לוח משרות דרושים NLP/Machine Learning משרה מלאה

In one sentence
Join our companys cutting-edge amAIz development group, shaping the future of AI-driven solutions for the telecom industry.
We are looking for a dynamic and visionary Development Manager to lead a newly formed, high-impact development team within our companys GenAI & Data organization. In this role, you will manage a talented and independent team of developers focused on building innovative AI products and solutions using Generative AI, Machine Learning, NLP, LLMs, Cloud-native architectures, and microservices.
You will work at the pace of a startup, turning groundbreaking ideas into reality. Collaborate closely with Product Managers and System Architects to develop our companys AI product and deliver end-to-end, scalable, and secure solutions that will revolutionize the telecom industry.
What will your job look like?
Lead and mentor a team of skilled developers, fostering a culture of innovation and technical excellence.
Drive the development of AI-based products and platforms, leveraging Python, React, and modern frameworks like LangGraph and MCP, A2A protocols.
Collaborate with global cross-functional teams, including Product Management and Architecture, to ensure alignment and successful execution.
Operate in a fast-paced, agile environment, balancing multiple priorities and delivering high-quality results.
Champion best practices in CI/CD, DevOps, containerization (Docker, Kubernetes), and cloud deployment (AWS, Azure, GCP).

In one sentence
we are a global leader in software and services for communications, media, and digital enterprises. As AI reshapes the future of software, we are harnessing its power to transform networks, IT systems, and business operations.
We are building a pioneering AI Evangelist team, and we are seeking a leader who will shape the vision, strategy, and execution of this group. This role combines technical depth, strategic thinking, and people leadership to accelerate AI adoption inside our company and establish us as a thought leader in the global AI ecosystem.
What will your job look like?
1. Strategic Leadership & Team Building
Define and execute the strategy for AI Evangelism and Enablement across our company.
Build, manage, and scale a high-performing team of AI Evangelists.
Attract, hire, and develop top talent; foster a culture of innovation, collaboration, and continuous learning.
Set clear goals, measure impact, and align team efforts with our companys broader AI transformation agenda.
2. Internal AI Enablement
Partner with engineering, product, and business leaders to embed AI/GenAI tools and workflows into the delivery lifecycle.
Establish organization-wide standards, best practices, and frameworks for AI-assisted development.
Build and nurture internal communities of practice to ensure responsible, scalable adoption of AI.
3. Hands-on Innovation
Guide pilots, prototypes, and proof-of-concepts to demonstrate business impact of AI.
Provide architectural direction for integrating LLMs, AI services, and automation frameworks at scale.
Balance strategic oversight with occasional hands-on contributions to showcase technical credibility.
4. Knowledge Sharing & Capability Building
Drive the development of training programs, workshops, and enablement content.
Mentor Evangelists, Engineers, and Analysts, ensuring they are empowered with skills and confidence to apply AI in real-world contexts.
Establish metrics to measure the adoption, impact, and maturity of AI practices across the company.
5. External Advocacy & Thought Leadership
Represent our company externally at industry events, customer forums, and developer communities.
Publish articles, whitepapers, and open-source contributions that highlight our companys innovative AI adoption.
Identify external trends and translate them into actionable opportunities for our company.

We are looking for a visionary and deeply technical Chief Architect for Data, AI & GenAI Platforms to drive the architecture, tooling, and long-term technological direction of our enterprise data and GAI products and initiatives. This is a foundational leadership role that sits at the intersection of hands-on system design, cross-functional enablement, and long-term strategic innovation.
You will serve as the chief architect and technology strategist across all data, AI, and GenAI efforts-owning the blueprint that powers intelligent products, agent-based experiences, and scalable platforms. Your work will influence product design, platform infrastructure, governance models, and the broader technical ecosystem we operate in.
We are seeking someone with deep, hands-on experience building large-scale, production-grade data and AI systems-combined with the ability to mentor teams, influence engineering leaders, and partner with product and business leadership to deliver enterprise-scale transformation.
Key Responsibilities
Define and own the technology vision, architecture, and evolution roadmap for all data, ML/AI, and GenAI systems across the organization.
Lead the architectural design and hands-on guidance of scalable data pipelines, real-time analytics, AI agent platforms, model hosting infrastructure, and enterprise knowledge frameworks.
Oversee and connect multiple AI and data-related initiatives, including LLM agents, vector databases, RAG pipelines, MLOps, and enterprise data lakes-ensuring coherence, reusability, and security.
Establish and enforce technical standards, patterns, and tooling across teams to ensure high-quality engineering, model performance, and platform scalability.
Partner with product, engineering, and business leaders to align technology strategy with product goals, business outcomes, and customer needs.
Guide the evaluation and adoption of emerging technologies including open-source GenAI frameworks, fine-tuning platforms, orchestration tools, and scalable cloud-native architectures.
Mentor and support principal engineers, data scientists, platform leads, and architects-creating a culture of technical excellence, experimentation, and ownership.
Champion data quality, model explainability, AI governance, and responsible AI practices across the entire lifecycle.
Serve as a senior thought leader internally and externally-representing the company in technical forums, conferences, and customer engagements when needed.

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.

We are seeking a highly skilled AI Application Team Lead to build and lead a team responsible for developing, running, and optimizing large-scale AI workloads on our AI hardware platform. This role focuses on benchmarking state-of-the-art models (e.g., LLaMA, DeepSeek), executing MLPerf suites, analyzing system-level performance, and driving cross-stack optimizations across hardware, runtime, and software frameworks.
The ideal candidate combines strong technical depth in AI/ML systems, hands-on experience with LLM workloads, and leadership capability to guide a high-performance engineering team.
Responsibilities
Lead and mentor a team of AI application and performance engineers.
Run and optimize AI workloads (LLaMA, DeepSeek, etc.) and execute MLPerf benchmarks.
Analyze end-to-end performance and identify HW/SW bottlenecks.
Develop optimization strategies across models, kernels, frameworks, and runtime.
Build profiling, debugging, and validation tools for large-scale AI workloads.
Collaborate with hardware, compiler, and device software teams to improve performance.

Were looking for an experienced MLOps Engineer to join our team and help design, implement, and maintain scalable machine learning infrastructure and data processing pipelines.
The ideal candidate is passionate about operational excellence, automation, and building reliable systems that empower data scientists and engineers alike.
This role is responsible for enhancing, automating, monitoring, and optimizing data pipelines that collect, transform, cache, index, and manage large-scale datasets.

, we are looking for smart and humble team members to join the team and solve complex problems. Our technical challenges include developing new trading strategies, , improving the performance of our algorithms, finding new ways to beat the markets.
As an ML researcher you will collaborate with our R&D team to execute live trading strategies. If you are looking to make an impact by putting into practice successful ideas and seeing immediately the outcome, make influence on financial performance this is a great opportunity.
In this role you will:
Mange and lead independent research applying ML/DL methods to a wide variety of datasets.
Creatively find new trading strategies
Work with other team members to optimize Algorithms

we are looking for a AI/ML/Software Engineer.
Here, you will tackle ever-evolving challenges and leverage the dynamic AI landscape to craft solutions that transform the cybersecurity industry. You'll have the chance to build cutting-edge models and AI systems for cybersecurity. You'll gain deep expertise in the fields of both AI and security, engaging with all facets of Generative AI techniques and their deployment in production environments. You will collaborate with a talented team of researchers, engineers and security experts, and play a pivotal role in developing groundbreaking AI solutions. Shape the future of AI for Security with us and make an enduring impact on AI adoption across the world!
Develop and train cutting-edge AI models for the security domain.
Develop a platform for AI data processing, training, fine tuning, evaluation and other AI related needs.
Develop agentic systems that automate and uplift security operations.
Author blog posts, white papers and research papers related to developments in AI for the security landscape.
Collaborate with cross-functional teams of researchers and engineers to translate research ideas into products.
Contribute to our groups culture as an early member of the team.

We are looking for researchers and applied scientists to join the Central Applied Science team. Central Applied Science is an interdisciplinary team of quantitative scientists that aims to deliver research and innovation that fundamentally contribute to Meta's success. By applying your expertise in quantitative methods, you will be empowered to drive impact across a range of products, infrastructure and company operations.
Individuals in this role are expected to have expertise and publications within research areas in the board field of machine learning. The ideal candidate will have a passion for building data-driven products and forming research frameworks to solve challenging, real-world problems.
Research Scientist, Central Applied Science Responsibilities
Work with vast amounts of data, generate research questions that push the state-of-the-art, and build data-driven products
Develop novel quantitative methods on top of Meta's unparalleled data infrastructure
Learn new tools, systems, and programming languages quickly as required by the particular project you are working on
Work towards long-term ambitious research goals, while identifying intermediate milestones
Communicate best practices in quantitative analysis to partners
Work both independently and collaboratively with other scientists, engineers, UX researchers, and product managers to accomplish complex tasks that deliver demonstrable value
Publish research results in top-tier conferences and at leading journals
Actively identify new opportunities within Meta's long term roadmap for applied science contributions.

The financial risk management (FRM) machine learning principal will be the most senior machine learning engineer and strategist for financial risk at Meta. The principal will enable the risk organization to deliver significant lift over current long range objectives for friction and leakage through the generation of new Machine Learning opportunities for the organization and support of successful delivery of the risk management ML architecture. This person will partner closely with the FRM engineering leader (Director level) and be part of Metas risk management leadership circle.
Software Engineer, ML (Technical Leadership) Responsibilities
Address core business and technical machine learning opportunities: elevate the existing portfolio of machine learning solutions to be state-of-the-art for minimizing Metas financial losses (due to leakage, good revenues loss and friction). Following are a few examples of technical and business problems we aim to address. - Provide a solution for optimizing the risk machine learning model ensemble (covering the entire end-to-end advertiser funnel including detection, decisioning, enforcement and remediation) through optimization of the current model portfolio and individual models. - Minimize the impact of the prolonged financial fraud feedback loop. - Improve models measurement and performance. - Optimize data/label strategy. - Optimize balance between specific targeted model strategy and broad umbrella model strategy to optimize for short and long term benefits
Lead Research and Introduction of Advanced Technologies: - Collaborate with Financial Integrity's senior ML Engineers to lead the research and introduction of deep learning and Large Language Model (LLM) technologies. - Remain current on industry-wide advancements in ML and introduce relevant advancements in Financial Risk Management
Collaborate on Next-Generation ML Architecture: - Work closely with financial harms principals and risk management tech leads to deliver the next-generation ML architecture for Meta's risk management system. - Collaborate with Principal ML engineers from across the company to adopt best industry and Meta practices within the FRM team. - Resolve or mitigate design dilemmas, balancing business and technical trade-offs. - Identify and initiate opportunities for collaboration and impact with other organizations at Meta
Identify and Initiate New Business Opportunities: - Collaborate with Meta FinTech, Central Integrity and Core Ads Growth partnerships to identify and initiate new business opportunities based on third-party capabilities. - Conduct proof of concept for different opportunities and initiate integrations to enhance business performance
Grow Other Senior ML Engineers - Actively invest in the growth of other senior ML engineers through goal-driven formal and informal mentorship. Provide regular feedback to other engineers regarding their technical work.

We are building the Windows agent that powers GenAI Protect, flagship initiative to secure AI workflows across endpoints, browsers, and SaaS. In this role you will help define how AI and security intersect at the OS level and solve problems no one has solved before. If you want to work on technology that sits on the critical path of how people and machines use GenAI every day, this is where you want to be.



Key Responsibilities
Own the Windows protection layer: design and implement the core proxy, hooks, and anti-tampering mechanisms for GenAI agents.
Collaborate with Mac, Cloud, and Security Engine teams to build unified multi-platform behavior analysis.
Design IDE and developer environment integrations to monitor and protect AI-driven code flows.
Deliver production-ready, high-performance agent components with deep OS-level visibility.
Influence architecture decisions, threat models, and agent-core evolution.