דרושים » תוכנה » Experienced Software Engineer, Data Core

We are seeking a detail-oriented and collaborative Senior ML Engineer to help support and maintain our machine learning capabilities. This role is ideal for someone who enjoys working closely with production systems, ensuring reliability, scalability, and explainability of models while enabling research teams to deliver impact faster.



Responsibilities



Collaborate with cross-functional teams to ensure ML systems remain robust, explainable, and aligned with business needs.
Monitor and report on ML model performance, reliability, and explainability metrics.
Participate in model retraining procedures, implement automation and optimization of MLOps pipelines.
Extend and scale monitoring pipelines, including support for new features in development.
Investigate, troubleshoot, and resolve issues in production ML workflows (tiered support from initial triage to root-cause analysis with model owners).
Develop and maintain repositories for feature engineering, inference monitoring pipelines, and artifact monitoring tools.
Perform exploratory data analysis (EDA) on historical datasets to identify quality issues and maintain data health.
Implement and oversee production based adjusters across customer deployments.
Evaluate and track critical ML artifacts such as explainability files, coverage metrics, and alignment of features.
Support development and maintenance of internal tools (e.g., interfaces, registries, and feature monitoring frameworks).
Build and maintain static and temporal features, including seasonality, event-based, and price-related features.

we are looking for a Staff Software Engineer - Cloud Security.
Your Role:
Design, develop, and maintain complex, scalable, and high-performance systems with a focus on writing clean, efficient, and maintainable code.
Collaborate with cross-functional teams, including product managers and architects, to implement technical solutions aligned with business objectives.
Provide input on architectural design and participate in technical planning to ensure long-term maintainability and compliance with standards.
Identify and troubleshoot production issues, conducting root cause analysis and implementing fixes to ensure system reliability.
Contribute to code reviews and technical discussions, sharing knowledge and fostering a culture of collaboration and continuous improvement.

Were looking for a Senior Data Engineer to join our Research Engineering Team and play a pivotal role in shaping the data infrastructure that powers innovative solutions. In this role, youll design, build, and scale data pipelines and data warehouses from the ground up, creating the backbone for the worlds leading data classification engine. Youll collaborate closely with researchers and machine learning experts to enable the development of advanced models, ensuring a seamless flow of high-quality, reliable, and well-structured data. Your contributions will directly impact the scalability, performance, and precision of our platform, advancing our mission to protect critical data.

What Youll Do

Design and build scalable batch and streaming data pipelines that process complex datasets from diverse sources, enabling reliable and high-performance model training and inference.

Collaborate closely with researchers and data scientists to deliver high-quality, structured datasets that accelerate experimentation and model iteration.

Lead large-scale historical backfills and migration initiatives to ensure data consistency and integrity across evolving storage and compute platforms.

Optimize data workflows through advanced query tuning, indexing, partitioning, and cost optimization strategies to support efficient large-scale analytics.

Architect and maintain high-performance cloud-based data platforms using modern data stack components across AWS, GCP, or Azure.

Operate distributed data processing engines to handle massive volumes of structured and unstructured data.

Design and implement event-driven architectures using large-scale queue systems such as Kafka or SQS to ensure reliable and efficient data movement.

Develop automated monitoring and validation systems that guarantee uptime, schema compatibility, and pipeline reliability.

Deploy and manage data infrastructure in containerized, Kubernetes-based environments to support scalable and resilient services.

Were looking for a Data Engineer to join our Data Labs (DL) department, which specializes in professional services for our super-premium customers. This role will report to our DL (Datalabs) Data Science Team Manager in the R&D.

As part of this role, you will create and support a complex data model pipeline that helps analyze the petabytes of data we receive from various sources, and research and develop new features and capabilities for our product solutions

As a data engineer in the Datalabs team, you will work on the very core of the company. Part of your role will be to create processes that help turn raw data into usable metrics and leverage AI models and statistical algorithms to support out-of-the-box requests from customers who want custom data labs. The Datalabs departments business-oriented nature also means you will be supporting a team of analysts and data scientists who interact directly with customers. Together with them, you will translate the voice of these customers into best-in-class data labs.

So, what will you be doing all day?

Building and maintaining our big-data pipelines
Take a major part in designing and implementing complex high-scale systems using a large variety of technologies
Be part of a team with smart and motivated engineers, and data scientists, to collaborate on the planning, development, and maintenance of our products
Implement solutions in the AWS cloud environment, and work in Databricks with PySpark

We are looking for a Senior Software Engineer to join our Sensors Team and play a key role in the development of our Endpoint Sensor (Agent) platform. This is a hands-on senior position with strong technical ownership, focused on designing, building, and maintaining high-performance endpoint sensors across multiple operating systems.

In this role, you will work closely with sensor, analysis, and platform teams to ensure reliable, efficient, and scalable data collection in highly complex and demanding customer environments. The position requires deep systems knowledge, strong problem-solving skills, and the ability to influence technical direction through technical expertise.

RESPONSIBILITIES
Design, implement, and maintain endpoint sensors on Windows, macOS, and multiple Linux distributions, including installation processes and shared APIs.
Take technical ownership of key components within the endpoint sensor stack, ensuring high performance, reliability, and low resource footprint.
Collaborate with cross-functional engineering teams to define APIs, schemas, and data flows, ensuring data accuracy, availability, and correctness across the system.
Participate in architectural and design discussions, contributing to technical decisions and long-term system evolution.
Identify and implement improvements across the system, from core business logic to new data sources and monitoring capabilities.
Troubleshoot and resolve complex issues related to sensor deployment, behavior, and performance across different operating systems and environments.
Maintain high engineering standards, including code quality, testing, documentation, and maintainability, while working within an agile development process.

Were looking for a Big Data Engineer to develop and integrate systems that retrieve, process and analyze data from around the digital world, generating customer-facing data. This role will report to our Team Manager, R&D.

So, what will you be doing all day?

Your role as part of the R&D team means your daily responsibilities may include:

Design and implement complex high scale systems using a large variety of technologies.
You will work in a data research team alongside other data engineers, data scientists and data analysts. Together you will tackle complex data challenges and bring new solutions and algorithms to production.
Contribute and improve the existing infrastructure of code and data pipelines, constantly exploring new technologies and eliminating bottlenecks.
You will experiment with various technologies in the domain of Machine Learning and big data processing.
You will work on a monitoring infrastructure for our data pipelines to ensure smooth and reliable data ingestion and calculation.

we are looking for a Engineering Team Lead.
In this role, you will take an integral part in the creation of a new and innovative SaaS product.
If you are a talented software engineer that likes to solve complex problems and looking for your next challenge we want you to join our team!
What youll do: As the Team Leader , you will lead a talented team to design, implement, and deploy scalable data solutions for an innovative SaaS product. Youll be responsible for shaping the direction of a system that impacts millions of users worldwide. If you're an experienced manager with a strong technical background, ready to lead in a dynamic, fast-paced production environment, we want you on our team!
Responsibilities:
Collaborate effectively with cross-functional teams (Data Science, Security, etc.) to ensure alignment on business needs and security standards.
Manage the technical backlog, make critical decisions on product milestones, and ensure timely, secure, high-quality delivery and deployment.
Foster the growth of team members through mentorship, personal development opportunities, and the promotion of continuous improvement.
Identify, manage, and mitigate security risks across the data platform, maintaining high standards in all initiatives.
Define and implement methodologies to guarantee the performance, scalability, and quality of our data infrastructure.

At UVeye, we're on a mission to redefine vehicle safety and reliability on a global scale. Founded in 2016, we pioneered the world's first fully automated suite of AI-powered vehicle inspection systems, combining computer vision, machine learning, and generative AI.
With over $380M in funding and strategic partnerships with Toyota, Amazon, General Motors, JLR, Volvo, and Hertz, our technology is deployed across manufacturing plants, dealerships, wholesale auctions, fleets, and seaports worldwide. Named one of Fast Company's Most Innovative Companies of 2026, our 300+ global employees are solutions-oriented, accountable, and driven by one shared goal: making roads safer for everyone.
We are looking for an experienced Data Engineering Team Leader In this role, you will lead and strengthen our Data Team, drive innovation, and ensure the robustness of our data and analytics platforms.
?A day in the life and how you’ll make an impact:
* Drive the technical strategy and roadmap for the data engineering function, ensuring alignment with overall business objectives.
* Own the design, development, and evolution of scalable, high-performance data pipelines to enable diverse and growing business needs.
* Establish and enforce a strong data governance framework, including comprehensive data quality standards, monitoring, and security protocols, taking full accountability for data integrity and reliability.
* Lead the continuous enhancement and optimization of the data analytics platform and infrastructure, focusing on performance, scalability, and cost efficiency.
* Champion the complete data lifecycle, from robust infrastructure and data ingestion to detailed analysis and automated reporting, to maximize the strategic value of data and drive business growth.

We're looking for curious minds who think big and want to define tomorrow's technology. At Amazon, you'll grow into the high-impact engineer you know you can be, supported by a culture of learning and mentorship. Every day brings exciting new challenges and opportunities for personal growth.

Key job responsibilities
- Collaborate and communicate effectively with experienced cross-disciplinary Amazonians to design, build, and operate innovative products and services that delight our customers, while participating in technical discussions to drive solutions forward.
- Design and develop scalable solutions using cloud-native architectures and microservices in a large distributed computing environment.
- Participate in code reviews and contribute to technical documentation.
- Build and maintain resilient distributed systems that are scalable, fault-tolerant, and cost-effective.
- Leverage and contribute to the development of GenAI and AI-powered tools to enhance development productivity while staying current with emerging technologies.
- Write clean, maintainable code following best practices and design patterns.
- Work in an agile environment practicing CI/CD principles while participating in operational responsibilities including on-call duties.
- Demonstrate operational excellence through monitoring, troubleshooting, and resolving production issues.

We are looking for a Data Engineering Team Lead to drive the development and optimization of our data infrastructure.


So, what will you be doing all day?
Team Management

Serve as the direct manager for data engineers, providing regular feedback, career guidance, and technical mentorship.
Translate business requirements into actionable technical roadmaps; prioritize and assign daily tasks using sprint methodologies.
Cultivate a collaborative, high-performance team culture focused on continuous improvement and engineering excellence.
Cultivate a collaborative, high-performance team culture rooted in a delivery mindset, a business-driven focus, and engineering excellence.


Hands on Engineering

Design, build, and maintain robust, scalable data pipelines capable of processing massive datasets.
Oversee and maintain multiple development and production environments to ensure seamless deployment and high availability.
Design and implement highly cost-efficient cloud data infrastructure, constantly monitoring and optimizing resource utilization.
Research, develop, and integrate AI models and autonomous agents into the data ecosystem to automate pipeline monitoring, optimize data curation, and unlock intelligent data-driven capabilities.