דרושים » תוכנה » Machine Learning Engineer

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.

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.

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.

Were looking for a Product Manager to lead LLM Infrastructure - a foundational role driving the development of systems that enable smarter, AI-powered decision making across the marketplace.

As the PM for LLM Infrastructure, youll shape the capabilities that turn unstructured data into structured, explainable, and actionable insights. Youll work closely with ML engineers, data scientists, and product leaders to design scalable tools and frameworks that support use cases across personalization, matching, search understanding, trust and safety, and more.

Your mission will be to build reliable and extensible LLM-based systems that serve as core building blocks for future-facing product innovation.

What am I going to do?
Define the product vision and roadmap for LLM infrastructure, aligning with long-term company strategy and cross-team needs.
Lead the development of scalable systems that extract meaning.
Structure from conversational and behavioral data.
Drive adoption of LLM capabilities across by building unified APIs, shared frameworks, and streamlined integration pipelines.
Partner with engineering, data science, and research teams to deliver high-quality infrastructure that powers AI-native product experiences.
Collaborate on system design and architecture decisions to ensure alignment between technical solutions and product scope.
Ensure reliability, scalability, explainability, and performance in all LLM-based systems.
Manage technical complexity and connect infrastructure efforts with clear business value.

We are looking for a Senior Data Engineer.
As a Senior Data Engineer, youll be more than just a coder - youll be the architect of our data ecosystem. Were looking for someone who can design scalable, future-proof data pipelines and connect the dots between DevOps, backend engineers, data scientists, and analysts.
Youll lead the design, build, and optimization of our data infrastructure, from real-time ingestion to supporting machine learning operations. Every choice you make will be data-driven and cost-conscious, ensuring efficiency and impact across the company.
Beyond engineering, youll be a strategic partner and problem-solver, sometimes diving into advanced analysis or data science tasks. Your work will directly shape how we deliver innovative solutions and support our growth at scale.
Responsibilities:
Design and Build Data Pipelines: Architect, build, and maintain our end-to-end data pipeline infrastructure to ensure it is scalable, reliable, and efficient.
Optimize Data Infrastructure: Manage and improve the performance and cost-effectiveness of our data systems, with a specific focus on optimizing pipelines and usage within our Snowflake data warehouse. This includes implementing FinOps best practices to monitor, analyze, and control our data-related cloud costs.
Enable Machine Learning Operations (MLOps): Develop the foundational infrastructure to streamline the deployment, management, and monitoring of our machine learning models.
Support Data Quality: Optimize ETL processes to handle large volumes of data while ensuring data quality and integrity across all our data sources.
Collaborate and Support: Work closely with data analysts and data scientists to support complex analysis, build robust data models, and contribute to the development of data governance policies.

We are scaling our AI team with mission-driven individuals eager to shape the future of mobility. As a Machine Learning Model Evaluation Engineer (Computer Vision), youll collaborate closely with our research team to design, build, and optimize data infrastructure and annotation workflows. You will be the focal point between the team and the annotation team, ensuring high-quality labeled data and efficient processes. Additionally, you will help optimize our algorithms, analyze performance metrics, and define optimal operating points to enhance model effectiveness. Your work will directly contribute to pushing the boundaries of Vision AI and advancing our cutting-edge projects.


RESPONSIBILITIES

Model Evaluation
Work closely with the research team to evaluate model performance and define optimal operating points using precision, recall, and other ML evaluation metrics.
Annotation Management
Be the focal point for annotation processes to ensure high-quality labeled data and streamlined workflows.
Database Management
Manage and maintain internal research databases for data-driven decision-making.
Cloud Infrastructure
Develop, maintain, and optimize cloud-based data infrastructure (AWS, GCP).
Benchmarking Framework
Build and maintain a benchmarking framework for continuous algorithm performance evaluation, including human-in-the-loop pipelines.
Dataset Curation
Curate training and testing datasets by querying databases and annotations, and by running data quality and auto-labelling tools.
Model Execution
Run algorithms and deep-learning models at scale.

Now were looking for an experienced Software Engineer to join our Data team. In this key role, you will develop our data platform, working on cloud-based microservices data pipelines. As we are building the company data platform, it has direct impact on our customers and also enabled many of the other groups in the organization. You will also be responsible for building microservices that need to work on big data scale (about 250K records/sec) in a law latency as part of a dynamic team.
Key Responsibilities:
End-to-end development of company massive data infrastructures and services.
Researching new technologies and adapting them for use in the companys product
Working closely with the product, DevOps, and security teams.

We are growing and are looking for a Senior Data Platform Engineer
who value personal and career growth, team-work, and winning!
What your day will look like:
Design, plan, and build all aspects of the platforms data, machine learning (ML) pipelines, and infrastructure.
Build and optimize an AWS-based Data Lake using best practices in cloud architecture, data partitioning, metadata management, and security to support enterprise-scale data operations.
Collaborate with engineers, data analysts, data scientists, and other stakeholders to understand data needs.
Solve challenging data integration problems, utilizing optimal ETL/ELT patterns, frameworks, query techniques, and sourcing from structured and unstructured data sources.
Lead end-to-end data projects from infrastructure design to production monitoring.

We are looking for a Staff Engineer.
What Youll Do:
Lead architecture and system design for critical components of the Developer Experience platform, ensuring scalability, resilience, and long-term maintainability.
Own end-to-end delivery of complex initiatives, from requirements gathering and design to implementation, rollout, and observability.
Design, implement, and maintain robust microservices supporting high-throughput and low-latency operations.
Define and uphold API design standards, including gateway configuration, versioning strategy, and long-term lifecycle management.
Build and optimize backend systems that enable developer-facing products such as SDKs, APIs, and webhooks.
Work with both relational and NoSQL databases to ensure data consistency, scalability, and performance.
Collaborate with cross-functional teams to design systems that meet operational and business requirements.
Research and implement cloud-native architectures to support growth and scalability.
Contribute to the creation of developer tools and standards that improve the usability of our APIs and SDKs.