דרושים » תוכנה » ML 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.

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.

We are looking for a Senior Backend Engineer to join our AI/ML team. In this role, youll work closely with data scientists to transform cutting-edge machine learning models into scalable, production-ready services. You will take ownership of designing, building, and maintaining the backend systems that power our AI-driven features.

This is a key position that bridges the gap between data science and production engineering, ensuring high performance, reliability, and maintainability of our ML-powered products.

Responsibilities:
Collaborate with data scientists to understand modeling outputs and convert them into deployable services.
Design and develop robust, scalable backend systems and microservices to support AI use cases.
Own the deployment and monitoring of ML models in production (with CI/CD, logging, observability).
Implement data processing pipelines in support of model training and inference.
Ensure software adheres to best practices in architecture, testing, and documentation.
Optimize model inference for latency, throughput, and resource efficiency.
Contribute to design decisions and technical strategy alongside AI and infrastructure leads.

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.

We are seeking for a talented AI/ML developer with strong focus on Python expertise and hands-on experience in AI/ML models to join our Data Science group. The Data Science group plays a pivotal role in driving the execution and delivery of advanced AI and modern Machine Learning solutions, that empower impactful projects to our target sectors.
Key Responsibilities:
Take part in all development aspects, from concept to production, of AI/ML models and LLM-based features (agents development)
Stay up to date with state-of-the-art research in the field of LLM and apply relevant advancements to improve our solutions
Mentor new team members and share your expertise to strengthen the teams collective knowledge.

Were seeking a visionary and technically hands-on AI Lead to join Alison.ai and take charge of driving innovation across our core AI systems. As the AI Lead, you'll guide the architecture and development of advanced machine learning models that power our video and creative analysis platform. You will collaborate cross-functionally with product managers, engineering, and business development teams to deliver cutting-edge features that push the boundaries of whats possible in creative performance analysis.

This is a high-impact role for someone who thrives at the intersection of machine learning, product strategy, and creativity.



Key Responsibilities

Lead the development, deployment, and optimization of machine learning models for video, image, and creative performance analysis.
Architect scalable AI/ML pipelines and infrastructure that support real-time and batch processing of multimedia data.
Guide research and experimentation initiativesidentify new technologies, modeling techniques, and opportunities for innovation.
Mentor and grow a team of machine learning engineers and data scientists as we scale.
Champion AI ethics, fairness, and explainability in our model development and deployment.
Stay ahead of industry trends in generative AI, computer vision, NLP, and Martech innovation, translating insights into competitive advantages.

We are looking for experienced, creative and impact-oriented Algorithm Developers to join our team!
As an Algorithm Developer you will be responsible for building state of the art algorithms powering LLMs and agentic frameworks. You will be part of a multi-disciplinary team that also includes engineers and product professionals, all working together to bring our products to life.
You will take part in the full life cycle of our development process, deeply understand the problem we are solving, come up with algorithmic approaches for solving these problems, devise strategies for collecting necessary training data, train and evaluate large language models and other machine learning models and also be in charge of deploying these solutions in production.
Role and Responsibilities:
Build the algorithms that power our various products
Develop production-grade solutions to challenging product-driven NLP tasks by combining language models, RL and classical ML/NLP.
Collaborate with product, sales and customer success teams to define success criteria and translate them into quantitative measures and objectives
Devise innovative strategies for collecting training and evaluation data
Train and evaluate models in realistic production scenarios
End-to-end ownership of the algorithmic components of our products, from design, through implementation and monitoring in production

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.

Shape the Future of Cybersecurity with Us Are you driven by curiosity, innovation, and the desire to turn cutting-edge research into real-world impact? Join Cynet, an established but rapidly growing cybersecurity startup, where you'll be part of a small, elite team building groundbreaking AI-powered security products from the ground up. Work alongside top minds in security research, R&D, product, and data engineering to drive innovation and create real value for global customers. This is your chance to contribute to a foundational mission - developing AI technology that proactively protects against todays most sophisticated cyber threats.

What will you do:
As a data Scientist at Cynet, youll play a central role in shaping our future technology. Youll: Own AI product creation end-to-end - from the initial concept through building prototypes to full-scale production. Drive innovation by developing and integrating ML and Generative AI solutions into Cynets core cybersecurity products: Endpoint, XDR, Network Detection, and Posture Management. Analyze massive volumes of security data to uncover hidden patterns, threats, and insights. Develop and fine-tune models with state-of-the-art optimization strategies and performance metrics. Contribute to and expand our AI infrastructure, including data pipelines, evaluation tools, and deployment frameworks. Conduct rigorous experimentation, explain and monitor the real-world performance of your models. Write production-ready code that makes it into our deployed AI systems.

We are looking for an experienced AI/ML Engineer to join our Applications team within our platform engineering group. In this role, you'll be responsible for designing, building, deploying, and maintaining production-grade AI systems and ML pipelines. You'll translate cutting-edge data science research into practical, scalable solutions, handling model deployment both in cloud environments and on-premises using GPUs and CUDA. Youll optimize and implement ML models, workflows, and AI agents to ensure high performance and reliability in production environments.

Responsibilities
Design, implement, and deploy ML models, AI-driven applications, AI workflows, and LLM-based agents into production.
Build, manage, and maintain robust ML pipelines and systems.
Deploy models on cloud and on-premises GPU servers.
Optimize system performance, including model inference, scalability, and resource utilization both on cloud and on-premises.
Develop and maintain services, APIs and integrate ML models into microservices-based applications.
Collaborate with cross-functional teams including data science, backend, DevOps, and platform teams.
Stay up to date with the latest developments in AI, machine learning, and related fields, focusing on LLMs, exploring how emerging technologies can be applied to improve products and services.