DevJobs

AI Engineer

Overview
Skills
  • Python Python ꞏ 2y
  • AI frameworks ꞏ 2y
  • CNNs ꞏ 2y
  • Debugging ꞏ 2y
  • Deep learning architectures ꞏ 2y
  • Transformers ꞏ 2y
  • System-level design ꞏ 2y
  • Performance optimization ꞏ 2y
  • Video pipelines
  • Agentic workflows
  • Triton
  • Tracking models
  • TensorRT
  • Segmentation models
  • Reasoning systems
  • Real-time systems
  • Open-source LLMs
  • NVIDIA NIM
  • NVIDIA CUDA
  • Low-latency systems
  • Large Language Models
  • High-performance systems
  • GPU performance profiling
  • Detection models
  • Computer vision
  • AI-driven applications

About Us

We are an NVIDIA partner, delivering professional services in advanced software development, artificial intelligence systems, and high-performance AI solutions.

We build production-grade AI systems optimized for NVIDIA GPU platforms, working across multiple applied AI domains, including Generative AI / Agentic Systems and Computer Vision.


Role Overview

We are looking for an experienced Senior AI Engineer to take a leading role in designing, building, and delivering advanced AI systems for real-world applications.

This role is suited for a hands-on engineer with strong software engineering skills and deep experience in applied AI, who enjoys solving complex problems, owning technical solutions end-to-end, and mentoring junior team members.

Projects typically focus on one primary domain: either LLM-based agentic systems or computer vision systems, depending on business needs and expertise.


What We Work On

Our work spans two main AI domains:

1. Agentic AI & Large Language Models

  • Design and implementation of agentic systems powered by Large Language Models (LLMs)
  • Deployment of open-source LLMs on NVIDIA GPUs
  • High-performance inference using NVIDIA technologies such as NVIDIA NIM (Inference Microservices)
  • System-level design for reliability, scalability, and performance

2. Computer Vision & Deep Learning

  • Design and development of advanced computer vision systems
  • CNN and transformer-based models for real-world vision tasks
  • Detection, segmentation, tracking, and video analytics pipelines
  • Performance optimization on GPU platforms


Key Responsibilities

  • Lead the design and development of AI systems in either LLM-based agentic systems or computer vision
  • Own end-to-end delivery of AI solutions, from architecture and prototyping to production deployment
  • Optimize model performance, latency, and throughput on NVIDIA GPU platforms
  • Design clean, maintainable, and scalable AI software architectures
  • Collaborate with customers, product teams, and engineers to translate requirements into technical solutions
  • Mentor junior engineers and contribute to technical best practices
  • Evaluate new tools, models, and frameworks and drive their adoption when appropriate


Required Background & Experience

  • BSc or MSc in Computer Science, Electrical Engineering, or a related field
  • 5+ years of experience in software engineering and applied AI (or equivalent)
  • Strong proficiency in Python and modern AI frameworks
  • Proven experience delivering production-grade AI systems
  • Solid understanding of deep learning architectures (CNNs, transformers)
  • Experience with system-level design, debugging, and performance optimization


Domain-Specific Experience (One or More)

LLM / Agentic Systems:

  • Experience working with Large Language Models (LLMs)
  • Building agentic workflows, reasoning systems, or AI-driven applications
  • Deploying and optimizing open-source LLMs for inference

Computer Vision:

  • Strong background in computer vision and deep learning
  • Hands-on experience with detection, segmentation, and tracking models
  • Experience with video pipelines and real-time or near-real-time systems


Nice to Have

  • Experience with NVIDIA technologies (CUDA, TensorRT, Triton, NVIDIA NIM)
  • Experience with GPU performance profiling and optimization
  • Background in high-performance or low-latency systems
  • Experience mentoring engineers or leading technical initiatives


What We Offer

  • Ownership of complex, high-impact AI projects
  • Work with cutting-edge NVIDIA GPU and AI technologies
  • Influence over architecture, tooling, and technical direction
  • A collaborative, engineering-driven culture
  • Opportunities for technical leadership and professional growth
  • Real-world, production-scale AI challenges


Requirements:

  • BSc or MSc in Computer Science, Electrical Engineering, or a related field
  • 2+ years of experience in software engineering and applied AI (or equivalent)
  • Strong proficiency in Python and modern AI frameworks
  • Proven experience delivering production-grade AI systems
  • Solid understanding of deep learning architectures (CNNs, transformers)
  • Experience with system-level design, debugging, and performance optimization

Domain-Specific Experience (One or More)

LLM / Agentic Systems:

  • Experience working with Large Language Models (LLMs)
  • Building agentic workflows, reasoning systems, or AI-driven applications
  • Deploying and optimizing open-source LLMs for inference

Computer Vision:

  • Strong background in computer vision and deep learning
  • Hands-on experience with detection, segmentation, and tracking models
  • Experience with video pipelines and real-time or near-real-time systems

Nice to Have

  • Experience with NVIDIA technologies (CUDA, TensorRT, Triton, NVIDIA NIM)
  • Experience with GPU performance profiling and optimization
  • Background in high-performance or low-latency systems
  • Experience mentoring engineers or leading technical initiatives

What We Offer

  • Ownership of complex, high-impact AI projects
  • Work with cutting-edge NVIDIA GPU and AI technologies
  • Influence over architecture, tooling, and technical direction
  • A collaborative, engineering-driven culture
  • Opportunities for technical leadership and professional growth
  • Real-world, production-scale AI challenges


Full time Job

Location: Haifa, Hybrid

We at Deloitte believe that diversity and inclusion among our people is a critical component of our success and that is why we cultivate an organizational culture that contains and embraces diversity in all its forms.

Deloitte