Senior MLOps Engineer

עדכון קורות החיים לפני שליחה

8838208

שירות זה פתוח ללקוחות VIP בלבד

משרות דומות שיכולות לעניין אותך

דיווח על תוכן לא הולם או מפלה

שמך המלאמה השם שלך?

מייל

תיאור

שליחה

תודה על שיתוף הפעולה

מודים לך שלקחת חלק בשיפור התוכן שלנו :)

המשרה נמחקה

תוכל לצפות בה בדף המשרות שלי

המשרה הוחזרה לרשימת תוצאות החיפוש

האם תרצה להסיר את המשרה מרשימת

המשרות השמורות שלך?

כן לא

אירעה שגיאה בשליחת פרטיך למשרה

חברת השמה / כח אדם

3 ימים

Principal/Senior ML Platform Engineer (Cortex)

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

We are looking for a Principal MLOps Engineer with a deep focus on ML Platforms and Infrastructure to join our Data & AI group at Cortex Research. Our team is responsible for designing, building, and scaling the foundational MLOps and LLMOps platforms that power both our Data Scientists and Security Researchers. You will architect the high-performance core infrastructure that enables these roles to build, train, and deploy advanced AI systems-ranging from optimized Small Language Models (SLMs) to complex agentic workflows and RAG systems. If you are passionate about building scalable compute platforms and automating the full ML lifecycle to solve complex data and security challenges, we want to hear from you.
Key Responsibilities
Scale Distributed Training: Design and optimize infrastructure for training and fine-tuning LLMs and SLMs, leveraging distributed GPU workloads, efficient clustering, and compute optimization.
Automate the ML Lifecycle: Architect robust, automated pipelines for continuous training (CT) and deployment (CD) of models, ensuring a seamless flow from raw data collection to production environments.
Build Model Infrastructure: Own the serving architecture for LLMs/SLMs, balancing latency, throughput, and GPU utilization under production traffic.
Implement Advanced Monitoring: Establish comprehensive observability systems to monitor live model performance, data drift, and computational metrics, feeding insights back into the automated training loops for continuous improvement.
Collaborative Architecture: Partner closely with data scientists and security researchers to productize complex model architectures and streamline their workflows, while collaborating with our DevOps team to integrate with core cloud infrastructure.

Requirements:
Required Qualifications
Core Engineering: 4+ years experience as a Senior ML Engineer, MLOps Engineer, or Backend Platform Engineer (Hands-On) working with cloud environments.
Model Lifecycle Engineering: Hands-on experience managing the technical lifecycle of diverse model architectures, spanning classic ML, LLMs/SLMs, and agentic/RAG systems. This includes engineering scalable data preparation and processing pipelines as well as implementing infrastructure for model training, fine-tuning, optimization, and high-throughput production serving.
Distributed Training & Compute: Strong foundational knowledge of Deep Learning concepts (neural network architectures, training dynamics, optimization techniques) paired with proven experience setting up and optimizing distributed training workloads across multiple GPUs (using PyTorch, DeepSpeed, Megatron-LM, or cloud-native training infrastructure).
Cloud & Infrastructure Architecture: Strong infrastructure knowledge within a major cloud provider ecosystem (GCP, AWS, or Azure), specifically leveraging managed AI platforms and services.
Python Expertise: Expert-level Python skills focused on ML infrastructure, pipelines, and automation frameworks.
CI/CD Integration: Experience with modern CI/CD patterns (such as GitLab CI or GitHub Actions) for automating software and model delivery loops.
AI Tooling & Development: Proficient in leveraging day-to-day AI tools and ecosystems (e.g., Claude, Gemini, MCPs, custom skills, and markdown formatting) to generate, review, and test code dynamically within your development cycle.
Preferred Qualifications
Strong GCP ecosystem experience.
Background in data science or deep learning workflows.
Cybersecurity domain knowledge.

This position is open to all candidates.

עדכון קורות החיים לפני שליחה

8834186

שירות זה פתוח ללקוחות VIP בלבד

שמך המלאמה השם שלך?

מייל

תיאור

שליחה

תודה על שיתוף הפעולה

מודים לך שלקחת חלק בשיפור התוכן שלנו :)

המשרה נמחקה

תוכל לצפות בה בדף המשרות שלי

המשרה הוחזרה לרשימת תוצאות החיפוש

האם תרצה להסיר את המשרה מרשימת

המשרות השמורות שלך?

כן לא

אירעה שגיאה בשליחת פרטיך למשרה

חברת השמה / כח אדם

10/09/2026

ML Software Engineer

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

We are looking for a strong Backend Software Engineer to bridge the gap between our Machine Learning research team and our enterprise production systems. You will act as the technical backbone for our ML Scientists - by advising, designing and implementing the production facing features. If you are a backend expert who wants to solve complex system architecture challenges and dive into the world of ML platforms & Agentic LLM pipelines, this is the role for you - An exciting role collaborating with ML science team, data/infra team and DevOps to drive real customer impact.

As a ML Engineer, you will:

Lead ML delivery: transforming research output (code, models, ideas) into robust, scalable, low-latency microservices in production

Help architect e2e solutions to real customer pains ranging from ingestion, integration, ETLs, DB design up to low-latency services

Design, build, and maintain automated workflows for ML models, including auto-trains, benchmarking, testing, performance gating, and production deployment.

Tackle complex backend challenges: optimizing API response times, managing database connectivity and concurrency at scale, balancing accuracys drive for complex questions with the business needs of fast responsiveness by making hard technical trade-offs between customer gains and business costs.

Design and optimize data pipelines and ETL processes, connecting our Snowflake data warehouse to our training environments.

Work within our existing ML infrastructure (Kubeflow, MLflow, KServe) to ensure smooth model lifecycles and performance monitoring.

Collaborate closely with ML Scientists, guiding them on software engineering best practices without slowing down their research.

Monitor and optimize production models for performance, cost efficiency, availability, and observability.

Requirements:
6+ years of backend software engineering experience designing, building, and maintaining large-scale, high-throughput production systems

Strong coding skills, Ability to write clean, maintainable code, OOP familiarity, package design, microservices etc.
Note: Work is in python, but strong engineers with deep Java/C# backgrounds who have some Python experience and are willing to transition fully are highly encouraged to apply.

Solid Database design & SQL skills, Deep understanding of SQL, experience working with relational and/or bigdata (columnar) databases, ORMs, and efficient query design.

API & Performant Design Proven experience - building robust systems, you understand how to handle concurrency, ETL tradeoffs, building fault-tolerant best effort data flows

This position is open to all candidates.

עדכון קורות החיים לפני שליחה

8818291

שירות זה פתוח ללקוחות VIP בלבד

שמך המלאמה השם שלך?

מייל

תיאור

שליחה

תודה על שיתוף הפעולה

מודים לך שלקחת חלק בשיפור התוכן שלנו :)

המשרה נמחקה

תוכל לצפות בה בדף המשרות שלי

המשרה הוחזרה לרשימת תוצאות החיפוש

האם תרצה להסיר את המשרה מרשימת

המשרות השמורות שלך?

כן לא

אירעה שגיאה בשליחת פרטיך למשרה

לפני 3 שעות

Senior Applied AI Engineer

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

Were looking for a Senior Applied AI Engineer who combines deep data science expertise with the engineering skills to turn research into reliable, production-ready products.
Youll be a hands-on technical leader, owning significant AI capabilities from problem definition, academic survey, and system design through research, experimentation, deployment, and continuous improvement. Your work will span classical machine learning, large-scale data analysis, and AI agents that power brand intelligence, market research, and performance marketing.

You should have a track record of driving complex projects, not just contributing to them, and be comfortable making technical decisions, navigating ambiguity, and delivering in a fast-moving startup environment. Youll build systems that Fortune 500 marketing teams rely on to make consequential business decisions.
Responsibilities
Own AI capabilities end to end. Translate business and product needs into well-defined problems, research plans, and technical designs. Take solutions from initial exploration through production deployment and ongoing improvement.
Develop and improve our core algorithms.
Build production-grade AI agents - performance marketing, market research agents, auto-ML agents.
Turn research into maintainable software. Build reusable modules, data pipelines, and services with clear interfaces, automated tests, and robust deployment practices-not just standalone prototypes.
Own quality and performance in production. Monitor system behavior, investigate failure cases, and continuously improve accuracy, reliability, latency, and cost as usage and data volumes grow.
Drive technical decisions and execution. Choose the right approach for each problem, balancing statistical methods, classical ML, and LLM-based systems. Make explicit trade-offs between research depth, delivery speed, and operational complexity.
Provide hands-on technical leadership. Partner with product and engineering to shape priorities, lead technical initiatives, review designs and code, and mentor teammates.

Requirements:
MSc or PhD in Computer Science, Data Science, Statistics, Mathematics, or a related quantitative field.
5+ years of experience in data science or applied machine learning, plus 2+ years in ML engineering or software engineering, with direct responsibility for deploying and maintaining production systems.
Proven ownership of significant AI products or features. You have been a primary technical driver, taking ambiguous problems from initial concept to a working product used by real customers.
Strong foundations in machine learning and statistics, including experimental design, model evaluation, and practical experience with NLP, embeddings, clustering, or related methods for analyzing unstructured data.
Strong Python, SQL and Typescript skills, alongside solid software engineering practices: modular architecture, automated testing, version control, code reviews, and maintainable production code.
Hands-on experience building LLM-powered applications or AI agents beyond the prototype stage, including tool calling, structured outputs, context management, and systematic evaluation
Experience deploying and operating systems in a cloud environment, including containerization, CI/CD pipelines, logging, monitoring, and debugging production issues.
Strong product judgment and independent execution. You can define milestones, prioritize experiments, communicate technical trade-offs, and collaborate effectively across product, engineering, and business teams in a fast-moving environment.
Advantage
Experience as a core technical contributor at a high-growth startup, building new products and scaling them as adoption grows.
Experience in advertising technology, marketing analytics, search, information retrieval, ranking, or recommendation systems.
Familiarity with agent frameworks and SDKs such as ADK, LangChain, or comparable tooling.

This position is open to all candidates.

עדכון קורות החיים לפני שליחה

8837997

שירות זה פתוח ללקוחות VIP בלבד

שמך המלאמה השם שלך?

מייל

תיאור

שליחה

תודה על שיתוף הפעולה

מודים לך שלקחת חלק בשיפור התוכן שלנו :)

המשרה נמחקה

תוכל לצפות בה בדף המשרות שלי

המשרה הוחזרה לרשימת תוצאות החיפוש

האם תרצה להסיר את המשרה מרשימת

המשרות השמורות שלך?

כן לא

אירעה שגיאה בשליחת פרטיך למשרה

23/08/2026

Software Engineer (Infrastructure)

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

We are a well-funded, early-stage startup looking for a talented and motivated Backend Engineer specializing in infrastructure to join our founding team. The focus of this role is to build and scale the infrastructure that powers autonomous AI agents automating complex enterprise workflows. You will own the systems, pipelines, and platforms that let our AI agents run reliably, securely, and at scale in production.

Your Impact
Infrastructure & Platform

Design, build, and own the core infrastructure powering our AI agent platform, from data pipelines to production deployment systems.

Build and scale the backend systems that support high-throughput document processing and data extraction workloads.

Cloud Infrastructure and Scalability

Architect and deploy infrastructure on cloud platforms (AWS, GCP, or Azure) with a focus on scalability, reliability, and cost efficiency.

Own containerization and orchestration (Docker, Kubernetes) for all production workloads.

Build and maintain CI/CD pipelines and DevOps practices that let the team ship fast without breaking things.

Data Infrastructure

Design and manage data pipelines to process and analyze large volumes of documents and unstructured data at scale.

Build the infrastructure layer connecting AI agents to databases, vector stores, and enterprise systems (ERP, CRM).

API & Systems Integration

Build and maintain robust, well-documented APIs connecting AI agents with external systems and enterprise software.

Design for reliability: retries, observability, and graceful degradation across distributed systems.

Security and Compliance

Implement authentication and authorization mechanisms (OAuth2, JWT) to secure AI-driven systems.

Ensure compliance with data privacy standards (e.g. GDPR, HIPAA) and drive best practices for secure data handling across the infrastructure.

Monitoring and Optimization

Build observability and monitoring systems to track infrastructure health, performance, and cost.

Continuously optimize system performance for speed, reliability, and cost-efficiency at scale.

Collaboration

Work closely with AI/ML engineers, product, and the founding team to make sure infrastructure decisions support fast iteration and production-grade reliability.

Participate in code reviews, design discussions, and architecture planning to drive infrastructure strategy.

Requirements:
5+ years of experience in backend or infrastructure engineering, ideally supporting production AI/ML systems or high-throughput data pipelines.

Proven track record of building and scaling infrastructure in production environments.

This position is open to all candidates.

עדכון קורות החיים לפני שליחה

8793026

שירות זה פתוח ללקוחות VIP בלבד

שמך המלאמה השם שלך?

מייל

תיאור

שליחה

תודה על שיתוף הפעולה

מודים לך שלקחת חלק בשיפור התוכן שלנו :)

המשרה נמחקה

תוכל לצפות בה בדף המשרות שלי

המשרה הוחזרה לרשימת תוצאות החיפוש

האם תרצה להסיר את המשרה מרשימת

המשרות השמורות שלך?

כן לא

אירעה שגיאה בשליחת פרטיך למשרה

02/09/2026

Researcher

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

Join our company, an innovative startup building a fully-managed LLM-inference platform, that enables data heavy enterprises to perform any AI task at any scale without limits.
We're looking for an Experienced Performance Researcher to join our founding team. Youll be responsible for building and optimizing scalable cloud infrastructure solutions tailored for AI workloads. This role offers a unique opportunity to directly shape our infrastructure strategy, improve system reliability and performance, and contribute to establishing our company as a leader in adaptive AI compute management.
Join us to tackle the magic that make AI tick under the hood and build the backbone powering the AI revolution.
What Youll Do
- Design and build high-performance distributed inference pipelines for LLMs, focused on large-batch, non-real-time scenarios.
- Optimize GPU memory usage, kernel execution, and communication across nodes (NCCL, MPI, etc.).
- Own CUDA kernels, compiler-level tricks, and multi-GPU scheduling logic.
- Lead profiling and performance tuning for throughput, and cost- down to the kernel level.
- Collaborate with infra, product, and research teams to define SLAs, resource allocation logic, and runtime behaviors.
- Help build the core infrastructure that will run LLM workloads across hybrid GPU environments (cloud/on-prem/self-hosted).

Requirements:
- Deep experience with CUDA programming, GPU architecture, and low-level performance engineering.
- Fluency with Python and C++, and a mastery of profiling tools like Nsight, nvprof, perf, etc.
- Experience building systems for large-scale distributed training or inference (PyTorch, DeepSpeed, Ray, Horovod, etc.).
- Hands-on familiarity with cluster and container orchestration tools (Kubernetes, Slurm, Docker).
- Self-motivated and able to operate independently in a fast-moving startup environment.
- Strong analytical skills and a passion for elegant performance wins.
- A collaborative team player with strong interpersonal skills, a positive and easygoing attitude, and the potential to grow into a leadership role.
- Prior experience building inference runtimes or scheduling frameworks.
- Experience with serverless GPU models, model parallelism, tensor slicing, and batching tricks.
- Contributions to open-source HPC or ML infra projects.
- Understanding of AI/ML privacy and compliance concerns in enterprise environments.
- Track record of working on distributed systems at bleeding-edge research labs or infrastructure teams.

This position is open to all candidates.

עדכון קורות החיים לפני שליחה

8807342

שירות זה פתוח ללקוחות VIP בלבד

שמך המלאמה השם שלך?

מייל

תיאור

שליחה

תודה על שיתוף הפעולה

מודים לך שלקחת חלק בשיפור התוכן שלנו :)

המשרה נמחקה

תוכל לצפות בה בדף המשרות שלי

המשרה הוחזרה לרשימת תוצאות החיפוש

האם תרצה להסיר את המשרה מרשימת

המשרות השמורות שלך?

כן לא

אירעה שגיאה בשליחת פרטיך למשרה

23/08/2026

AI Engineer

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

We're forming a new AI Group and looking for a Senior AI Engineer to help shape it from an early stage - a greenfield, long-term effort to evolve how decisions are made across the platform using AI-driven systems. You won't just integrate APIs or build demos; you'll build the AI brain that works alongside (and increasingly drives) our core automation engine, with real production impact from day one and room to grow into technical leadership as the group scales.

Agentic AI Architecture: Design and build autonomous AI agents that analyze infrastructure in real time and make intelligent decisions. Work with modern agentic frameworks (LangGraph, PydanticAI) and conversational AI to create multi-agent systems - including troubleshooting, optimization, FinOps, and how-to agents. Leverage core LLM capabilities (tool-use, memory, retrieval) to operate safely in production.
Platform Integration & Intelligent Decision Systems: Develop MCPs to expose capabilities to AI agents that reason over infrastructure environments, metrics, configurations, and cost signals. Build integrations with tools like Slack, Jira, and AI-powered IDEs (Cursor, Windsurf) to deliver context-aware insights, from "why is this pod not scheduling?" to "how can we reduce costs by 30% safely?"
AI Model Development & MLOps: Build and deploy machine learning models that learn from infrastructure patterns - detecting the right resource policies for workloads, predicting optimal scaling triggers, and recommending GPU configurations. Own the complete ML pipeline from training to production, ensuring models are reliable, monitored, and continuously improving.
R&D AI Tools Development & Adoption: Build and embed internal AI tools to accelerate engineering, development, research, and support.
AI Tools for Business Impact: Develop AI-powered tools that help Sales and Support teams demonstrate value instantly - agents that analyze customer infrastructure, generate cost optimization reports automatically, and turn technical data into clear business recommendations.
End-to-End Ownership: Own AI systems from concept to production, ensuring they're fast (sub-2-second responses), reliable, safe, and cost-effective. Build evaluation frameworks to measure quality, implement security controls, and balance performance tradeoffs in production.
Technical Leadership: Define AI architecture and best practices as a founding member of the AI team. Make key technical decisions - choosing frameworks, designing multi-agent systems, establishing data governance - and shape how evolves from AI-enhanced internal tools to customer-facing AI products.

Requirements:
Core Engineering: Significant software engineering experience (typically 4+ years) with strong Python skills and solid backend engineering fundamentals.
Production Experience: Experience building and operating production systems in cloud environments.
Real-World GenAI Experience: Practical experience bringing LLM-based systems into production, including handling latency, cost control, and failure modes. Familiarity with additional agentic frameworks (e.g., LangChain, MetaGPT) and evaluation frameworks.
Builder Mentality: Strong ownership and the ability to operate independently while collaborating closely across teams, with the motivation to grow into technical leadership as the group expands.
(Advantage) Data & RAG: Experience enabling LLMs to consume structured or operational data (configurations, logs, metrics) and experience with retrieval systems (RAG) or vector databases.

This position is open to all candidates.

עדכון קורות החיים לפני שליחה

8792284

שירות זה פתוח ללקוחות VIP בלבד

שמך המלאמה השם שלך?

מייל

תיאור

שליחה

תודה על שיתוף הפעולה

מודים לך שלקחת חלק בשיפור התוכן שלנו :)

המשרה נמחקה

תוכל לצפות בה בדף המשרות שלי

המשרה הוחזרה לרשימת תוצאות החיפוש

האם תרצה להסיר את המשרה מרשימת

המשרות השמורות שלך?

כן לא

אירעה שגיאה בשליחת פרטיך למשרה

02/09/2026

Founding Forward Deployed Engineer

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

We're looking for our **first Forward Deployed Engineer**. You'll sit directly with our customers' engineering teams and get their workloads onto Impala - from the first scoping conversation to a production endpoint carrying real traffic, at a cost and latency profile they couldn't hit anywhere else.
This is an engineering role. You will write code every day, in customer repos and in ours. It also carries pieces of solutions architecture, product management, and pre-sales, and you should want that mix rather than tolerate it. Ambiguous business goals come in; observable, benchmarked, production services go out.
As the founding FDE you also define the function: what a POC looks like, what we promise and measure, which patterns get productized, and how the field feeds the roadmap. The next FDEs will work from what you build here.
What You'll Do
- **Own customer outcomes end to end:** problem framing, evaluation design, migration, deployment, benchmarking, monitoring. You're the technical owner from first call through expansion.
- **Win the POC:** turn a vague objective into a tight spec and a working proof of concept fast, with explicit quality, latency, throughput, and cost-per-token targets - and hit them.
- **Tune serverless inference for real workloads:** model and engine selection, batching strategy, KV cache behavior, speculative decoding, quantization, parallelism, cold-start and autoscaling behavior under bursty traffic. Diagnose regressions down to the inference engine.
- **Migrate workloads onto Impala:** move customers off OpenAI-compatible APIs, self-managed vLLM, SageMaker, or their own GPU fleets - and prove out the quality and cost delta with numbers.
- **Guide model strategy:** advise on open-weight model selection, distillation, and fine-tuning for specific tasks; help customers get from a general-purpose frontier model to a smaller, faster, cheaper one that holds quality.
- **Close the product loop:** bring the field back into the roadmap - write the PRDs, land the PRs, and turn one-off customer work into platform features.
- **Be the technical anchor in the room:** support sales on complex evaluations, run technical onboarding, earn trust with staff engineers and CTOs.

Requirements:
- **4+ years** building and shipping production software
- **Inference in production:** hands-on experience serving LLMs with **vLLM, SGLang, TensorRT-LLM** or equivalent, and real intuition for what makes inference fast or expensive.
- **Optimization fundamentals:** working knowledge of batching, KV cache, quantization, speculative decoding, tensor and pipeline parallelism - and the tradeoffs between them.
- **Model judgment:** fluency with the open-weight model landscape and good instincts on model selection for a given task, hardware profile, and latency budget.
- **Production cloud comfort:** containers, Kubernetes, observability, CI/CD. You don't need to be an SRE, but nothing here should be a black box.
- **Range in the room:** you can hold a technical conversation with a skeptical staff engineer and a commercial one with their VP, in the same meeting.
- **Default ownership:** ambiguity, unfamiliar codebases, and a customer waiting on you are the normal conditions of this job, not exceptions.
- Prior forward-deployed, solutions architecture, or applied ML engineering experience at an infrastructure company.
- Post-training experience: LoRA, SFT, DPO, RLHF, GRPO, distillation.
- GPU-level performance work CUDA, Triton, memory bandwidth and throughput profiling.
- Experience selling into or building for regulated, data-sensitive enterprises.
- Open-source contributions to inference or serving projects.
- You've been the first or second person in a function before.

This position is open to all candidates.

עדכון קורות החיים לפני שליחה

8807348

שירות זה פתוח ללקוחות VIP בלבד

שמך המלאמה השם שלך?

מייל

תיאור

שליחה

תודה על שיתוף הפעולה

מודים לך שלקחת חלק בשיפור התוכן שלנו :)

המשרה נמחקה

תוכל לצפות בה בדף המשרות שלי

המשרה הוחזרה לרשימת תוצאות החיפוש

האם תרצה להסיר את המשרה מרשימת

המשרות השמורות שלך?

כן לא

אירעה שגיאה בשליחת פרטיך למשרה

לפני 4 שעות

Senior AI Engineer and Agentic Platforms - Network Architecture

חברה חסויה

Location: Tel Aviv-Yafo and Yokne`am

Job Type: Full Time

We are at the forefront of the AI revolution, delivering brand new accelerated compute platforms for global impact. Our Network Architecture group is seeking a talented and motivated Sr. Software Engineer to build the agentic workflows that our architects use in their daily work. The software at the center of this role is our hardware network simulation environment - you will design multi-step agent workflows over it, engineer the context that grounds them in our own specifications and source code, and optimize their runtime performance. If you are passionate about building the practical infrastructure that brings intelligent agents to life, we want to hear from you.

What you'll be doing:
Build agentic workflows - loops, graphs, and multi-step pipelines - that carry real hardware network simulation and analysis work end to end.
Engineer the context these workflows run on, turning our simulation models, specifications, design documents, and source code into context that makes agents accurate in our domain.
Work closely with network architects to understand their workflows and translate them into agent workflows they use daily.
Optimize the runtime performance of our simulation tooling on these platforms, including execution time, compute cost, and end-to-end latency.
Define evaluation and regression testing for agent workflows, so that changes to a prompt, a graph, or a context source are measurable.
Build observability across agent runs: what the agent did, where it failed, and why.
Champion guidelines for secure and reliable agent workflows, including data handling, access control, and interaction boundaries.
Serve as a key technical resource for solving sophisticated integration issues between agents and internal tooling.

Requirements:
What we need to see:
B.Sc. or above in Computer Science, Computer Engineering, or a related field, or equivalent experience.
5+ years of hands-on experience in software engineering, with demonstrated ownership of production systems from design through deployment.
Expert-level programming skills in C++, with strong Python skills alongside it.
Strong understanding of the full stack, including hardware: memory, I/O, networking, accelerators, and where real performance bottlenecks occur.
Current, practical knowledge of how to build systems around AI models: agent loops, tool interfaces, context retrieval and management, and common failure modes.
Understanding of inference serving, including request lifecycle, batching, caching, and the tradeoffs between throughput, latency, and cost.

Ways to stand out from the crowd:
Experience writing hardware simulation software - network, system, or architectural simulators, models, or testbenches.
Networking experience - protocols, fabrics, switching, or RDMA - and experience working alongside silicon, systems, or architecture teams.
Hands-on experience with inference serving engines such as vLLM, TensorRT-LLM, or Triton Inference Server, including low-level internals such as KV cache, batching and scheduling, and quantization, and related performance work such as profiling and GPU programming.
Hands-on experience building or fine-tuning LLMs or other generative models.
Agent workflows, tooling, or context pipelines adopted by other engineering teams.

This position is open to all candidates.

עדכון קורות החיים לפני שליחה

8837912

שירות זה פתוח ללקוחות VIP בלבד

שמך המלאמה השם שלך?

מייל

תיאור

שליחה

תודה על שיתוף הפעולה

מודים לך שלקחת חלק בשיפור התוכן שלנו :)

המשרה נמחקה

תוכל לצפות בה בדף המשרות שלי

המשרה הוחזרה לרשימת תוצאות החיפוש

האם תרצה להסיר את המשרה מרשימת

המשרות השמורות שלך?

כן לא

אירעה שגיאה בשליחת פרטיך למשרה

חברת השמה / כח אדם

25/08/2026

AI Software Engineer

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

This role sits at the intersection of AI and high-performance systems engineering, focused on solving real-world problems under strict constraints. You will work on systems where performance and reliability are critical and where improvements have a direct, measurable impact on real-world safety.

This is a senior, systems-focused role with end-to-end ownership over performance and reliability of production computer vision pipelines. You will define optimization strategies, identify bottlenecks across the system, and drive improvements under real-world constraints.

What youll do
Build and optimize real-time computer vision pipelines running on edge systems processing live maritime video streams (e.g, NVIDIA Jetson, Triton Inference Server).
Take models from research and turn them into production-ready, reliable components deployed on vessels.
Profile and improve end-to-end system performance across: multi-camera video ingestion; preprocessing; inference; postprocessing
Identify and resolve bottlenecks across CPU, GPU, memory, and pipeline coordination.
Make and justify tradeoffs between latency, accuracy, stability, and resource utilization.
Design and implement robust data and inference pipelines (video -> model -> actionable output for crew).
Develop benchmarking and evaluation workflows to measure performance end-to-end and support release gating.
Build and improve observability tools, including logging, monitoring, and debugging workflows for production systems.
Define and maintain clear interfaces between research code and production systems.
Work closely with research and backend teams to integrate new models into production systems.
Continuously improve system efficiency and reliability under hardware and runtime constraints.

Requirements:
Requirements:
5+ years of software engineering experience, with a strong focus on systems and performance.
Hands-on experience working with computer vision or deep learning systems in production.
Strong programming skills in Python and/or C++.
Experience working with edge or embedded systems (e.g., NVIDIA Jetson platforms).
Strong understanding of system bottlenecks, including CPU, GPU, memory, and latency constraints.
Strong intuition for profiling-driven optimization and performance tuning.
Experience debugging complex systems and reasoning about behavior in real-world, noisy environments.

Strong advantage:
Experience working with edge or embedded systems.
Experience working with custom high-performance data or inference pipelines.
Familiarity with multi-sensor fusion (e.g., combining vision with radar or other signals).
Experience deploying and maintaining ML models in production environments.
Experience with low-level optimization and/or C++ performance tuning.
Proven experience optimizing model inference (e.g., TensorRT, ONNX Runtime, quantization, pruning, or similar techniques).

This position is open to all candidates.

עדכון קורות החיים לפני שליחה

8796312

שירות זה פתוח ללקוחות VIP בלבד

שמך המלאמה השם שלך?

מייל

תיאור

שליחה

תודה על שיתוף הפעולה

מודים לך שלקחת חלק בשיפור התוכן שלנו :)

המשרה נמחקה

תוכל לצפות בה בדף המשרות שלי

המשרה הוחזרה לרשימת תוצאות החיפוש

האם תרצה להסיר את המשרה מרשימת

המשרות השמורות שלך?

כן לא

אירעה שגיאה בשליחת פרטיך למשרה

30/08/2026

Senior Delivery Consultant - AI/ML - Application Development, Professional Services Israel

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

We are seeking an experienced Senior Delivery Consultant - Modernization with deep expertise in Artificial Intelligence to join our Professional Services (ProServe). This role combines strategic architectural vision with hands-on technical leadership to deliver innovative AI solutions that drive customer success and business transformation across diverse industries and use cases.

Key job responsibilities
* Architecture & Design: Design and architect end-to-end AI-powered application solutions aligned with customer business objectives and technical requirements.
* Define application architecture patterns, standards, and best practices for AI/ML integration on us.
* Create technical roadmaps for customer AI application development and modernization initiatives
* Evaluate and recommend AWS AI/ML services and technologies including our Bedrock, SageMaker, and generative AI solutions
* Design data pipelines and ETL processes to support AI model training and inference using AWS services
* Customer Engagement & Consulting:
Lead customer engagements from discovery through implementation, serving as trusted technical advisor
* Conduct AI readiness assessments and develop adoption strategies tailored to customer maturity levels
* Facilitate architecture workshops and design sessions with customer stakeholders
* Deliver Well-Architected reviews focused on AI/ML workloads
* Build strong relationships with customer technical teams and executive leadership
* Guide customers in constructing AI processes aligned with AWS best practices
* Technical Leadership: Lead cross-functional teams in implementing AI solutions from concept to production
* Provide technical guidance on AI model integration, deployment strategies, and optimization on AWS
* Conduct architecture reviews ensuring solutions meet scalability, performance, security, and cost-efficiency requirements
* Mentor customer teams and junior ProServe consultants on AI best practices and AWS technologies
* Collaborate with data scientists, ML engineers, and software developers to translate AI models into production applications
* AI Solution Development: Design architectures for generative AI applications including RAG (Retrieval-Augmented Generation) systems, chatbots, and intelligent agents using Amazon Bedrock
* Architect real-time and batch AI inference pipelines with appropriate monitoring and observability
* Implement MLOps practices using SageMaker for model versioning, deployment automation, and continuous improvement
* Design solutions for responsible AI including bias detection, explainability, and governance frameworks
* Optimize AI application performance, cost, and resource utilization across AWS services
Knowledge Sharing & Thought Leadership
* Develop reusable assets, reference architectures, and best practice documentation
* Contribute to AWS ProServe knowledge base and customer-facing content

דרישות:
Basic Qualifications
- 10+ years of software development experience.
- 5+ years of machine learning, statistical modeling, data mining, and analytics techniques experience.
- Knowledge of AWS services including compute, storage, networking, security, databases, machine learning, and serverless technologies.
- Knowledge of programming languages such as C/C++, Python, Java or Perl.
- Master's degree in computer science, engineering, mathematics or equivalent, or experience in defining and creating benchmarks for assessing GenAI model performance.
- Understanding of various AI domains: NLP, computer vision, recommendation systems, predictive analytics.
- Willingness to travel to customer sites as needed.

Preferred Qualifications
- Certified Machine Learning Specialty or AI Practitioner or Generative AI - Associate.
- Contributions to open-source AI projects or published research.
- Experience with responsible AI frameworks, governance practices, and compliance requirements.
- Prior experience in ProServe, consulting, or systems integrati המשרה מיועדת לנשים ולגברים כאחד.

עדכון קורות החיים לפני שליחה

8802053

שירות זה פתוח ללקוחות VIP בלבד