דרושים » דאטה » Data Engineering Manager

The AI Engineering group builds modern infrastructure and solutions that improve how algorithms are developed at our company.
We are a small, independent team of experienced engineers with a mix of skills in algorithms, software, and infrastructure. We work in a DevOps style and build cross-team solutions that support research and development of advanced perception algorithms.
Our flagship project is a unified AV dataset used to train and evaluate next-generation models. We take large volumes of multi-camera video, object labels, HD maps, and sensor data from across the organization, and turn it into a curated, high-quality training set - at scale.
We are looking for someone who brings ML and computer-vision depth to the team - someone who can help shape the intelligence layer that decides what data is worth training on.
What will your job look like:
Work collaboratively with shared ownership. Your focus area will be the curation and ML side of our data pipeline, but you will contribute across the full stack alongside the rest of the team.
Build and improve the curation pipeline - from vision-model embeddings and scene detection, through VLM-based scene analysis, to scoring, deduplication, and sampling that produces a balanced and diverse dataset.
Run and optimize GPU inference at scale (embedding extraction, VLM inference) across thousands of driving sessions using workflow orchestration.
Develop scoring and sampling strategies that ensure rare but important scenarios (night driving, adverse weather, hazardous situations) are well-represented in the final dataset.
Work with algorithm teams to understand what data gaps hurt model performance and translate those into curation criteria.
Build validation and diagnostics that measure dataset quality - not just pipeline health, but whether the data is actually good for training.
Contribute to the core dataset SDK, converter, and 3D-geometry tooling (camera projection, calibration, coordinate transforms).

We're looking for a Data Platform Engineer to own and scale the Kubernetes infrastructure powering our large-scale data processing platform.

This is a hands-on role at the intersection of infrastructure and data engineering. You'll operate Kubernetes clusters running thousands of nodes, supporting workloads like Spark, Airflow, and remote shuffle services. Your focus: making distributed data workloads reliable, cost-efficient, and performant at scale.

This is not a traditional DevOps or SRE role. You won't be building CI/CD pipelines or managing web services. Instead, you'll be deep in Spark executor scaling, shuffle optimization, batch scheduler tuning, and capacity planning for clusters that process massive datasets daily.

If you've tuned Spark on Kubernetes at scale, wrestled with shuffle storage bottlenecks, or optimized batch scheduling across thousands of concurrent pods - this role is for you.

WHAT YOU'LL DO:
Operate and scale Kubernetes clusters with thousands of nodes supporting large-scale Spark and data processing workloads.
Manage and optimize Apache Spark on Kubernetes - executor autoscaling, driver scheduling, resource tuning, spot instance strategies.
Deploy and tune remote shuffle services (e.g., Apache Celeborn) to handle shuffle data at scale across multiple availability zones.
Operate and improve self-hosted Apache Airflow infrastructure on Kubernetes
Configure and optimize batch schedulers (e.g., YuniKorn, Volcano) for gang scheduling, fair-share queuing, and resource prioritization.
Drive cost optimization across large compute fleets - spot vs. on-demand strategies, node right-sizing, autoscaling policies, local SSD utilization.
Support and collaborate with Data Engineering teams on workload. performance, resource allocation, and infrastructure requirements.
Manage infrastructure-as-code (Terraform) and GitOps deployments (ArgoCD, Helm) for data platform services.
Integrate with managed data platforms (e.g., Databricks) and cloud storage for hybrid processing architectures.

Were looking for a hands-on AI Engineering Tech Lead to define and drive AI-native engineering practices, lead the architecture and development of scalable, intelligent systems, and embed AI across the software development lifecycle. This role involves providing technical leadership, identifying and solving architectural challenges, and collaborating cross-functionally to deliver high-impact, production-grade solutions.
Responsibilities:
Define and codify AI-native engineering practices, patterns, and guidelines to elevate the software development lifecycle.
Provide technical leadership and mentorship, fostering an AI-first engineering culture across teams.
Architect and lead the development of AI-native system frameworks that emphasize modularity, extensibility, and adaptive scalability.
Identify architectural risks, systemic bottlenecks, and long‑term scalability concerns - and proactively drive solutions.
Collaborate closely with Product, Customer success, Security and Business stakeholders to ensure technical solutions deliver real business impact.

We're looking for an experienced hands-on Software Engineering Team Lead to lead a highly skilled team of backend and frontend engineers through implementation, delivery, iteration, and build scalable systems that serve our customers.
Responsibilities:
Foster a positive, collaborative culture and grow the teams capabilities.
Lead and mentor engineers to ensure on-time delivery, quality development, productivity, and efficiency by conducting and lead design reviews & code reviews.
Work together with product managers to translate requirements into scalable technical solutions.
Balance refactoring and evolution with steady delivery of new features.
Drive a culture of technical excellence, ownership, and continuous improvement.
Oversee system reliability, monitoring, performance optimization and incident response.

We are looking for a highly skilled and motivated Software Team Lead to drive the technical direction of our development team while maintaining a substantial hands-on contribution. This role involves leading the team, hiring top talent, and ensuring the successful delivery of high-quality software solutions.
Responsibilities:
Technical Leadership: Guide the team in designing, developing, and maintaining robust cybersecurity solutions using Golang, C#, and Python.
Hands-On Development: Write high-quality, scalable, and secure code (50% of the time).
Team Management & Growth: Hire, mentor, and grow a team of talented engineers to build innovative cybersecurity products.
Code Reviews & Best Practices: Ensure high code quality through reviews, technical mentorship, and the enforcement of best practices.
Collaboration: Work closely with product managers, security researchers, and other stakeholders to define and deliver features.
Technical Roadmap: Contribute to architectural decisions and shape the future of the company's technology stack.

we are looking for a Software Team Lead.
Job description:
Manage a team and foster an innovative technological culture.
Work closely with project managers, QA managers, infrastructure managers, developers, and the executive staff.
The role requires reliability, transparency in management, high personal responsibility, commitment to success, monitoring and review skills, and serving as a role model.
Develop and lead web projects in the digital department.