דרושים » הנדסה » MLOps Team Lead

We are hiring an Engineering Manager to own and grow the Data Science group - the R&D team behind our company's security and safety AI models and the data platform that powers them. You will lead a multidisciplinary team of ML engineers, data scientists, and software engineers who ship real-time inference at scale, automated red-teaming of GenAI systems, and the Databricks/Spark data platform underneath. This is a hands-on people-leadership role: you set technical direction, are accountable for delivery and quality, and you build and grow the team.
What your team owns
The group is responsible for a large Python + Rust + PySpark monorepo (dozens of production services and shared libraries) spanning three connected domains:
1. Content-moderation inference at scale
Real-time, multi-tenant detection across text, image, video, and audio - hate speech, CSAM, nudity, child grooming, extremism, PII, prompt injection, age estimation, and more - served through an in-house ActiveServe framework over NVIDIA Triton and a Rust detection monolith, on latency-sensitive, SLA-bound, customer-facing traffic with per-customer custom models.
2. GenAI safety & red-teaming
Automated red-teaming that attacks customers' LLM applications with a research-driven attack taxonomy and measures attack-success rate, alongside the defensive side - LLM-as-judge escalation to cut false positives and the tooling that authors and refines moderation policies - built on a multi-provider LLM foundation (Bedrock, Anthropic, OpenAI, Gemini, xAI Grok) and forming our company's leading edge into agentic-AI safety.
3. Data platform & MLOps
An end-to-end lakehouse and MLOps stack on Databricks - bronze/silver/gold ingestion, PySpark pipelines, and model training, versioning, and promotion through MLflow / Unity Catalog into Triton serving - with the performance-critical hot paths engineered in Rust (PyO3/maturin) for sub-millisecond, high-QPS matching and detection.
What you'll do
Lead and grow the team - mentor ML engineers, data scientists, and software engineers, and own hiring, onboarding, 1:1s, career development, and performance.
Set direction and deliver - set technical direction and standards, turn company and product goals into a prioritized roadmap, and own the quality, reliability, and delivery of the systems above across parallel workstreams.
Champion excellence and partnership - stay hands-on to review designs and unblock the team, drive engineering excellence (testing, observability, CI/CD, on-call, cost/latency), keep the team at the state of the art in ML, LLMs, and GenAI safety, and partner with Product, Platform, and GenAI-safety stakeholders.
Leadership competencies
People-first: builds trust, grows engineers, and creates a healthy, inclusive, high-ownership culture.
Outcome-oriented: drives clarity, sets priorities, and delivers under ambiguity without micromanaging.
Technical credibility: earns the team's respect through sound judgment on architecture and trade-offs.
Systems thinker: balances short-term delivery against long-term platform health, cost, and tech debt.

We are seeking an experienced and highly motivated Team Lead to lead our Data Infrastructure team. This role is responsible for managing a team of engineers while driving the design, scalability, reliability, and operational excellence of the companys core data platform.
The ideal candidate combines strong technical expertise in distributed systems and data technologies with proven leadership capabilities, strategic thinking, and the ability to lead complex initiatives end-to-end - from initial design and planning through implementation, deployment, and production ownership.
Key Responsibilities:
Lead, mentor, and develop a team of Data Infrastructure engineers, fostering a culture of ownership, collaboration, and continuous improvement
Define and execute the technical roadmap for the organizations data infrastructure platform
Oversee the architecture, scalability, reliability, and performance of large-scale data systems and pipelines
Define and drive data quality standards, monitoring, and validation processes to ensure trust and reliability across the data platform
Partner with engineering and product teams to enable scalable data foundations for analytics, machine learning, and AI-driven initiatives
Lead cross-functional technical initiatives end-to-end, including requirements gathering, architecture design, implementation, deployment, and post-production ownership
Partner closely with cross-functional teams including Data Engineering, Analytics, Backend Engineering, DevOps, and Product Management
Drive operational excellence through monitoring, observability, automation, and incident management best practices
Ensure high availability and stability of critical production systems
Lead technical design discussions, architecture reviews, and engineering planning processes
Establish and promote engineering standards, development best practices, and quality assurance processes
Manage project prioritization, resource allocation, and timely delivery of strategic initiatives
Support recruitment, onboarding, performance management, and career development of team members
Evaluate emerging technologies and recommend improvements to the data platform ecosystem

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.

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 hiring an Engineering Manager to own and grow the Data Science group - the R&D team behind Alice's security and safety AI models and the data platform that powers them. You will lead a multidisciplinary team of ML engineers, data scientists, and software engineers who ship real-time inference at scale, automated red-teaming of GenAI systems, and the Databricks/Spark data platform underneath. This is a hands-on people-leadership role: you set technical direction, are accountable for delivery and quality, and you build and grow the team. What your team owns The group is responsible for a large Python + Rust + PySpark monorepo (dozens of production services and shared libraries) spanning three connected domains: 1. Content-moderation inference at scale Real-time, multi-tenant detection across text, image, video, and audio - hate speech, CSAM, nudity, child grooming, extremism, PII, prompt injection, age estimation, and more - served through an in-house ActiveServe framework over NVIDIA Triton and a Rust detection monolith, on latency-sensitive, SLA-bound, customer-facing traffic with per-customer custom models. 2. GenAI safety & red-teaming Automated red-teaming that attacks customers' LLM applications with a research-driven attack taxonomy and measures attack-success rate, alongside the defensive side - LLM-as-judge escalation to cut false positives and the tooling that authors and refines moderation policies - built on a multi-provider LLM foundation (Bedrock, Anthropic, OpenAI, Gemini, xAI Grok) and forming Alice's leading edge into agentic-AI safety. 3. Data platform & MLOps An end-to-end lakehouse and MLOps stack on Databricks - bronze/silver/gold ingestion, PySpark pipelines, and model training, versioning, and promotion through MLflow / Unity Catalog into Triton serving - with the performance-critical hot paths engineered in Rust (PyO3/maturin) for sub-millisecond, high-QPS matching and detection. What you'll do
* Lead and grow the team - mentor ML engineers, data scientists, and software engineers, and own hiring, onboarding, 1:1s, career development, and performance.
* Set direction and deliver - set technical direction and standards, turn company and product goals into a prioritized roadmap, and own the quality, reliability, and delivery of the systems above across parallel workstreams.
* Champion excellence and partnership - stay hands-on to review designs and unblock the team, drive engineering excellence (testing, observability, CI/CD, on-call, cost/latency), keep the team at the state of the art in ML, LLMs, and GenAI safety, and partner with Product, Platform, and GenAI-safety stakeholders. Leadership competencies
* People-first: builds trust, grows engineers, and creates a healthy, inclusive, high-ownership culture.
* Outcome-oriented: drives clarity, sets priorities, and delivers under ambiguity without micromanaging.
* Technical credibility: earns the team's respect through sound judgment on architecture and trade-offs.
* Systems thinker: balances short-term delivery against long-term platform health, cost, and tech debt.



About Alice:
Alice is a trust, safety, and security company built for the AI era. We safeguard the communicative technologies people use to create, collaborate, and interact- whether with each other or with machines. In a world where AI has fundamentally changed the nature of risk, Alice provides end-to-end coverage across the entire AI lifecycle. We support frontier model labs, enterprises, and UGC platforms with a comprehensive suite of solutions: from model hardening evaluations and pre-deployment red-teaming to runtime guardrails and ongoing drift detection. Alice is widely considered a global leader in online safety and AI security. We have some of the most forward-thinking and passionate minds in the world working to safeguard over 3 billion users across the largest AI and tech platforms. If you're creative an

Join our mission to build and scale the engineering platform behind a leading SaaS cybersecurity solution trusted by enterprises worldwide.
We are looking for a passionate DevOps Group Lead. You'll lead a strategic engineering organization responsible for the platforms, infrastructure, and automation that power our software delivery lifecycle. You'll manage four Team Leaders and their engineering teams, driving innovation across CI/CD, Kubernetes, AWS, developer platforms, and cloud operations while enabling fast, secure, and reliable software delivery.
This is a leadership role for someone who combines strong technical expertise with exceptional people leadership and a passion for building high-performing engineering organizations.
How will you make an impact?​
Lead, mentor, and develop 3 Team Leaders and their engineering teams, fostering a culture of ownership, collaboration, and continuous learning.
Define and execute the DevOps and Platform Engineering strategy supporting a large-scale SaaS cybersecurity platform.
Own the architecture, scalability, availability, security, and operational excellence of our cloud infrastructure and engineering platforms.
Drive the evolution of modern CI/CD pipelines, Kubernetes platforms, Infrastructure as Code, GitOps, and developer self-service capabilities.
Partner closely with Engineering, Product, Security, Architecture, and R&D leadership to accelerate software delivery while maintaining the highest standards of security and reliability.
Lead cloud-native initiatives with a strong focus on AWS, Kubernetes, automation, and platform standardization.
Establish engineering metrics, operational KPIs, SLOs, and continuous improvement initiatives across the organization.
Champion DevSecOps best practices and embed security into every stage of the software delivery lifecycle.
Lead organizational planning, hiring, budgeting, prioritization, and execution while supporting the growth and development of future engineering leaders.

You are the guardian of our source of truth. our company runs on a stack of 25+ interconnected SaaS tools, Salesforce, HubSpot, NetSuite, Workato, Gong, Outreach, IronClad, Okta, and more, and when that stack misfires, every team in the company feels it. Your job is to make sure it doesnt.
But ownership isnt just maintenance. As we scale our GenAI capabilities across the company, the quality of our core systems becomes the foundation everything else is built on. Youll be the one who ensures that when our GenAI Builder, our RevOps team, or our Finance team needs data, its clean, current, and accessible. Youre not a systems administrator. Youre the person who decides alongside with the business opener what the core stack looks like, how it grows, and how to build our agentic layer on top of it.
Youll manage a small team alongside a curated bench of specialized freelancers and subcontractors for deep technical work, and youll be the escalation point when things break. You report directly to the CFO.
What Youll Own
Core Stack Administration
Own the full tech stack: GTM (Salesforce, HubSpot, Outreach, Gong, ZoomInfo, Seismic), Finance (NetSuite, Stripe, Mesh, Opstream, Dokka, Expensify), Operations (JIRA, Notion, IronClad), and Infrastructure (Okta, Workato, Slack, Google Analytics) some of the tools will be co owned with IT
Ensure data integrity, system reliability, user access governance, and documentation across all platforms
Manage vendor relationships, license renewals, and cost optimization across the portfolio.

Required Algorithm Team Lead - Geometric Data Infrastructure
About the team:
The AV Sensing group is responsible for the critical and challenging task of object detection and scene comprehension using LiDAR and Radar sensors. Our team develops scalable infrastructure and algorithmic solutions for processing, validating, and understanding complex 3D sensor data.
What will your job look like:
Lead and mentor a team of ~5 Algo and Software Developers while remaining hands-on and closely involved in technical and algorithmic challenges.
Design and build scalable Python libraries, data workflows, validation and monitoring systems for spatial data.
Develop algorithms and geometric tools for 3D data processing, sensor calibration, coordinate transformations, and spatial relationships.
Build and maintain development infrastructure, including databases, dashboards, CI/CD pipelines, and automated documentation.
Take ownership of complex algorithmic challenges from research through production, while collaborating with cross-functional teams to integrate solutions into the broader system.

Were looking for a Director of Engineering Security to join our organization and lead multiple engineering teams building the next generation of secuirty products.
This is a hands-on engineering leadership role for someone who is a builder at heart, an experienced software engineering lead who loves to code, understands the full product and technical lifecycle, and knows how to scale both people and technology.
Youll work closely with the VP of AI and leaders across Product, Engineering, and other functions to turn ambitious ideas into high-quality products, while building and mentoring strong engineering teams.
What Youll Do:
Lead and manage multiple engineering teams, including managing and mentoring Team Leads.
Set the technical direction and execution standards across the teams.
Stay close to the technology and remain hands-on when needed- this is not a purely managerial role.
Drive the full engineering lifecycle, from architecture and design through development, deployment, and production.
Build and scale SaaS products in a fast-moving environment.
Partner closely with Product and other departments to translate business needs into technical execution.
Make pragmatic tradeoffs between long-term architecture and short-term delivery.
Encourage a culture of ownership, speed, experimentation, and continuous improvement.
Motivate engineers by connecting their work to the broader product and business goals.
Collaborate closely with managers and stakeholders across the organization.
Resolve conflicts effectively and build strong, collaborative relationships across teams.
Help identify technical risks and long-term implications while maintaining a strong focus on delivering results now.