Experienced Software Engineer - ML Platform

17/06/2026

Experienced Software Engineer - ML Platform

חברה חסויה

Location: Ramat Gan

Job Type: Full Time

our company's ML Platform group builds and operates the core infrastructure that powers large-scale AI workloads across on-prem bare-metal GPU clusters and multi-cloud environments. Our goal is to deliver the modern infrastructure and tooling that accelerates our company's entire algorithm development lifecycle - from a researcher's first experiment to a production deployment.
We are a small, independent group of engineers with diverse skills across software, infrastructure, and systems. We set the standards, build the cross-company products, and take end-to-end ownership of everything we ship.
What will your job look like?
Design, develop, and maintain the Python framework that enables algorithm developers across our company to train, validate, quantize, and deploy deep learning models - locally, on-prem, and across cloud providers - through a single unified interface
Build high-performance data streaming libraries that feed large-scale distributed training pipelines in Rust with Python interfaces
Set the standard for reliable, reproducible research at scale - experiment tracking, configuration management, checkpoint handling, and multi-node training
Work directly alongside algorithm researchers to understand friction, propose solutions, and ship them - without layers of process in between
Contribute to open source when the right fix/feature belongs upstream.

Requirements:
A value-first mindset focused on shipping early and often
2+ years of hands-on experience as a software engineer in the industry or in a similar relevant role
B.Sc. in Computer Science, Software Engineering, or equivalent hands-on experience
Strong software engineer skills in Python - tested, production-grade code that other engineers can build on
Familiarity with deep learning frameworks (ideally Pytorch) and distributed training workflows
Experience with containerization and CI/CD pipelines
Contributions to open source projects
Familiarity with Linux internals - networking, file systems, process management
Experience in Rust/C/Cuda
Experience with cloud infrastructure (AWS or similar) and distributed storage
Exposure to infrastructure-as-code or Kubernetes-based deployments.

This position is open to all candidates.

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8699142

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17/06/2026

Senior ML Data Engineer

חברה חסויה

Location: Ramat Gan

Job Type: Full Time

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).

Requirements:
4+ years in data engineering or backend/software engineering with serious data work - pipelines that run in production, not just notebooks.
Strong Python and the PyData stack (NumPy, PyArrow, Pandas, DuckDB).
Some background in research, algorithms, or ML - enough that you can read a paper, understand a model's outputs, and have informed conversations with algorithm engineers.
Comfort working with vision-model outputs as data: embeddings, detection results, VLM responses.
Ability to work across team boundaries - this role lives between algorithm teams, infra teams, and our own.
Experience with autonomous-driving datasets or perception pipelines.
3D geometry and camera model intuition (or the mathematical background to ramp up).
Workflow orchestration (Argo, Airflow, Kubeflow).
Vector databases or columnar analytics (LanceDB, DuckDB, Parquet at scale).
Familiarity with curation concepts (active learning, hard-example mining, distribution balancing) - useful context, not a requirement.
Exposure to LLM agents or agentic workflows for data tasks.

This position is open to all candidates.

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10/06/2026

AI Infrastructure Engineer

חברה חסויה

Location: Ramat Gan

Job Type: Full Time

Required AI Infrastructure Engineer
Description
We are building its internal AI infrastructure layer from the ground up. We have real agents running in production, a growing base of employees using AI in their daily work, and a clear architectural direction. What we don't have yet is a dedicated engineer to own it.
You'll be the first. Your job is to close the gap between "working prototype" and "production platform" - owning the foundation that hosts our agents, the pipelines that ship them, and the reliability layer (observability, cost controls, audit trails, evals) that makes it safe to run AI at scale in a trust & safety company.
This is an infrastructure-first role with deep AI fluency - not a prompt engineer, not a wrapper-framework operator, not a no-code builder. You should be equally comfortable writing a Terraform module, debugging a Kubernetes pod, and tracing an agent's tool-call chain.
We dont operate with a predefined backlog here; you will be responsible for identifying high-impact needs and bringing them to life. The perfect fit for this role has a track record of deploying agentic systems that have held up under real-world usage, balances a focus on infrastructure with a deep concern for user experience, and recognizes that the primary hurdle in AI integration is rarely the model itself.
Responsibilities:
Platform & Infrastructure:
Architect, build, and run the AWS/Kubernetes platform that hosts our internal AI agents and tools; drive AWS Well-Architected pillars (operational excellence, security, reliability, performance, cost, sustainability).
Own Infrastructure-as-Code: Terraform modules, standards, and reviews for Bedrock, agent runtimes, vector DBs, and supporting services.
AI Systems:
Design and ship production-grade agents and multi-agent pipelines using the Anthropic Agent SDK, Claude Code, AWS Bedrock, and MCP - not wrapper frameworks.
Own the full agent lifecycle: scoping → prototyping → eval → deploy → monitor → iterate.
Integrate agentic workflows into internal and product systems via APIs, databases, webhooks, Slack, and email.
Reliability, Observability, Cost:
Build first-class observability across apps and infra: OpenTelemetry, Prometheus, plus LLM-specific tracing (Langfuse or equivalent), token/cost metrics, and eval pipelines.
Define SLOs/SLIs and error budgets for AI services - latency, model fallback chains, eval regression gates, agent success rates. Lead incident readiness, response, and post-mortems.
Drive FinOps: model routing by cost, cache hit rates, batch vs. realtime tradeoffs, budget alarms, per-team chargeback visibility.
Implement guardrails: prompt-injection defenses, PII redaction, model allowlists, human-in-the-loop checkpoints, audit trails.
Org Impact:
Identify high-leverage workflows across the organization and translate them into scalable agentic automations.
Partner with R&D, Delivery, security, and external vendors to deliver platform capabilities.

דרישות:
Requirements (must-have)
3-5 years in software engineering, shipping and operating production-grade systems.
2+ years hands-on AWS, Kubernetes, and Terraform in production - not familiarity, ownership.
1-2 years hands-on building and deploying LLM-powered or agentic systems in production.
Proficiency in Python: async patterns, REST APIs, cloud-native architecture.
Production experience with native agentic SDKs (Anthropic Agent SDK, Claude Code) and MCP - tool-calling patterns, server configuration, memory systems, vector DBs.
Hands-on AWS Bedrock for model access, IAM-based auth, and enterprise deployment patterns.
Production CI/CD ownership (GitHub Actions, Argo CD, or equivalent) and observability stack experience (OpenTelemetry + Prometheus, plus LLM tracing).
Proven ownership: design → implement → release → operate → improve, independently and within a team.
Strong debugging instincts across multi-step agent chains and distributed המשרה מיועדת לנשים ולגברים כאחד.

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17/06/2026

ML Software Engineer

חברה חסויה

Location: Ramat Gan

Job Type: Full Time

we are seeking a strong ML Software Engineer to join our deep learning LiDAR & Radar group and help scale the systems that bring cutting‑edge perception models into production. Youll build the software layers, data pipelines, and runtime systems that turn advanced neural networks into reliable, high-performance solutions running on edge devices.
This is a hands-on, high‑ownership role within a growing group working closely with algorithm developers. The work spans Python and C++, ML infrastructure, model integration, performance optimization, and production delivery.
** The role includes working on-site at our Jerusalem office several days per week.
What will your job look like:
Lead end-to-end development of features - from design and implementation to integration, testing, and deployment
Build ML pipelines for data-based diverse dataset creation and efficient model inference
Design data selection and sampling strategies to ensure coverage of rare and critical scenarios
Partner with algorithm teams to translate model weaknesses into data curation criteria
Develop validation and diagnostics to measure dataset quality-not just pipeline health but training effectiveness
Integrate neural network models into C++ production systems, including runtime, data flow, and pre/post‑processing
Bring models from research/prototype stage into robust, production‑ready deployments
Optimize runtime performance (latency, memory, and throughput) in resource‑constrained environments
Contribute to deployment flows (e.g., model conversion, profiling, optimization)
Build and improve CI/CD pipelines, automated testing, and development workflows.

Requirements:
B.Sc. in Computer Science, Software Engineering, or equivalent
3+ years of hands-on C++ development experience
3+ years of hands-on Python development experience, including the PyData stack (NumPy, Pandas)
Experience working in Linux environments
Strong motivation to work closely with deep learning algorithms and production of AI systems
Interest in neural network deployment on edge devices, including inference runtimes, performance optimization, and model integration
Proven ability to work across team boundaries (algorithms, infra, product)
Strong motivation to work on production AI systems and deep learning integration
Interest in edge deployment, inference runtimes, and performance optimization
Advantages:
Experience with autonomous-driving datasets or perception pipelines
Background in 3D geometry and/or strong mathematical foundation
Experience with workflow orchestration tools (Airflow, Argo)
Familiarity with data curation techniques (e.g., active learning, hard example mining, distribution balancing)
2+ years in data engineering or backend systems with large‑scale data (production environments).

This position is open to all candidates.

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לפני 15 שעות

Staff Architect, Data & AI Infra

חברה חסויה

Location: Ramat Gan

Job Type: Full Time

We are looking for a Staff Architect, Data & AI Infra to shape, build, and scale the infrastructure that powers data, AI, and research platforms. This is a senior player-coach role with broad architectural ownership across data infrastructure, ML infrastructure, developer experience, reproducibility, and production reliability. You will work across the wider engineering group as a hands-on technical architect, while also managing a small team of individual contributors focused on ML infrastructure.

This role is ideal for someone who can move between long-term platform architecture and practical execution: defining standards, building core systems, mentoring engineers, improving reliability, and partnering with Data Engineering, AI/Research, Product Engineering, Security, Bioinformatics, and Leadership to make data and AI platforms scalable, reproducible, secure, compliant, and easier to use.

Location: Ramat Gan, Israel (hybrid model)

What will you do?

Architectural Leadership: Own and evolve the technical roadmap for data and AI platforms, ensuring scalable and reliable architecture that supports current needs and prepares for a multi-cloud future.
MLOps & Platform Development: Design and build end-to-end MLOps systems-covering experimentation, training, reproducibility, and deployment-while managing specialized infrastructure like BigQuery, orchestration tools (Dagster/Airflow), and R/Python workloads.
Infrastructure Strategy: Define and lead strategy for GPU resources (scheduling, utilization, batch compute) and establish engineering best practices, data architecture standards, and platform guardrails.
Developer Experience: Enhance developer productivity by building self-service platforms, automation, internal tooling, and reusable templates that simplify workflows and reduce operational friction.
Team Leadership: Act as a player-coach to mentor engineers and manage a small team of ICs, fostering a culture of sound decision-making and technical excellence across the broader group.
Security & Reliability: Partner with Security to enforce compliance (SOC2, HIPAA, GDPR) and access controls, while mitigating operational risk through improved observability, incident readiness, and robust support processes.

Requirements:
8+ years of industry experience in infrastructure, platform, data, or ML engineering, with a deep background in designing production infrastructure for data-intensive or AI/ML systems.
Hands-on expertise building and operating MLOps systems (for model development, training, and deployment) and managing GPU infrastructure, including scheduling, resource management, and utilization.
Proficient in managing data infrastructure technologies (e.g., BigQuery, data warehouses, object storage, orchestration systems like Dagster or Airflow) and operating within Kubernetes/containerized environments.
Demonstrated ability as a player-coach, including people-management experience or leading small engineering teams, with a focus on mentoring senior engineers and influencing technical direction.
Strong communication skills with the ability to partner effectively across diverse groups, including Data Engineering, AI/Research, Product Engineering, Security, Bioinformatics and Leadership.

This position is open to all candidates.

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29/06/2026

Big Data Engineer

חברה חסויה

Location: Ramat Gan

Job Type: Full Time

we are looking for a Big Data Engineer.
As a Senior Big Data Engineer, working within Mobility Group, you will play a pivotal role in designing, developing, and maintaining the data infrastructure that powers our location analytics platform.
RESPONSIBILITIES:
Data Pipeline Architecture and Development: Design, build, and optimize robust and scalable data pipelines to process, transform, and integrate large volumes of data from various sources into our analytics platform.
Data Quality Assurance: Implement data validation, cleansing, and enrichment techniques to ensure high-quality and consistent data across the platform.
Performance Optimization: Identify performance bottlenecks and optimize data processing and storage mechanisms to enhance overall system performance and reduce latency.
Cloud Infrastructure: Work extensively with cloud-based technologies (GCP and AWS), to design and manage scalable data infrastructure.
Collaboration: Collaborate with cross-functional teams including Data Analysts, Data Scientists, Product Managers, and Software Engineers to understand requirements and deliver solutions that meet business needs.
Data Governance: Implement and enforce data governance practices, ensuring compliance with relevant regulations and best practices related to data privacy and security.
Monitoring and Maintenance: Monitor the health and performance of data pipelines, troubleshoot issues, and ensure high availability of data infrastructure.
Mentorship: Provide technical guidance and mentorship to junior data engineers, fostering a culture of learning and growth within the team.

Requirements:
Strong hands-on Apache Spark experience - building and operating pipelines in production, not just familiarity
Proficiency in PySpark or Scala for Spark development
Proven track record delivering ETL pipelines and data integration at scale
Solid SQL skills and command of data modeling concepts
Cloud platform experience (AWS, GCP, or Azure) in a production data context
Comfortable working with distributed systems and big data formats (Parquet, Delta Lake)
Nice to have:
Experience with pipeline orchestration tools, particularly Apache Airflow
Exposure to the geospatial or location analytics domain
Familiarity with Hadoop ecosystem components
Background in both Python and Scala (beyond Spark context)

This position is open to all candidates.

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8715025

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03/06/2026

AI Automation & Agent Engineer

חברה חסויה

Location: Ramat Gan

Job Type: Full Time and Hybrid work

As we scale our portfolio of live automations, were looking for an experienced AI Automation & Agent Engineer to take on a broad and high-impact role. Youll lead new automation projects from ideation to production, own the reliability of existing systems, and serve as the go-to expert helping our employees get the most out of AI tools - especially Claude Code. This is a hands-on, cross-functional position at the center of how we adopt and scale AI internally.
Responsibilities
Lead Automation Projects:
Partner with department leads across sales, support, finance, and HR to identify high-impact AI and automation opportunities.
Design and build LLM-based workflows, integrating APIs, MCP servers, and internal tools.
Develop agent-like automations and internal copilots that augment decision-making and execution.
Own the full lifecycle - from ideation and process design through development, testing, and production launch.
Present project plans, progress updates, and outcomes with measurable impact to stakeholders at all levels.
Build AI Systems & Integrations:
Build robust, maintainable workflows using N8N, Claude Code, and other orchestration tools.
Integrate across systems using REST APIs, webhooks, and external/internal tools.
Design reusable patterns for skills, agents, and workflows that can scale across teams.
Continuously evaluate and adopt new AI tooling, MCP capabilities, and agent frameworks.
Maintain & Improve Live Systems:
Monitor, triage, and resolve issues across all live AI automations, copilots, and agents.
Identify recurring failure patterns and implement systemic improvements to reliability, performance, and cost.
Ship incremental improvements and new capabilities quickly and safely.
Maintain clear documentation for workflows, agents, and system behavior.
Drive AI Adoption, Skills & Governance Across:
Act as the internal expert and first point of contact for employees using Claude Code and AI tools.
Help teams build and scale AI skills - from basic usage to advanced workflows and agent design.
Manage and optimize AI usage and performance across the organization (tokens, costs, reliability, adoption).
Build and evolve an internal AI control tower - providing visibility into usage, performance, governance, and impact.
Run onboarding sessions, workshops, and create practical guides that empower teams to work independently with AI.
Guide teams through MCP integrations, tool configurations, and best practices.
Stay current on Claude Code updates, new MCP capabilities, and emerging AI tooling - and proactively share relevant developments with the team.

Requirements:
Must-haves:
3+ years of experience in a technical role in software development, data analyst or AI/ML operations.
Proven ability to lead projects end-to-end, from requirements to production.
Hands-on experience building LLM-based workflows, automations, or agents.
Strong experience with workflow tools (N8N, Zapier, Make, Temporal, or similar).
Solid coding skills in Python and/or JavaScript.
Experience integrating systems using APIs, webhooks, and structured data (JSON).
Strong communication skills - able to work closely with non-technical teams and translate needs into solutions.
Nice-to-haves:
Experience building internal copilots or AI-powered tools.
Familiarity with multi-agent systems, MCP ecosystem, or orchestration frameworks.
Experience defining best practices, patterns, or frameworks for AI usage.
Background working across business domains (sales, finance, support, HR)
Experience enabling AI tool adoption - training, documentation, or internal consulting for business teams.

This position is open to all candidates.

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2 ימים

Senior ML Engineer

חברה חסויה

Location: Ramat Gan

Job Type: Full Time

we are looking for a Senior ML Engineer.
Responsibilities:
Work on core data and machine learning infrastructure, which is at the heart of offering. You will create innovative solutions for data ingestion and normalization from multiple data sources, feature engineering and feature selection, as well as actual model training and evaluation. All in large scale and completely automated.

Requirements:
5+ years experience as a Machine Learning Engineer.
10+ years of experience with Python/Java/Scala.
Strong understanding of distributed systems, object-oriented programming and design patteri
Distributed Compute frameworks such as Spark, Dask, Ray etc
Hands-on experience designing, training, and deploying machine-learning models
MLOps
Hands-on experience with open source ML libraries like: catboost, lightgbm, xgboost, scikit-learn, NumPy, Pandas, Microservices architecture, cloud technologies, Docker/K8s.
Ability to design and own a feature through all its phases.
Bonus:
BSc./MSc. In CS or similar - an advantage
Building data pipelines using Apache Airflow
Hands on experience with Spark, SparkSQL, Spark streaming and other Spark related projects

This position is open to all candidates.

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8727975

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01/06/2026

software engineer, Interceptor Systems

חברה חסויה

Location: Ramat Gan

Job Type: Full Time

Hands-on software engineering for our cutting-edge missile interceptor system. You'll develop and integrate components across the software stack, either on the Embedded / flight side (RTOS, low-latency sensor and comm code on the interceptor) or on the ground station / Command & Control side (distributed services for mission monitoring, threat evaluation, and visualization). You'll work under the Software Group Lead's architectural direction, with deep ownership of the modules you ship. We are looking for a "builder" mentality, someone who drives end-to-end delivery from concept to field deployment, and who treats AI coding tools as a force multiplier rather than a curiosity.
Why Join us?:
This is a unique opportunity to be at the heart of a defense-tech startup during its most exciting growth phase!
Responsibilities:
Build: Develop flight software, sensor fusion algorithms, and secure communication protocols between the interceptor and C2; or build distributed microservices for the ground station, depending on which area fits your background. Integrate: Work alongside Hardware Engineering (mechanical, electrical, GNC), Systems Engineering, and Program Management to integrate the software with the rest of the missile and ground station. TEST : Participate in HIL/SIL testing phases, support field trials, and write the automation that keeps these tests fast and reliable. AI-assisted delivery: Use modern AI coding tools (GitHub Copilot, Cursor, Claude Code, etc.) heavily across your daily work to ship faster without compromising safety-critical standards. Collaborate: Contribute to design reviews and architectural decisions; raise issues and propose alternatives rather than waiting for direction.

Requirements:
Experience: 3-5+ years in software engineering, ideally with exposure to aerospace, defense, robotics, or another safety-critical domain. Strong in C / C ++ for hard Real-Time environments, OR strong in distributed/back-end stacks (Go, Rust, Python, Node) for the ground-station side. One or more of these depending on your specialization:
* RTOS experience (FreeRTOS, VxWorks, Embedded Linux, etc.)
* Communication bus protocols: CAN bus, MIL- STD -1553, SPI, Ethernet
* Distributed systems on containerized environments (Kubernetes, Docker)
* Low-latency data visualization and geospatial situational awareness Education: B.Sc. in Computer Science, Aerospace Engineering, or Electrical Engineering. Project history: Direct experience contributing to UAVs, missiles, autonomous kinetic systems, or similar safety-critical hardware/software systems.
* Eligible for security clearance. Preferred Qualifications AI tooling fluency: Proven track record of using AI agentic tools to ship faster, refactoring legacy systems, documenting complex architectures, generating tests. DevOps for Embedded Experience building CI/CD pipelines for Embedded systems, including automated Hardware-in-the-Loop (HIL) testing. Sensor fusion (Radar, EO/IR, IMU) and target tracking experience.
* Knowledge of cybersecurity frameworks for defense-grade software (e.g., MISRA C / C ++).
* Experience with secure, jam-resistant RF data links and network protocols.
* M.Sc. in a relevant field.

This position is open to all candidates.

עדכון קורות החיים לפני שליחה

8675481

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מייל

תיאור

שליחה

תודה על שיתוף הפעולה

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אירעה שגיאה בשליחת פרטיך למשרה

2 ימים

Senior DevOps Engineer

חברה חסויה

Location: Ramat Gan

Job Type: Full Time

As a Senior DevOps Engineer on the Price-It Platform team, youll own core cloud infrastructure, CI/CD, and the Kubernetes platform that powers Earnixs cloud-based decisioning products for global insurers and banks. Youll take end-to-end technical ownership of high-impact platform initiatives - from design through production - working hands-on across AWS, Kubernetes, and automation, while shaping how the team builds and ships.
What You'll Do: Own and evolve the cloud platform: AWS infrastructure, EKS/Kubernetes, and Terraform-based Infrastructure-as-Code. Build and maintain CI/CD pipelines and GitOps workflows that keep delivery fast, safe, and repeatable. Design and operate secure networking and access (ALB, OIDC/OAuth2, JWT/M2M, Okta, firewalling). Drive reliability, scalability, and resilience - including disaster recovery and multi-region readiness. Partner closely with R&D, Product, QA, and Support to take initiatives from design to production. Improve Developer experience and velocity, including through AI-assisted and agentic engineering workflows. Mentor and raise the engineering bar through technical leadership, design reviews, and documentation.
Position Intro:
Earnix is the premier provider of mission-critical, cloud-based intelligent decisioning across pricing, rating, underwriting, and product personalization. These fully-integrated solutions provide ultra-fast ROI and are designed to transform how global insurers and banks are run by unlocking value across all facets of the business. Earnix has been innovating for insurers and banks since 2001 with customers in over 35 countries across six continents and offices in the Americas, Europe, Asia Pacific, and Israel.

Requirements:
Youll Do It Using: 5+ years of hands-on DevOps / Platform Engineering experience. Production expertise with AWS, Kubernetes (EKS), and Terraform (Infrastructure-as-Code). Strong CI/CD (Jenkins or equivalent), GitOps (ArgoCD), Helm, and containerization (Docker). Solid cloud networking, security, and IAM fundamentals. Scripting in Python and/or Bash. Familiarity with AI-assisted / agentic development tools (e.g. Cursor, Claude). Advantages: Observability (Prometheus/Grafana/Datadog), Karpenter, Crossplane, Kyverno, DR/multi-region, FinOps; relevant academic background or equivalent practical experience.
Youll Excel By: Working effectively in a fast-paced, growing, and global environment. Bringing a creative, structured, and proactive approach to problem solving. Communicating clearly and professionally with different audiences. Being well-organized, independent, collaborative, and accountable.

This position is open to all candidates.

עדכון קורות החיים לפני שליחה

8726804

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אירעה שגיאה בשליחת פרטיך למשרה

17/06/2026

Expert Deep Learning Research Engineer - Road Detection

חברה חסויה

Location: Ramat Gan

Job Type: Full Time

The Road Algorithm team is responsible for one of the most critical and challenging tasks in autonomous driving - detecting and understanding the drivable road. Our work leverages Deep Neural Networks and geometric modeling to deliver reliable and high-quality road perception for autonomous vehicles.
We are looking for an Expert Deep Learning Research Engineer who will both drive independent deep learning research and collaborate closely with other developers to help unlock new directions, solve complex challenges, and elevate the teams algorithmic capabilities.
What will your job look like:
Conduct hands-on research and development of deep learning algorithms for road understanding, drivable area detection, and scene structure modeling
Lead exploratory investigations into new architectures, training strategies, and data utilization methods
Join forces with other developers to troubleshoot difficult problems, introduce new ideas, and guide technical decisions
Own projects end-to-end - from concept and experimentation to integration and scalable deployment.

Requirements:
B.Sc. or M.Sc. in Computer Science, Electrical Engineering, or a related field
5+ years of hands-on experience in Machine Learning / Deep Learning research and development
Strong experience with Transformer-based architectures (e.g., Vision Transformers or similar)
Strong proficiency with PyTorch or TensorFlow and practical experience building and optimizing deep neural networks
Experience working with cloud environments (e.g., AWS) - including data handling, distributed training, or running large-scale batch jobs
Proven ability to work both independently and collaboratively, supporting others and leading technical investigations
Excellent analytical skills, creativity, and a drive to push the limits of applied research.

This position is open to all candidates.

עדכון קורות החיים לפני שליחה

8699139

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