דרושים » מדעים מדוייקים » Senior Machine Learning Algorithm Engineer

Required Senior Algo Data Engineer
Realize your potential by joining the leading performance-driven advertising company!
As a Senior Algo Data 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 Algo Data 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 tech stack:
Java, Python, TensorFlow, Spark, Kafka, Cassandra, HDFS, vespa.ai, ElasticSearch, AirFlow, BigQuery, Google Cloud Platform, Kubernetes, Docker, git and Jenkins.

We are looking for a Senior ML Engineer.
As a Senior ML Engineer , you will lead the design, deployment, and maintenance of production-ready machine learning systems that power legal insights at scale. Youll work across disciplinesintegrating LLMs, building pipelines, and optimizing infrastructureto deliver real-world impact.
Youll gain full ownership over the systems you build, from selecting the tools and platforms to deploying services in production. Youll work closely with DevOps and Data Engineering to ship robust solutions that drive meaningful change in the world.
Responsibilities :
Design and implement production-grade ML systems, including APIs, batch jobs, and streaming pipelines using Databricks, MLflow, AWS/GCP.
Build and manage ML infrastructure, including data pipelines, model training, deployment, and monitoring.
Develop and maintain end-to-end ML/LLM pipelinesfrom data ingestion and labeling to synthetic data generation, model registry, and rollout.
Own and improve MLOps practices: automated testing, CI/CD, monitoring, alerting, and model governance.
Write clean, maintainable Python code and uphold best practices in engineering and documentation.
Collaborate with DevOps and Data Engineering teams to scale systems and improve performance.
Research and recommend the best tools, platforms, and practices to support ML at scale.

Required Staff Algo Data Engineer
Realize your potential by joining the leading performance-driven advertising company!
As a Staff Algo Data 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 Algo Data 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 tech stack:
Java, Python, TensorFlow, Spark, Kafka, Cassandra, HDFS, vespa.ai, ElasticSearch, AirFlow, BigQuery, Google Cloud Platform, Kubernetes, Docker, git and Jenkins.

We are seeking a Senior Data Scientist to lead the development of personalization models that power our AI agents. In this role, youll design and deploy intelligent systems that understand each travelers preferences, intent, and behaviortransforming complex user journeys into effortless, hyper-personalized experiences.This is a high-impact, cross-functional role working closely with product managers, engineers, designers, and the AI/LLM platform team to create deeply personalized, autonomous travel assistance that feels like magic (but is all math and modeling underneath).
What Youll Do:
Design and build machine learning models that power personalization across our agentic platform, including traveler profiles, flights & hotels recommendation engines, and behavioral prediction systems.
Develop algorithms that adapt and learn from user behavior over time, channels, and modalities (text, voice, action).
Collaborate with PMs, engineers, and conversational designers to integrate ML into real-time decision loops, conversational agents, and proactive UX flows.
Own experimentation pipelines and performance evaluation, AB tests, offline metrics, and production agent behavior.
Work hands-on with structured and unstructured data (e.g., travel history, chat logs, user feedback, booking behavior) to extract insights and drive model improvement.
Define and maintain robust MLops practices: monitoring, retraining, feature pipelines, and real-time inference.
Stay current with the latest in recommender systems, LLM integration, embeddings, retrieval augmentation, and agentic reasoning to continuously evolve our approach.

Were hiring a Machine Learning Engineer to accelerate AI-driven innovation across our B2B SaaS product and the broader organization.
This is a hands-on, end-to-end development role where you'll lead the implementation of ML/LLM-based solutions that boost operational efficiency and deliver exceptional product experiences. As an AI-First company, we embed AI across every department and workflowyou'll be at the heart of this transformation.
You will collaborate closely with product managers, engineers, and stakeholders to identify impactful AI opportunities, build state-of-the-art systems, and scale them across the organization.
What You Will Do:
AI-First Development: Design and implement POCs and production-ready ML/LLM solutions that address real-world business problems.
End-to-End Execution: Own projects from research through deployment, including model training, evaluation, integration, and monitoring.
Tool Evaluation: Stay current with state-of-the-art ML/LLM tools and frameworks (e.g., LangChain, Hugging Face Transformers, TensorFlow, PyTorch) and recommend their application.
Collaboration: Partner with engineering, product, and operations teams to embed AI into user-facing features and internal workflows.
System Integration: Build scalable microservices and APIs to deliver AI capabilities across the product.
Operationalization: Contribute to DevOps practices for CI/CD, observability, and ongoing optimization of AI models.
Strategic Reporting: Communicate progress and insights directly to senior management.

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.

Required Staff MLOps Engineer
Apply
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
Our tech stack:
Java, Python, TensorFlow, Spark, Kafka, Cassandra, HDFS, vespa.ai, ElasticSearch, AirFlow, BigQuery, Google Cloud Platform, Kubernetes, Docker, git and Jenkins.

Required Senior MLOps Engineer
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 tech stack:
Java, Python, TensorFlow, Spark, Kafka, Cassandra, HDFS, vespa.ai, ElasticSearch, AirFlow, BigQuery, Google Cloud Platform, Kubernetes, Docker, git and Jenkins.

We are seeking an exceptional Data Scientist to lead applied research in machine learning and drive the AI transformation . This pivotal role will shape the next generation of customer-facing products and internal tools, helping to redefine the trading experience through advanced AI.
Key Responsibilities:
Design and build end-to-end AI workflows including synthetic dataset generation, data preprocessing, model development, deployment, and agent orchestration.
Design and implement LLM (Large Language Model) evaluation frameworks to assess new AI models, techniques, and parameters.
Process and analyze large-scale structured and unstructured data from databases, APIs, and develop machine learning models for time series forecasting, regression, and classification tasks.
Design and implement enterprise-grade RAG systems using LLMs, vector databases, GraphRA, G, and intelligent agents.
Optimize AI-user interactions through advanced prompt engineering and retrieval strategies.
Translate cutting-edge AI research into practical, scalable tools for internal and customer-facing applications and collaborate with global and cross-functional R&D teams to drive innovation across product lines.
Apply MLOps and LLMOps best practices to ensure robust model training, deployment, and monitoring pipelines.

Required Senior Deep Learning Algorithm Developer
We are a global leader in autonomous vehicle (AV) technology. If youre an experienced deep learning developer driven by a passion to shape the future of mobility, join us to make AV a reality.
Object Perception team leverages cutting-edge multi-task deep learning to provide AVs with a rich understanding of vehicle behavior and interactions. Using vast amounts of video data, our algorithms capture intricate semantics and time-sensitive features, forming the backbone of AV scene understanding.
What will your job look like?
Design, develop, and optimize deep learning models that extract complex, dynamic insights from real-world scenes.
Collaborate across teams to solve key technical challenges and ensure model scalability.
Research and integrate the latest advancements in multi-task learning, temporal analysis, and AI architectures into our solutions.
Enhance and refine algorithmic performance through rigorous experimentation and innovation.
Develop primarily in Python, with occasional work in C++.
Work environment: Hybrid schedule: 4 days in-office (Tel Aviv or Jerusalem) and 1 day remote.