דרושים » תוכנה » MLOps Team Lead

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.

We are looking for a Staff Architect, Data & AI Infra to shape, build, and scale the infrastructure that powers our 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 our 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 our 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.

We are looking for an experienced Data Infrastructure Team Lead to lead our Data Infrastructure team. In this role, you will have formal people-management responsibility for a multidisciplinary team that builds, productionizes, and improves big data and analytics infrastructure. You will be responsible for team delivery, combining technical depth, agile leadership, and an AI-first mindset to help the team build reliable systems, improve how it works, and continuously raise its engineering standards.

Location: Ramat Gan (Bursa area), Israel - Hybrid model

What will you do?

Lead, manage, and develop a data infrastructure team of approximately 5-7 people.
Take responsibility for team delivery, including planning, prioritization, execution, and continuous improvement.
Lead agile ways of working, including scrum-based delivery practices.
Guide the design, productionization, and ongoing improvement of big data and analytics infrastructure.
Partner closely with cross-functional stakeholders across technical, scientific, and business interfaces.
Help the team adopt AI-first engineering practices, including automation and AI-assisted development workflows.
Drive improvements in team processes, technical quality, delivery predictability, and collaboration.
Support architectural and technical decisions across cloud infrastructure, data pipelines, orchestration, and production systems.
Create an environment where team members can grow, contribute, and improve together.

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.

As the Software Group Lead, you will be the primary architect and execution lead for a cutting-edge missile interceptor system. This is a high-stakes executive role requiring a rare blend of low-latency embedded engineering and high-level Command & Control (C2) orchestration. You will be responsible for building a multi-disciplinary software team from the ground up, defining the software lifecycle, and ensuring the seamless integration of missile subassemblies with ground-based mission control.
We are looking for a "builder" mentality, capable of switching between high-level architectural strategy and driving end-to-end delivery from concept to field deployment.
Why Join us?
This is a unique opportunity to be at the heart of a defense-tech startup during its most exciting growth phase!
The SW Group Lead will report directly to the CTO and act as a member of the company's leadership.
Responsibilities
Team Leadership: Recruit, mentor, and manage a high-performance team of embedded, full-stack, and GNC (Guidance, Navigation, and Control) engineers.
System Architecture: Design the end-to-end software stack, from real-time operating systems (RTOS) on the interceptor to the distributed microservices of the ground station.
Execution & Integration: Oversee the development of flight software, sensor fusion algorithms, and secure communication protocols between the interceptor and C2.
AI-Driven SDLC: Implement and champion the use of modern AI coding tools (GitHub Copilot, Cursor, Claude Code, etc.) across the entire software lifecycle to accelerate development cycles without compromising safety-critical standards.
Strategic Oversight: Align software milestones with hardware integration, testing phases (HIL/SIL), and field trials.
Key Interfaces: Works closely with Hardware Engineering leads (mechanical, electrical, GNC), Program Management, and Systems Engineering teams internally; externally interfaces with defense customers, government program offices, and key technology vendors.

As an Engineering Manager in the data department, youll build and scale our data platform and data apps that powers our business insights. Youll design and implement robust pipelines to process billions of daily records, leveraging cutting-edge cloud technologies to transform data into actionable intelligence.

If youre passionate about data engineering and driving business growth through insights, wed love to hear from you!

Responsibilities
Lead and grow Data Engineering and Machine Learning teams in a high-scale environment (tens of billions of events per day).
Own the design and evolution of a self-service data platform enabling internal teams to easily build, ship, and consume data products.
Architect and scale batch and streaming pipelines powering core business and ML use cases.
Drive production ML systems end-to-end (recommendation, ranking, prediction) with direct business KPI impact.
Ensure reliability, scalability, and observability of large-scale data and ML systems in production.

We are a fast-growing cybersecurity startup redefining how organizations protect themselves. Our Data Team is at the heart of that mission - powering everything from security insights to customer-facing intelligence. We are looking for a Software Engineer to help design and develop the core services and applications that drive our data capabilities. In this role, you will build high-quality, scalable software; contribute to the architecture of our next-generation data systems; and collaborate with research and product teams to turn cutting-edge ideas into production-ready features.
Responsibilities:
Design, develop, and maintain scalable backend services and components that power our data workflows, analytics, and product features.
Build high-quality internal tools and applications that improve engineering workflows and enable data-driven development across the organization.
Contribute to the architecture and evolution of our new data platform with a strong focus on clean design, testability, maintainability, and performance.
Collaborate closely with security researchers, analysts, and product managers to translate innovative cybersecurity concepts into reliable, production-ready software.
Apply engineering best practices across the stack - including code quality, testing, observability, versioning, and documentation - to ensure system robustness as we scale.

We are looking for an ML Infra Engineer to play a central role in evaluating, and deploying our AI models. You will own and evolve our benchmarking and evaluation capabilities for foundation models and multimodal systems, while also working closely with modeling teams to support model development, iteration, and validation. This role sits at the intersection of software engineering, model understanding, and applied AI, with broad influence on how models are built, compared, and improved across the organization.

This is NOT a core algorithmic research role - but rather, a role focused on building out the ML engineering infrastructure for the evaluation and deployment of models.

Location: Ramat Gan, Israel (hybrid model)

What will you do?
Own & Evolve Benchmarking - Design, build, and maintain our benchmarking suite for foundation models and multimodal AI systems.
Define Core Abstractions - Create clean, extensible abstractions and APIs for datasets, tasks, models, metrics, and evaluation workflows.
Develop Metrics & Evaluations - Implement metrics that capture predictive performance, biological relevance, and multimodal alignment.
Support Model Development - Work closely with AI scientists and data scientists to integrate new models, tweak architectures, and enable rapid, fair iteration.
Bring in New Models & Baselines - Add external and internal models to benchmarks and ensure meaningful comparisons.
Explore Data When Needed - Dive into data and results to debug evaluations, understand model behavior, and unblock modeling work.
Enable Rigor & Reproducibility - Ensure evaluations are consistent, well-versioned, and trustworthy over time.

We are seeking an exceptional senior-level Python engineer to join a small team working on complex data pipelines, AI/ML systems, and cutting-edge software solutions.
This role will be responsible for managing technical objectives, providing technical leadership, and maintaining a hands-on approach to development. The ideal candidate will work closely across teams within as part of our business-facing technology organization.
A successful candidate will possess deep expertise in Python development, data engineering, software architecture, and design principles. They should be able to mentor junior team members, conduct code reviews, and drive architectural decisions. Experience with AI and large language models (LLMs) is highly desirable.

You will build globally distributed, fault-tolerant, and highly scalable identity threat detection systems that analyze billions of authentication events per day to detect sophisticated Active Directory attacks, credential theft, and lateral movement across hybrid and multi-cloud (Azure/Entra, Okta, AWS) environments. You'll design, lead, and implement the next generation of our Identity Protection detection platform - evolving it from on-prem appliances toward cloud-native, event-streaming microservices.

What You'll Do

Design and implement real-time detection rules and pipelines over high-throughput Kafka event streams, maintaining sub-second detection latency at massive scale.

Build the pluggable detection engine and rule framework that turns raw authentication telemetry into indicators, and indicators into enriched, customer-facing alerts.

Develop machine-learning and behavioral-anomaly models, and integrate LLM-based detection reasoning (e.g. AI-driven severity scoring) into production detection flows.

Translate security research into production-grade detections, partnering with security researchers who guide you on the threat landscape.

Own detections in production: observability, latency SLOs, safe per-customer rollouts (feature-flag-gated), and incident response for the detection pipeline.

Work across a polyglot stack - Python for detection logic and ML, Go for the high-performance streaming services, Java for backend alert management.


This position is based in our Ramat-Gan, Israel office and requires strong leadership presence and ability to work closely with cross-functional teams.