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Location: Jerusalem
Job Type: Full Time
we are looking for a Machine Learning Software Engineer, who will be challenged by bridging the gap between cutting-edge machine learning research and robust production deployment.
In this position, you will combine software engineering expertise with machine learning deployment knowledge, responsible for taking our algorithms and developing robust production solutions that serve them at scale.
The work at algorithms department is fast-paced and requires staying ahead of the curve with the latest engineering solutions and best practices adopted across the ML community, while staying informed about emerging solutions in both computer vision and NLP domains and understanding the specific problems they address.
What will your job look like:
Your role will include developing production deployment systems for classical and machine learning algorithms from research and building robust, scalable inference pipelines.
You will develop primarily in Python and infrastructure tools (Kubernetes, Docker, etc.), taking part in both maintaining existing deployment systems and developing new production capabilities.
Finally, you will need to learn and implement new deployment technologies and best practices that can address emerging production challenges as they arise, while staying current with the latest MLOps and inference optimization techniques.
Requirements:
B.Sc. in Computer Science, Software Engineering, or related technical field.
2+ years of experience in production software development, preferably in ML deployment.
Strong problem-solving skills and ability to tackle complex, real-world production challenges.
Proficiency in Python and experience with containerization and orchestration technologies (Docker, Kubernetes)- advantage.
Hands-on experience with model serving frameworks and inference optimization- advantage.
Background in distributed systems and cloud infrastructure- advantage.
This position is open to all candidates.
 
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Location: Jerusalem
Job Type: Full Time
we are looking for a Senior DevOps Engineer - ML Platform.
AI Engineering's ML-Platform team goal, is to deliver a modern infrastructure and solutions to enhance Algorithm development life cycle and shorten our delivery times. We are an independent group, consisting of excellent and experienced engineers with diverse skills in algorithms, software, and infrastructure. We strive to implement a DevOps culture allowing our engineers to easily collaborate on large-scale products.
We develop cross-company products that enable the research and deployment of state-of-the-art algorithms.
What will your job look like?
Build and maintain infrastructure for large‑scale AI and HPC workloads across on‑prem and cloud environments
Operate and enhance our multi‑cloud, multi‑cluster scheduling platform
Develop automation, tooling, and platform services und Bash
Troubleshoot complex issues across the stack: compute, networking, storage, orchestration, and distributed systems
Improve reliability of critical systems
Collaborate with ML, data, and backend teams to support evolving platform needs
Drive best practices in CI/CD, infrastructure-as-code, and system design
Participate in on‑call rotations for critical infrastructure components
Requirements:
10+ years of hands‑on experience in DevOps, SRE, systems engineering, or similar roles
Linux knowledge, including debugging, performance tuning, ana system internals
Proven experience working with HPC environments, large clusters, or high‑performance compute systems
Solid experience with Kubernetes (EKS or similar managed K8s services)
Knowledge of infrastructure‑as‑code tools(Terraform, Helm, etc.)
Hands‑on experience with:
PostgreSQL or similar relational databases
Elasticsearch or similar search/indexing systems
Prometheus/Thanos/Grafana or similar observability stacks
RabbitMQ or similar messaging systems
Strong proficiency in Bash, networking fundamentals, and debugging distributed systems.
Experience investigating complex issues across compute, storage, networking, and orchestration layers
Advantages:
Experience with multi‑cloud architectures
Experience with workflow orchestration tools such as Argo Workflows (or similar systems like Airflow, Prefect, Flyte)
Familiarity with GPU scheduling, AI/ML pipelines, or data‑intensive workloads
Background in large‑scale distributed systems or platform engineering
Ability to write production‑quality Go (Golang) code
This position is open to all candidates.
 
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31/12/2025
Location: Jerusalem
Job Type: Full Time
What you will be doing
As the ML Platform Engineering Manager, you'll lead a team of backend engineers building our company's AI infrastructure. Your team bridges research and production, taking cutting-edge ML and generative AI models from our research teams and turning them into scalable systems that power AI features for millions of users.
The ML Platform team owns the complete AI pipeline - from research prototype to production deployment. You'll build and maintain a high-performance inference platform that serves models at scale, enabling faster research iteration and seamless user experiences across our apps.
This role requires both technical leadership and people management skills. You'll make key architectural decisions for complex distributed systems while growing and mentoring your engineering team. Success means delivering reliable, scalable AI infrastructure that supports our rapid growth in a fast-paced environment.
Requirements:
6+ years of backend systems experience with 1-3 years in engineering management / strong technical leadership experience (tech lead, senior engineer leading platform initiatives)
Proven track record of building and scaling platform systems, with demonstrated ownership of complex technical projects from design to production
Solid experience with cloud-based distributed systems, including architecture decisions, deployment strategies, and operational practices
Strong backend development skills with focus on API design, system scalability, and observability/monitoring
Experience mentoring engineers and driving technical excellence within fast-growing teams
Excellent communication skills with ability to collaborate across engineering, product, and other technical teams
Interest in or exposure to ML model serving, GPU infrastructure, or ML platform tooling - preferred but not required
Comfortable working in a distributed team environment with flexibility across time zones
B.Sc. in Computer Science or equivalent technical background.
This position is open to all candidates.
 
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