דרושים » ניהול ביניים » Senior Python Software Engineer

Our group is responsible for building software enabling both the large-scale quantitative research operations that drive our platform and the production of our portfolio. The team is currently embarking on a multi-year journey to provide a powerful, scalable, and efficient platform to drive the firms next decade of growth. We are looking for someone who can own some of the unique technical challenges inherent in the problem and who can bring solid experience and perspective to the team.

We are looking for a skilled and motivated Senior Python Backend Engineer to join our Surveillance Engineering team. The ideal candidate will have a deep understanding of software development and technical expertise. This is a hands-on role for someone who wants both depth and ownership: youll design and build complex components, drive architecture and technology-selection decisions, and stay close to the product in production. The position requires strong collaboration and communication skills as you will be working alongside engineers, data scientists, and domain experts.

About the Surveillance Group: The Surveillance group at our company builds and operates advanced AI solutions. Our team is composed of engineers, data scientists and subject matter experts who work together to deliver a high-quality, production-ready Surveillance product. We push the boundaries of what is possible and measure ourselves by the impact we deliver to our clients.

Lets get down to business:

What Youll Do:

Design, build and maintain the software infrastructure and solutions that make up our Surveillance pipeline, combining classic machine learning models and GenAI models with complex business logic and analytical components.
Own significant architecture decisions and evaluate and select the technologies we build on.
Solve complex engineering problems end to end, from investigation and design through implementation and rollout.
Collaborate with engineers, data scientists and subject matter experts to deliver high-quality, production-ready that are fully integrated and scalable.
Support the product in production: investigate issues, improve observability, and make the system easier to run.
Build and operate services in containerized environments (Docker, Kubernetes) on AWS.
Hold a high engineering bar: meaningful unit tests, solid CI/CD following best practices.
Keep current with developments in software engineering and production ML infrastructure.

we are looking for a MLOps Team Lead.
As an MLOps Team Leader , you will own our AI infrastructure and backend engineering efforts, leading a team at the intersection of systems design and machine learning to build the engineering systems that turn Deep Learning and Computer Vision research into reliable, scalable production features.
What Youll Be Doing:
Lead MLOps Engineering: Own the roadmap and execution for a team of backend and AI infrastructure/MLOps engineers, setting technical direction, removing blockers, and holding the bar on delivery quality.
Build Production AI Systems: Design and implement production-grade, end-to-end AI solutions, including agentic workflows, that integrate Deep Learning models and Computer Vision algorithms into real features. Own the offline experimentation and validation layer, including POC environments that let the Algo team move from research to production confidently.
Architect Data Platforms: Drive the design and implementation of scalable data platforms and pipelines that power AI capabilities reliably and with an eye on cost and scale.
Cross-functional Collaboration: Work closely with the Algorithms and Data teams to tackle complex, real-world problems, translating research into shippable, maintainable systems.
Elevate Engineering Standards: Champion Software Engineering and System Design best practices across the group, introducing the right methodologies, tooling, and culture of craft.
Who You Are:

Were looking for an AI Software Engineer to own the RL Gym platform end-to-end: from architecting multi-site web environments that simulate real-world attack surfaces, to optimizing our in-house orchestration harness (AgenticVerse) for high-performance delivery into customer training pipelines.
This is a builder role. Youll lead a small team (including a dedicated web environments engineer), operating with high autonomy, moving fast from concept to working prototype to production system. Youll interact directly with customer engineering teams to understand their infrastructure constraints and deliver environments that meet their scale and reliability requirements.
Why this role
This is one of the few roles in the industry where your code directly influences how the next generation of AI models are trained. Youll be at the center of advancing AI safety, building systems that the worlds top labs depend on to make their models more robust. The work is technically deep, the problem space is genuinely novel, and the field is moving faster than any team can keep up with alone. Theres no playbook. Youll write it.
What youll do:
Platform & performance
Own and evolve AgenticVerse, our in-house orchestration harness that provisions and manages RL environments at scale. Focus on performance: low-latency provisioning, high concurrency, minimal overhead per environment instance
Design and build isolated, reproducible web environments using Firecracker microVMs or Docker containers
Architect multi-site scenarios (3-4 interconnected web applications per task) with rich interactions: drag-and-drop, file uploads, authentication flows, LLM-in-the-loop components
Implement deterministic verifiers that evaluate agent behavior with zero ambiguity
Customer delivery
Work directly with engineering teams at leading AI labs to integrate RL Gym environments into their training and evaluation pipelines
Translate customer specs into working environments, iterating rapidly on feedback
Own the technical relationship: SLAs, API contracts, integration architecture
Adapt environment delivery formats to cus tomer infrastructure (real-time API calls vs. offline batch, managed vs. raw artifacts)
Build customer-facing UIs when needed (dashboards, environment configuration portals, monitoring interfaces)
Rapid prototyping
Take ambiguous problem descriptions and produce working prototypes within days, not weeks
Validate new environment types, interaction patterns, and verifier approaches quickly
Build internal tooling that accelerates scenario authoring and testing.

we are looking for a MLOps Engineer.
As an MLOps Engineer, you will work at the intersection of backend engineering and machine learning, building the engineering systems that turn Deep Learning and Computer Vision research into reliable, scalable production features used by hundreds of thousands of families.
What you'll be doing -
Build Production AI Systems - Design and implement backend services and end-to-end AI solutions that integrate Deep Learning models, Computer Vision algorithms, and GenAI into real features.
Power Experimentation and Validation - Contribute to the offline experimentation and validation layer, including POC environments that let the Algo team move from research to production confidently.
Develop Data Pipelines - Build and maintain scalable data pipelines and big-data solutions that feed AI capabilities reliably and with an eye on cost and scale.
Own What You Ship - Take features end-to-end within your squad, from planning and design through implementation, deployment, and monitoring in production.
Cross-functional Collaboration - Work closely with the Algorithms and Data teams to tackle complex, real-world problems, helping translate research into shippable, maintainable systems.
Backend Guild Engagement - Actively contribute to a backend guild that drives Software Engineering and System Design best practices, guidelines, and standards across the R&D team.

Required Senior Software Engineer, Infrastructure, Cloud
About the job
Our software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to our needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.
As a Platform Engineer on this team, you will build, operate, and scale the mission-critical cloud infrastructure that powers Chronicle Security Orchestration, Automation and Response (SOAR) at scale. This is a heavy infrastructure operations and automation role. You will take autonomous ownership of complex operational challenges-from administering advanced Kubernetes (GKE) clusters to building sophisticated observability pipelines-ensuring the highest level of Enterprise-grade reliability and security.
You will not simply implement others' ideas, you will be expected to scope operational challenges, write robust Infrastructure as Code (IaC), and transform manual toil into software-driven platforms in close partnership with product development teams.
Responsibilities
Own all aspects of your immediate infrastructure area, leading the design and maintenance of platform tooling, deployment pipelines, and cloud systems that enhance the reliability and performance of Chronicle SOAR.
Administer, operate, and troubleshoot advanced Kubernetes (GKE) clusters and onboard new infrastructure features at scale.
Develop and manage infrastructure configurations and automation policies using Go to ensure secure, consistent, and auditable management of GCP resources.
Design and implement sophisticated monitoring, logging, and tracing solutions (e.g., Prometheus, Grafana) and manage Service Level Objectives (SLOs)/Service Level Indicators (SLIs).
Act as a point of contact for cross-functional partners. Analyze past incidents and proactively develop software solutions to prevent recurrence. Build automation to reduce manual toil and accelerate incident resolution.

Required Senior Data Engineer
About the role:
You will specialize in designing and building world class, scalable data architectures, ensuring reliable data flow and integration for groundbreaking biotechnological research. Your expertise in big data tools and pipelines will accelerate our ability to derive actionable insights from complex datasets, driving innovations in improving patients outcome and in delivering life savings treatment solutions.
In this role, you will work closely with data scientists, AI/ML engineers, architect and other cross-functional teams to understand their data needs and requirements. You will also be responsible for ensuring that data is easily accessible and can be used to support data-driven decision making.
Location: Ramat Gan, (Hybrid model)
What will you do?
Design, build, and maintain data pipelines that ingest, transform, and load noisy, heterogeneous biological data at scale - from single-cell sequencing, genomic, and clinical sources - across databases, APIs, and flat files
Enhance our data warehouse system to dynamically support multiple analytics use cases
Implement and productize complex scientific and computational algorithms as scalable, production-grade pipeline components
Drive our data infrastructure toward becoming AI-native, enabling AI/ML systems and agents to reliably query, reason over, and act on our data
Implement data governance policies and procedures to ensure data quality, security, and privacy
Collaborate with ML and AI scientists and other cross-functional teams to understand their data needs and requirements
Drive team capability growth by championing an AI-first SDLC, mentoring data engineers on AI-assisted development practices and tooling
Develop and maintain documentation for data pipelines, processes, and systems
Requirements
We will only consider senior data engineers that have demonstrated strong system design skills combined with an extensive background working with data orchestration, data warehousing and ETL tools.

Required Senior ML Data Engineer
About the team:
The AI Engineering group builds modern infrastructure and solutions that improve how algorithms are developed.
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 are looking for a Senior AI Software Engineer.
As a Senior AI Software Engineer, you'll help build that platform end to end - the agents, connectors, automation, and infrastructure that let the entire company unlock major productivity gains. You'll be designing and shipping AI that takes real work off people's plates, turning manual processes into automated ones, and building the systems that let teams do their best work faster.
Developing our use of Claude and Databricks - currently the backbone of that internal AI stack - is a key part of the mandate. Every one of our 500+ team members already uses Claude and BI in Databricks for analysis, automation, and research, and demand for deeper integrations is growing faster than our R&D team can deliver. You'll be tasked with driving these capabilities and impact to the next level - from surface-level usage to genuinely agentic, high-leverage workflows embedded across the business.
This is a hybrid role: part platform engineer, part internal-facing integration lead. You'll report to the COO and partner across AI Operations, R&D, Data Science, GTM, and other teams, owning the path from integration request to production-grade system. You'll also help build the triage and review process so the broader org can self-serve safely.
If you want to build the AI backbone of a fast-moving company - and see your work adopted by hundreds of people within days rather than quarters - this is that role.

We are actively seeking a seasoned and passionate Senior Python Software Engineer to play a pivotal role in shaping the technological landscape of our product. As a key member of our R&D team, you will be responsible not only for delivering top-tier code quality but also for driving innovation, implementing best practices as we navigate the ever-evolving startup environment.

What Youll Do
Develop high-quality, robust Python code that meets and exceeds industry standards.
Lead initiatives to continuously review and elevate internal code quality standards.
Participate actively in decision-making processes, contributing to architectural design and technology research.
Tackle diverse and complex problems related to scale, performance, and business logic.
Participate in on-call rotations, responding to production incidents, troubleshooting issues, and ensuring system reliability and availability.