לוח משרות דרושים

Required Senior ML Data Engineer
Jerusalem
Full time
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).

Required Senior ML Data Engineer
Ramat Gan
Full time
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 hiring an experienced, forward-thinking Automation Team Lead to lead the evolution of our quality engineering practices into an AI-driven testing ecosystem.

In this role, you will lead a global team of automation engineers while shaping the next generation of intelligent testing-leveraging AI/ML, generative AI, and data-driven approaches to dramatically improve quality, coverage, and delivery speed.

You will combine hands-on leadership with strategic thinking, driving both execution and innovation in how we validate complex security systems.

Responsibilities:
Lead, mentor, and grow a team of automation engineers, fostering engineering excellence and innovation.
Own the teams deliverables, quality outcomes, and technical direction.
Design and implement scalable automation frameworks using Java, Selenium, and modern tooling.
Drive adoption of AI-powered testing approaches, including:
Using LLMs to generate, refine, and prioritize test scenarios based on requirements, code, and production data.
Intelligent test maintenance and self-healing mechanisms.
Risk-based and predictive testing using data insights.
Define and execute an Agentic vision for QA, balancing practical impact with long-term innovation.
Integrate automation into CI/CD pipelines to enable fast, reliable releases.
Collaborate with R&D, DevOps, and Product to ensure high-quality delivery.
Review user stories and requirements with a quality-first mindset.
Support and guide manual testing where needed, evolving it toward automation and AI augmentation.
Establish and maintain QA standards, methodologies, and best practices.
Promote a shift-left quality strategy, including observability and production validation.
Work in an Agile (Scrum) environment.

we are looking for a Machine Learning Engineer II .
As a Machine Learning Engineer, you will work closely with experienced engineers and ML scientists to build scalable, production-grade GenAI applications. Your work will focus on designing, training, and deploying ML systems leveraging LLMs,, recommendation systems, and agent-based architectures, using state-of-the-art technologies. These solutions will directly power customer-facing experiences and play a key role in shaping the future of AI-driven travel products.
Key Job Responsibilities and Duties:
Deploying machine learning models: Design, develop and deploy in collaboration with scientists, scalable machine learning models and algorithms that provide content related insights and generative AI applications, ensuring scalability, efficiency, and accuracy.
Evaluating possible architecture solutions by taking into account cost, business requirements, emerging technologies, and technology requirements, like latency, throughput, and scale.
Generative AI Development: Contribute to the development of generative models such as GPT (Generative Pre-trained Transformer) variants or similar architectures for creative content generation, Q&A, chatbots, translation or other innovative applications.
Deployment and integration: Work closely with software engineers to integrate machine learning models into production systems. Ensure seamless deployment and efficient model inference in real-time environments. Collaborate with DevOps to implement effective monitoring and maintenance strategies.
Owning a service end to end by actively monitoring application health and performance, setting and monitoring relevant metrics and acting accordingly when violated.
Maintain clean, scalable code, ensuring reproducibility and easy integration of models into production environments, including CI/CD.
Collaborate with multidisciplinary teams: Collaborate with product managers, data scientists, and analysts to understand business requirements and translate them into machine learning solutions.

Due to a significant increase in product capabilities, alongside a rapidly growing customer base, we are expanding our engineering team. The system is evolving quickly, with a high volume of new features and increasing scale demands, requiring experienced engineers who can operate effectively in a fast-paced, production-critical environment. We are seeking a Senior backend Engineer with proven experience in large-scale systems and a deep understanding of performance and scalability to drive the evolution of our rapidly growing application. In this position, you will be part of delivering complex features while building the infrastructure required to support our product's enterprise-level growth. You will be involved in the entire lifecycle, from product requirements and technical design to implementation, for a complex system used by major global financial carriers. In this role, you will primarily act as a senior/lead backend engineer, taking ownership of the design and implementation of new features for a modern, growing product while also supporting the existing production system by investigating and resolving complex issues.
What youll do: Implement and deliver new features based on product requirements. Implement enhancement infrastructure to support the scale of the product. Participate in design discussions and conduct code reviews. Develop unit and integration tests. Assist in resolving Real-Time customer issues. Actively share knowledge with other team members to tackle technical challenges.
Position Intro:
Earnix is the premier provider of mission-critical, cloud-based intelligent decisioning across pricing, rating, underwriting, and product personalization. These fully integrated solutions provide ultra-fast ROI and are designed to transform how global insurers and banks are run by unlocking value across all facets of the business. Earnix has been innovating for insurers and banks since 2001 with customers in over 35 countries across six continents and offices in the Americas, Europe, Asia Pacific, and Israel.

We are looking for a Senior AI Engineer to join a strong and dynamic AI Engineering team. We are the focal point for AI initiatives, striving to constantly bring innovation and leverage AI capabilities across all company teams and products.
Today, AI is central to how we operate, across the entire organization. It allows us to move fast and release features at a rapid pace, empowers non-technical Forterians to utilize AI tools for increased efficiency, and provides the backdrop for much of the innovation currently occurring in the company.
If this kind of working environment sounds exciting to you, if you understand that Engineering is about building the most effective and elegant solution within a given set of constraints - consider applying for this position.
Why should you join us?
This is a great opportunity to be at the cutting edge of the AI revolution, helping to shape and build the AI platform for the future. Together, well build infrastructure for autonomous and interactive agents, enact AI guardrails and evaluation frameworks to ensure performance and safety, and implement state-of-the-art
AI and Agentic patterns.
This role presents a unique opportunity to enter the AI domain. For those with some experience in AI infrastructure, it offers the chance to grow within a team that is evolving us from the AI experimentation phase to building and leveraging AI-powered products.
What you will be doing:
Design, build, and maintain reusable AI capabilities - including models, tools, APIs, and platforms that power both internal and customer-facing solutions.
Develop and maintain our internal MCP server that easily and securely exposes our vast data stores to AI agents.
Create and implement robust evaluation frameworks and AI guardrails to safeguard our value and ensure model reliability.
Establish deep expertise and sustainable AI engineering practices.
Promote AI readiness and track adoption across the company to build lasting impact.
Build and optimize RAG (Retrieval-Augmented Generation) systems.
Take full ownership of projects: from gathering requirements from non-technical internal users to development, deployment, and operation.
Act as a consultant and advocate for AI engineering, helping other teams leverage the platforms and tools you build.
Partner with teams across to accelerate AI adoption and productization efforts.

We are seeking a highly skilled and motivated Electrical Validation (EV) Engineer and System Production/Testing/ATE Engineer to join our team. This position is crucial in supporting the design EV, development, and implementation of Automated Test Equipment (ATE) and production test systems.
The Electrical Validation Manager leads the electrical validation function across our company hardware platforms. This role owns validation strategy, methodology, lab infrastructure, and execution across all high-speed and control interfaces. The manager ensures robust electrical performance from early prototypes through production release and drives cross-functional alignment between design, SI, firmware, and manufacturing.
The role involves close collaboration with R&D, Quality, DevOps, and Contract Manufacturing (CM) teams to ensure the delivery of high-quality, reliable products.
Key Responsibilities
Define the electrical validation strategy for our company hardware platforms.
Own validation methodology for: High-speed Ethernet (100M-1600G), PCIe Gen1 to Gen5+, SerDes architectures (NRZ/PAM4), Control and management buses (I2C, SPI, RS-232, MDIO, etc.)
Establish structured validation plans aligned with hardware release milestones.
Build and manage a high-performance validation team.
Define lab architecture including: Equipment selection (oscilloscopes, BERTs, analyzers), Compliance platforms, Automation frameworks, Signal integrity validation environments
Drive early engagement with board design and SI teams to ensure design-for-validation.
Oversee: Compliance (IEEE, PCI-SIG, OIF), Interoperability testing, Stress and margin testing
Lead root cause analysis of electrical failures and systemic issues.
Support NPI, manufacturing bring-up, and yield improvement.
Develop automation and scalable validation methodologies.
Define validation documentation standards and sign-off criteria.
Collaborate with system architecture and software teams to ensure HW-SW integration robustness.
Manage external labs and certification processes where required.
Drive continuous improvement of validation coverage and efficiency.
Lead the full ATE development lifecycle from requirements definition to execution in production, including GUI design and Python scripting.
Develop and maintain boundary scan applications using JTAG Technologies.
Define and maintain test fixtures, including JIGs/Bed-of-Nails, etc. in collaboration with mechanical vendors.
Implement full test traceability systems for production yield and stability monitoring.
Collaborate with R&D and Quality teams to drive product quality and reliability improvements.
Provide onsite support at CM sites, including station setup, installation, training, maintenance, and debugging.
Perform in-depth failure analysis and troubleshooting at the system and component level.
Utilize and maintain a range of test equipment, including:
Work with various communication protocols: TCP/IP, Telnet, SSH, HTTP, SNMP, SFTP, SCP, FTP, RS232, GPIB, I2C, NI-VISA.
Support testing of embedded systems running on Linux platforms.

We are looking for an Engineering Platform Manager to lead one of our core engineering teams and drive the evolution of our container security platform at scale.

This is a high-impact leadership role combining people management, technical ownership, and strategic influence. You will lead a team building mission-critical systems, shaping both architecture and engineering culture, while working closely with Product, Security, and Platform teams.

In this role, you will also help drive the adoption of AI-driven systems and workflows, enabling smarter, more scalable, and more efficient engineering and customer-facing solutions.

If you are a hands-on leader who thrives in complex, high-scale environments and knows how to build strong teams and scalable systems - this role is for you.

What You Will Own?
Lead, mentor, and grow a team of engineers, fostering a culture of ownership, accountability, and technical excellence.
Own end-to-end delivery of core platform components - from design to production and long-term scalability.
Drive development of cloud-native microservices in large-scale production environments.
Lead architecture discussions, design reviews, and code quality standards.
Help define and design AI-driven solutions, workflows, and systems tailored to customer and product needs.
Design and implement internal tools and automation, including AI-powered workflows, to improve scalability and reduce manual work.
Partner closely with Product, Security, and cross-functional teams to align execution with business goals.
Step into strategic or complex customer engagements when needed and help drive them to success.
Drive data-driven decision making, continuous improvement, and innovation across the team.
Lead Agile execution, planning, and predictable delivery across the SDLC.
Improve performance, scalability, reliability, and observability across the platform.
Contribute to long-term engineering strategy and roadmap.
Stay hands-on when needed - guiding design, debugging, and system optimization.

We are looking for a senior, hands-on Security Operations Lead to build, mature, and operate detection, response, and corporate security capabilities. You will own the engineering, workflows, and processes that keep secure day-to-day, while continuously improving visibility, automation, and operational resilience across both corporate and production environments. This role requires a technical operator who can architect scalable detection and response pipelines, manage endpoint and identity security controls, streamline GTM security enablement, and collaborate across the company to reduce risk. You will balance strategic direction with hands-on execution-ensuring threats are identified quickly, incidents are handled effectively, and the organizations operational security posture remains strong as grows.
Responsibilities:
Own and mature Detection & Response program, including alerting, triage workflows, incident playbooks, and end-to-end response processes.
Build and maintain detection logic, integrations, and automation across logging, SIEM, EDR, cloud telemetry, and internal monitoring systems.
Lead incident investigations, coordinate response across engineering and business teams, and ensure clear communication and post-incident reviews.
Manage Corporate Security Program, including identity and access management, endpoint posture management, corporate data security controls, and DLP practices.
Oversee privileged access workflows and JIT access for corporate and production systems in alignment with least-privilege principles.
Partner with engineering teams to ensure production environments maintain strong security baselines, logging, and monitoring coverage.
Collaborate with GTM/Sales teams to support Security Enablement, including third-party security questionnaires, customer assurance needs, and auditor inquiries.
Build automation-first operational processes that reduce manual overhead and provide consistent, repeatable security outcomes.
Develop and refine detection and response runbooks, escalation paths, and cross-team coordination models.
Maintain and improve incident and operational metrics, dashboards, and KPIs to measure operational efficiency and threat coverage.
Drive the intake and prioritization of security operations requests through Jira and internal workflows.
Work closely with Product Security, Cloud/DevOps, and GRC to ensure shared visibility and aligned operational practices.
Identify operational security gaps, propose improvements, and lead implementation efforts across tooling, processes, and controls.
Promote a culture of proactive detection, fast response, and shared responsibility for organizational security.

We are looking for a driven and technically fluent Product Manager to join the MECI Group within the Software Engineering organization. The MECI Group enables Mobileyes algorithmic development flow by building scalable CI, build, test, and AI-driven tooling that supports the full development lifecycle. Our platforms allow Mobileye to scale efficiently and increase development velocity, while maintaining high standards of reliability, collaboration, and developer well-being. As a Product Manager in MECI, you will own and evolve core internal platforms that are foundational to how Mobileye develops, validates, and delivers algorithms. This role sits at the intersection of engineering, infrastructure, and developer experience, with broad impact across Algo, Validation, and Platform teams.
Why this role is unique
This role offers end-to-end ownership of products that are central to Mobileyes development ecosystem. You will lead products spanning development workflows, build and test systems, platform services, and AI-assisted tooling, operating across multiple teams and technical domains. The role combines strategic product leadership with hands-on collaboration in a highly technical environment, where scale, performance, and reliability are critical. Youll work closely with engineering leaders and cross-functional stakeholders to identify high-impact problems, define clear priorities, and drive delivery of solutions that measurably improve productivity, platform stability, and developer experience.
What your job will look like:
Own the product vision, strategy, and roadmap for key MECI platforms and capabilities
Drive cross-organizational alignment on platform priorities, architectural evolution, and adoption strategy
Translate needs from Algo developers, Validation teams, CI users, and Infrastructure stakeholders into clear product requirements, specifications, and user flows
Lead the full product lifecycle - from discovery and problem definition, through design and implementation, to rollout, monitoring, and continuous improvement
Maintain ongoing engagement with users to deeply understand workflows, pain points, operational constraints, and opportunities for improvement
Partner closely with engineering leadership on prioritization, scope, and delivery, balancing short-term needs with long-term platform health
Contribute to building a culture of collaboration, ownership, and sustainable development, with attention to developer well-being.

We are looking for a Senior Software Engineer to join a strong and dynamic AI Engineering team. We are the focal point for AI initiatives, striving to constantly bring innovation and leverage AI capabilities across all company teams and products.
Today, AI is central to how we operate, across the entire organization. It allows us to move fast and release features at a rapid pace, empowers non-technical Forterians to utilize AI tools for increased efficiency, and provides the backdrop for much of the innovation currently occurring in the company.
If this kind of working environment sounds exciting to you, if you understand that Engineering is about building the most effective and elegant solution within a given set of constraints - consider applying for this position.
Why should you join us?
This is a great opportunity to be at the cutting edge of the AI revolution, helping to shape and build the AI platform for the future. Together, well build infrastructure for autonomous and interactive agents, enact AI guardrails and evaluation frameworks to ensure performance and safety, and implement state-of-the-art
AI and Agentic patterns.
This role presents a unique opportunity to enter the AI domain. For those with some experience in AI infrastructure, it offers the chance to grow within a team that is evolving us from the AI experimentation phase to building and leveraging AI-powered products.
What you will be doing:
Design, build, and maintain reusable AI capabilities - including models, tools, APIs, and platforms that power both internal and customer-facing solutions.
Develop and maintain our internal MCP server that easily and securely exposes our vast data stores to AI agents.
Create and implement robust evaluation frameworks and AI guardrails to safeguard our value and ensure model reliability.
Establish deep expertise and sustainable AI engineering practices.
Promote AI readiness and track adoption across the company to build lasting impact.
Build and optimize RAG (Retrieval-Augmented Generation) systems.
Take full ownership of projects: from gathering requirements from non-technical internal users to development, deployment, and operation.
Act as a consultant and advocate for AI engineering, helping other teams leverage the platforms and tools you build.
Partner with teams across to accelerate AI adoption and productization efforts.

Required AI Engineering Team Lead - Applied AI Engineering Group
Tel Aviv Full-time
The Dream Job
It starts with you - a technical leader driven to build both the agentic AI platform and the engineering team behind it. You care about backend quality, platform reliability, and growing engineers through real ownership. We are AI-first across the board - every team builds and operates agents. You'll set the technical direction for the platform that makes this possible: agent orchestration frameworks, LLM gateways, evaluation infrastructure, tool-calling systems, and retrieval pipelines. Without this platform, agents don't ship - you own the layer that turns AI research into Sovereign AI products, deployed across cloud and on-prem environments. You stay close enough to the codebase to debug production incidents, unblock your engineers, and make sound architecture calls.
If you want to make a meaningful impact, join our mission and lead the team that builds the agentic AI platform driving Sovereign AI products - this role is for you.
The Dream-Maker Responsibilities
Architect and evolve the AI platform - agent orchestration, LLM gateways, context engineering pipelines, evaluation infrastructure, tool-calling systems, and retrieval pipelines - through RFCs, prototypes, and design reviews.
Lead and grow a small team of AI Engineers building the agent framework, production backend services, and AI platform infrastructure - hire, mentor, pair on hard problems, and raise the bar through hands-on code and design reviews.
Contribute to critical systems, debug production incidents, and maintain enough codebase context to make sound technical calls.
Own reliability across AI and agent services - set and enforce SLAs, build observability for non-deterministic systems, and harden tool execution environments for cost and security.
Set the standard for AI engineering practices - agent testing strategies, evaluation frameworks with human-in-the-loop oversight, retrieval quality benchmarks, and CI/CD for AI systems.
Work closely with ML Platform, Data Platform, DevOps, Data Science, and Product teams across the Applied AI Engineering group - ensure the AI platform evolves to serve teams building agentic workflows across the organization.
Measure and improve developer experience - deploy friction, onboarding time, CI turnaround - as seriously as system performance.

We are looking for a Director of Tech Strategy Labs to lead a group of architects to investigate and implement next-generation technologies, focusing on AI-native development, AI security, and enterprise SDLC, challenge existing solutions and standards, and harness your technology acumen to influence business strategy, innovation, and product roadmaps critical to the future of the Platform.
As a Director of Tech Strategy Labs, your work will influence thousands of companies using the Platform to drive their software release pipeline to create better value.
As a Director of Tech Strategy Labs at the CTO Office, you will...
Directly manage the CTO Office architects
Manage selected software development projects end-to-end with the highest quality
Explore, evaluate, and prototype new and differentiating products and capabilities enabled through emerging technologies, leading techniques, and contemporary patterns to create our next world-class solutions and experiences
Help identify research opportunities and drive innovation, coming from understanding our vision, the problems we are set to solve, the pain of our customers, the voice of market analysts and partners
Partner with community working groups and initiatives, such as those led under the CNCF
Maintain a deep understanding of the architecture of new and existing solutions under the Platform and how they interoperate
Work closely with the CTO, Product, Developers, Sales Engineers, Security, and Business Strategy teams to achieve common goals
Challenge existing architecture and solutions to improve customer experience, increase efficiency, reduce risk, increase resiliency, and improve performance
Provide technical leadership by synthesizing and communicating complex information being researched, and advance the topics mentioned above
Advocate clean code and clean architecture principles, and ensure documentation with proper technical specifications.

As the Team Lead, Technical Account Manager (TAM), you will lead a team responsible for delivering excellent technical account management, with a focus on guiding the seamless onboarding of new customers.
You will ensure your teams success in building strong customer relationships, addressing technical issues related to observability, and maintaining data-driven operational excellence. This role requires technical depth in logging, monitoring, and observability tools as well as strong leadership skills.
Key Responsibilities:
Leadership & Team Development:
Lead, mentor, and manage a team of TAMs to ensure successful customer onboarding and long-term success.
Develop KPIs for the team and track performance related to the onboarding experience, ensuring customer satisfaction.
Provide technical guidance and foster team collaboration on observability tools and log analytics.
Technical Expertise & Customer Engagement:
Oversee the implementation of observability tools, guiding customers through Logs, Metric and Traces monitoring, and real-time analysis.
Ensure that your team delivers expert-level onboarding and ongoing, for our observability and logging solutions.
Provide deep technical insights on cloud observability and integration of into customer infrastructures.
Customer Relationship Management:
Be the primary escalation point for customer technical challenges.
Proactively work with customers to enhance their logging and observability practices, integrating them seamlessly with platform.
Engage with stakeholders to provide tailored technical solutions that align with customer business goals.
Data-Driven Leadership:
Leverage customer feedback and usage data to enhance the onboarding process and overall TAM team performance.
Analyze patterns in customer data, ensuring that your team applies data insights to improve observability outcomes and preempt issues.
Collaborate with internal teams on product enhancements, informed by your team's customer data analysis

Required Senior ML Engineer - Applied AI Engineering Group
The Dream Job
It starts with you - an engineer driven to build the ML platform that turns research into reliable, production-grade intelligence. You care about reproducibility, low-friction experimentation, and infrastructure that earns the trust of the scientists and researchers who depend on it daily. You'll architect and ship our ML platform - training pipelines, model serving, feature stores, experiment tracking, and compute orchestration - turning models into production capabilities across cloud and on-prem, including air-gapped deployments. A significant part of the platform supports large language models, with unique challenges across training, evaluation, and inference in mission-critical environments.
If you want to make a meaningful impact, join our mission and build the ML platform that drives Sovereign AI products - this role is for you.
The Dream-Maker Responsibilities
Build and operate ML training infrastructure - distributed training pipelines, compute scheduling, and reproducible experiment workflows that data scientists rely on daily.
Own model serving and inference systems - packaging, deployment, autoscaling, A/B testing, canary rollouts, and latency/cost optimization for production models.
Run feature stores, model registries, and dataset versioning - enabling self-serve feature engineering, model lineage, and reproducible experiments across teams.
Build experiment tracking and evaluation infrastructure - automated evals, comparison dashboards, drift detection, and monitoring that give teams visibility into model behavior and performance.
Build and maintain production pipelines for training, fine-tuning workflows, and serving domain models - owning reliability, reproducibility, and scale.
Build and maintain the monitoring and observability layer - model performance tracking, data and prediction drift detection, data quality validation, and alerting.
Improve performance and cost across the ML stack - training throughput, inference latency, batch vs. real-time tradeoffs, and compute cost management.
Ship shared tooling - libraries, templates, CI/CD for models, IaC, and runbooks - while collaborating across Data Platform, AI, Data Science, Engineering, and DevOps. Own architecture, documentation, and operations end-to-end.