciplines to push our company's hardware to its full potential.
What youll be doing:
Cooperate with research teams to onboard new LLMs and VLMs into our company's opensource AI runtimes
Optimize inference workloads using sophisticated profiling and simulation tools
Build SOLID, extendable inference software systems, and refine robust APIs
Implement and debug low-level GPU code to harness the latest HW features
Own end-to-end inference acceleration features and work with teams around the world to deliver production-grade products.

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.

Were seeking an experienced AI/ML Platform Engineer to join our Foundations team, the group behind our next-generation GenAI platform powering innovation across the company and beyond. This team is building scalable, high-performance AI systems for both internal users and external customersdesigned to run seamlessly across cloud and on-premise environments using the latest advancements in hardware. In this role, youll lead efforts in distributed training, inference at large scale, resource optimization, and robust model lifecycle management using MLOps best practices. Your work will be critical to accelerating research, supporting production-grade AI infrastructure, and driving the development of our internal AI ecosystem.

Responsibilities
Architect and build scalable ML infrastructure for training and inference workloads across heterogeneous compute environments (on-premise and cloud).
Design and implement distributed systems to support model lifecycle management from data ingestion and preprocessing, to training orchestration and deployment.
Optimize performance and cost-efficiency of large-scale model training and serving pipelines using technologies like Ray, Kubernetes, Spark, and GPU schedulers.
Collaborate with AI researchers, data scientists, and product teams to understand their workflows and translate them into reusable platform services and APIs.
Drive adoption of best practices for CI/CD, observability, and reproducibility in ML systems.
Contribute to the long-term vision and technical roadmap of the ML platform, ensuring it evolves to meet the growing demands of AI across the company.

Were hiring a ML Engineer to accelerate AI-driven innovation across our companys B2B SaaS platform.
Youll be at the forefront of building intelligent systems that power core product experiences and automate internal operations, driving efficiency, speed, and scale across the organization. This is a high-impact, hands-on role in a fast-growing, AI-first company where machine learning is a foundational pillar, not a bolt-on feature. You'll partner with product, engineering, and operations teams to design and implement powerful ML and LLM-based solutions that make a measurable difference.
What You Will Do
Build Intelligent Systems: Design and develop ML/LLM-powered solutions that solve real-world challenges across our companys product and internal workflows.
Own Full Lifecycles: Take projects from concept all the way to production, including model training, evaluation, integration, and monitoring.
Leverage State-of-the-Art Tools: Work with leading frameworks like LangChain, Hugging Face, TensorFlow, and PyTorch to deliver cutting-edge functionality.
Collaborate Cross-Functionally: Partner with product managers, engineers, and stakeholders to embed AI capabilities into user-facing features and backend services.
Ship at Scale: Build and maintain scalable APIs and services, integrating best practices in CI/CD, observability, and cloud infrastructure.
Report with Impact: Share progress, challenges, and results clearly with technical and executive stakeholders.

We are looking for a senior DL researcher who is passionate about exploring complex data sets, drawing meaningful insights, and building high-quality real-time data products that complement our robust arsenal of industry-leading technologies.

As a senior DL researcher at Bigabid, you will be creating high-impact Machine Learning projects. In close coordination with stakeholders, you will play a major role in driving the data science roadmap and execution by providing the best solution to a game changer business problem.

Responsibilities

Deliver end-to-end ML products - including research, model development, prototyping, offline validation, implement in production, and online testing
Be a key player in the DS group - providing insights, best practices, novel techniques and research, and technical know-how to other data scientists
Develop ML solutions using advanced DL techniques to a diverse set of problems.
Analyze huge amounts of complex data to identify meaningful patterns and build useful features for machine learning models
Apply the scientific method to design, create, tune, and interpret machine learning models
Perform data manipulation, validation, and cross-domain research
Come up with new and creative research ideas and insights
Collaborate with our product and engineering teams to solve problems and identify trends and opportunities.

We are looking for an experienced and passionate Team Leader to lead our Deep Learning team. In this role, you will be responsible for leading the developing and delivering high-impact ML projects. You will work closely with stakeholders to identify and prioritize business problems, and develop and execute data science solutions.

Responsibilities

Lead and manage a team of DL researchers
Work with stakeholders to identify and prioritize business problems
Develop and execute DL solutions
Ensure that DL projects are delivered on time and within budget
Work closely with the Principal Researchers to plan the research roadmap
Collaborate with product and engineering teams to integrate ML solutions into our platform
Stay up-to-date with the latest advancements in ML research and development

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