לוח משרות דרושים NLP/Machine Learning

Alice is a leading platform for Trust & Safety teams worldwide, leveraging cutting?edge AI and world?class expertise to protect users from the widest spectrum of online harms. By continuously collecting and analyzing data, our solutions ensure customers stay two steps ahead of bad actors in an ever?changing threat landscape. We’re seeking an outstanding Backend Engineer with a Generative AI orientation to join our research team. We are building a new AI Platform from scratch to standardize AI development methods, ensure excellence and efficiency, and deliver robust, scalable, and compliant AI capabilities. This platform will handle GenAI models deployment, prompt management, data filtering, logging, and monitoring, centrally, so individuals can focus on their own business-specific logic. Key Responsibilities
* Build and maintain CI/CD pipelines that support fast, reliable integration and deployment of GenAI systems across complex environments, including orchestrating multiple models/agents and MCP clients/servers.
* Develop, deploy and integrate AI solutions and agentic frameworks, creating both command?line tools and interactive notebooks that support our team’s research and workflow automation needs.
* Build and manage data pipelines and databases (SQL) for large?scale data handling, automating data collection and curation (e.g., adversarial prompts for model red-teaming) to support AI training and evaluation.
* Integrate research into production by implementing the latest generative AI advancements (including white?box LLM development), integrating different models and agents, and developing evaluation frameworks (e.g., agentic reasoning tests) as part of our automated workflows.
* Deploy GenAI models from repositories such as HuggingFace onto our AWS platform, connect them to data pipelines, and automate end?to?end processes for prompt generation, labeling, and response evaluation.

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.

What We Are Looking For As a VP of AI Security Research you will lead, scale, and inspire multi-disciplinary teams focused on red teaming, sandboxing, adversarial testing, developing red-teaming engines, and guardrail protections for GenAI models and agentic AI systems. In this high-profile role, you will work closely with security research, product, engineering, and compliance teams to shape and deliver the next generation of AI cybersecurity solutions, while combining strategic vision with execution to effectively safeguard LLMs and agentic AI deployments at scale. Key Responsibilities
* Building and scaling global AI security teams, while providing mentorship to senior managers and fostering an innovation-driven security culture.
* Overseeing advanced adversarial evaluations for GenAI models, agentic AI, and multi-agent (A2A) systems, and delivering executive-level threat intelligence and risk assessments to inform corporate AI strategy.
* Defining and implementing AI red-teaming frameworks aligned with OWASP AI Security guidelines, MITRE ATLAS, and NIST AI RMF, and operationalizing automated red-team engines to continuously stress-test models at scale.
* Partnering with product and engineering to design and deploy enterprise-ready AI guardrails, including policy enforcement layers, monitoring pipelines, and anomaly detection systems – and championing secure deployment practices for GenAI (including agent orchestration via MCP and A2A workflows).

About Alice:
Alice is the leading provider of security and safety solutions for online experiences, safeguarding more than 3 billion users, top foundation models, and the world’s largest enterprises and tech platforms every day. As a trusted ally to major technology firms and Fortune 500 brands that build user-generated and GenAI products, Alice empowers security, AI, and policy teams with low-latency Real-Time Guardrails and a continuous Red Teaming program that pressure-tests systems with adversarial prompts and emerging threat techniques. Powered by deep threat intelligence, unmatched harmful-content detection, and coverage of 117+ languages, Alice enables organizations to deliver engaging and trustworthy experiences at global scale while operating safely and responsibly across all threat landscapes.

Hybrid:
Yes

Alice partners with the world’s leading AI labs to deliver best-in-class model assurance, red teaming, evaluations, and post-training data programs. We’re looking for a Technical Engagement Lead to guide the technical success of these strategic customers. In this role, you’ll be the key technical counterpart to frontier-model teams—helping them design, structure, and execute complex AI safety programs. You won’t be building prompts or running evals yourself; instead, you’ll lead the technical architecture and orchestration of our work, ensuring quality, coherence, and impact across multiple workstreams. You’ll work hand-in-hand with a Senior Account Manager, delivery teams, researchers, and product leaders to help GenAI customers push forward safely and responsibly. What You’ll Do
* Serve as the primary technical partner for leading LLM labs and GenAI-native organizations
* Translate customer goals into structured evaluation, red teaming and data programs
* Design engagement architectures across multiple parallel contracts and initiatives
* Ensure technical excellence and consistency in all deliverables
* Lead technical discussions with research, safety, and product teams
* Identify risks, dependencies, and evolving needs early, and drive resolution
* Stay ahead of emerging evaluation methodologies, safety approaches, and model risk trends
* Partner internally with Delivery, Research, Product, and Account Manager to ensure seamless execution
Why Alice Work with the world’s leading AI labs
* Help shape the safety and trustworthiness of next-generation AI models
* Join a mission driven, high performing team
* Enjoy opportunities for growth and professional development in a cutting-edge field.

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.




Hybrid:
Yes

We are seeking a visionary and hands-on AI Scientist to help shape the next generation of foundational language models and agentic systems that empower small and medium-sized businesses (SMBs) to thrive. In this role, you will play a key part in defining, designing, and building groundbreaking AI solutions that understand, reason, and act across complex financial and business contexts.
You will collaborate closely with cross-functional experts in AI research, data science, engineering, and product to create intelligent agents that help SMBs automate financial tasks, make smarter decisions, and operate more efficiently. Your work will combine scientific rigor with visionary execution, balancing theoretical innovation with large-scale practical impact.
The ideal candidate is a builder-scientist-a creative thinker who not only develops novel model architectures and training paradigms but also drives their implementation and validation in real-world applications. Youll have the opportunity to shape the AI foundation that powers transformative products serving millions of customers.
Responsibilities:
Design and develop foundational language models and agentic architectures that power intelligent decision-making for small and medium businesses.
Explore novel approaches in large-scale pretraining, fine-tuning, retrieval-augmented generation, and reasoning to improve factuality, adaptability, and alignment.
Build intelligent agents capable of understanding financial data, customer context, and business workflows - from bookkeeping and planning to communication and insights generation.
Collaborate with cross-functional teams across AI research, engineering, product, and design to translate breakthrough science into scalable products used by millions.
Define technical strategy and roadmap for next-generation agentic systems, driving innovation and excellence across the organization.
Publish and present research findings, internal innovations, or contributions to open-source frameworks where appropriate.

Come join as a Senior Staff Machine Learning Engineer (MLE).
Senior Staff MLEs deliver end-to-end AI solutions that span multiple domains and products, influencing the strategic direction of machine learning and AI across the company. You will identify cross-cutting opportunities, set technical direction for complex systems, and deliver scalable, responsible AI-driven experiences that unlock customer and business value at scale.
In this role, youll be expected to define and evolve ML architecture, guide multiple teams, and drive execution excellence across the full ML lifecycle-from experimentation to production. Youll partner closely with AI scientists, product engineers, and business leaders to solve high-impact problems and pioneer new capabilities that advance AI-native platform.

We are looking for a Machine Learning Engineer (MLE) to work on building foundational language models and agentic AI systems that empower small and medium-sized businesses (SMBs) in their financial and operational journeys.
In this role, youll work alongside Machine Learning Engineers, AI scientists and product teams to build LLM based solutions for millions of small and medium busniesses around the world, and build foundational models, involving translate breakthrough research into production systems - designing, implementing, optimizing cost, latency, serving models that reason, act, and learn across real-world business contexts. Youll build scalable pipelines and infrastructure that drive impact on customers lives with the state-of-the-art AI from prototype to customer impact.
This is a unique opportunity for an engineer who thrives at the intersection of science and production, combining deep technical understanding of AI systems with the rigor and creativity needed to deliver robust, reliable, and high-performing products at scale.
Responsibilities:
Implement, optimize, and deploy foundation and agentic models for large-scale use in financial reasoning, decision support, and business automation.
Collaborate with MLE, AI scientists to operationalize research ideas, turning model architectures and training methods into efficient, production-grade implementations.
Design, build, and maintain ML pipelines for data ingestion, preprocessing, training, evaluation, and continuous improvement.
Optimize inference efficiency and model latency, ensuring production systems meet real-time performance requirements.
Contribute to retrieval, memory, and orchestration components that enable agentic reasoning and long-term context management.
Establish best practices for model monitoring, evaluation, and safe deployment, including automated testing and observability in production environments.
Drive applied innovation, bridging the gap between research prototypes and large-scale, reliable business solutions used by millions of customers.

Join an amazing team driving AI solutions in the fintech industry, primarily focused on evaluating risk for lending products.
This Senior Staff role is a blend of leading the full AI/ML development cycle and acting as a Data Science Architect, responsible for all engineering aspects of the work to deliver excellent, high-quality, and operationally sound AI systems.
Responsibilities:
System Architecture & Operational Excellence:
Deliver robust AI/ML system designs that meet customer and systems requirements, including latency, throughput, cost, and maintenance.
Working with partners and architects, define the vision and align on architecture for integration, ensuring excellent deliveries in terms of quality, stability, security, compliance, and operational excellence.
Drive cross-functional end-to-end design architecture.
Lead conversations with partner architects to influence AI-driven product design and strategy
AI/ML Development & Modeling:
Lead the full cycle of iterative big data exploration, including hypothesis formulation, algorithm development, data cleansing, testing, and insight generation.
Apply advanced, predictive statistical modeling and testing to extract data-driven insights from complex, large-scale data sources (relational and non-relational).
Review complex and challenging work to help simplify and execute with speed.
Strategy & Consultation:
Provide guidance to business stakeholders on how best to harness available data and fully exploit the insights revealed through the research.
Drive the design and creation of reusable AI capabilities.

We are looking for a deep learning algorithm developer to join our growing team under Algorithms Group.
The team is building an innovative multimodal learning framework aimed at improving autonomous driving performance by understanding long-tail cases and providing actionable navigation insights. Were combining state-of-the-art vision-language models to revolutionize how we train, validate, and scale our autonomous systems.
If youre passionate about deep learning and engineering high-impact autonomous solutions - this is the place for you.
What will your job look like:
Contribute to dataset curation activities - collecting, cleaning, labeling, and preparing multimodal data for training and validation.
Train and fine-tune LLMs, VLMs, and VLA models to interpret visual scenes and produce actionable navigation insights supporting autonomous vehicle decision-making.
Support validation of multimodal models - evaluating vision-language-action behavior and helping identify performance gaps across driving scenarios.
Collaborate closely with AV planners, perception teams, and infrastructure engineers to ensure seamless deployment in a real-time ecosystem.
Youll have the opportunity to influence the strategic direction of language-driven autonomy - proposing new ideas, shaping model capabilities, and driving innovation from research to real-world deployment.

we are looking for a Machine Learning Software Engineer, who will be challenged by bridging the gap between cutting-edge machine learning research and robust production deployment.
In this position, you will combine software engineering expertise with machine learning deployment knowledge, responsible for taking our algorithms and developing robust production solutions that serve them at scale.
The work at algorithms department is fast-paced and requires staying ahead of the curve with the latest engineering solutions and best practices adopted across the ML community, while staying informed about emerging solutions in both computer vision and NLP domains and understanding the specific problems they address.
What will your job look like:
Your role will include developing production deployment systems for classical and machine learning algorithms from research and building robust, scalable inference pipelines.
You will develop primarily in Python and infrastructure tools (Kubernetes, Docker, etc.), taking part in both maintaining existing deployment systems and developing new production capabilities.
Finally, you will need to learn and implement new deployment technologies and best practices that can address emerging production challenges as they arise, while staying current with the latest MLOps and inference optimization techniques.

We are looking for an ML Engineer / MLOps Tech Lead to promote machine learning engineering excellence. Someone who is passionate about building scalable, high-quality data products and processes, while ensuring production systems maintain strong real-time performance observability.
You will focus on designing and maintaining the core infrastructure that empowers the Machine Learning Engineers working within Data Science product teams. Youll collaborate closely with stakeholders across data science, product, and engineering, playing a pivotal role in driving the business by architecting and enabling the infrastructure for machine learning model development, serving, and lifecycle management-the foundation of our product.
Responsibilities:
Partner with MLEs in Data Science product teams and key stakeholders to design and maintain infrastructure for:
Data wrangling - supporting and enabling data requirements for research, training, validation, and testing.
End-to-end ML delivery - enabling model performance development, training, validation, testing, and version control.
Drive engineering best practices including code and model versioning, CI/CD pipelines, rollout strategies, and disaster recovery procedures.
Build and support monitoring and observability tools - dashboards, alerts, and performance tracking of models in production.
Lead architecture projects such as:
Feature Store - centralizing feature engineering and serving across teams.
Vector Databases - enabling large-scale embedding storage and retrieval for advanced ML applications.
GPU Cluster Scaling - optimizing distributed training and inference infrastructure.
Collaborate with product, data science, and engineering teams to solve complex problems, identify trends, and create opportunities through robust ML infrastructure.

We are looking for a Senior Research Engineer who will both drive independent deep learning research and collaborate closely with other developers to help unlock new directions, solve complex challenges, and elevate the teams algorithmic capabilities.
** This role offers the flexibility to work part-time from our other sites, subject to seat availability.
What will your job look like:
Conduct hands-on research and development of deep learning algorithms for road understanding, drivable area detection, and scene structure modeling
Lead exploratory investigations into new architectures, training strategies, and data utilization methods
Join forces with other developers to troubleshoot difficult problems, introduce new ideas, and guide technical decisions
Own projects end-to-end - from concept and experimentation to integration and scalable deployment

We are seeking an experienced and visionary Head of Research to lead, shape, and advance the future of AI innovation across the organization. In this role, you will own the research strategy end-to-end - from long-term roadmap design to hands-on exploration, and guide a multidisciplinary team of NLP research engineers and linguists toward breakthroughs that elevate our core medical coding engine.
You will play a key role in the company, balancing exploratory research with high-impact product delivery. You will partner with Product, Engineering, and executive stakeholders to identify strategic opportunities, drive prioritization, and translate research capabilities into real-world outcomes at scale.
Responsibilities:
Manage and mentor a multidisciplinary research team while driving both technical excellence and personal growth.
Define the long-term research roadmap aligned with product and business objectives.
Lead the full research lifecycle, from ideation and feasibility studies to experimentation, evaluation methods, and production-ready delivery.
Evaluate and introduce new research capabilities and emerging trends such as LLM-based reasoning, semantic/graph modeling, hybrid rule-learning, and other frontier techniques.
Continuously track scientific trends to maintain a state-of-the-art research practice.
Collaborate closely with Product and Engineering teams to translate domain challenges into algorithmic solutions with measurable product impact.
Represent the Research function at leadership forums, communicate priorities and outcomes, and align stakeholders around research strategies and milestones.

A problem solver at heart, you have a passion for excellence, you love to learn but know when its time to deliver and make ends meet. You arent threatened by a complex, dynamic and demanding environment. There is no I in team, is a motto you believe in deeply and you are always looking out for your peers. You know how to take ownership and drive projects to completion.

We are looking for a passionate Senior Infra Engineer to join our all-star team.

This is an amazing opportunity to join a multi-disciplinary A-team while working in a fast-paced results, marketing and data-oriented environment.

If you are experienced but still hungry to learn and impact - wed love to have you on our team!



On a typical day, you will:

Design, scale, and operate high-throughput, low-latency infrastructure supporting RTB bidders and ML prediction services at extreme scale (2Million+ QPS).
Own production GCP environments end-to-end, including deployment, monitoring, 99.999 uptime, incident response, and post-mortems.
Build and maintain infrastructure for massive data ingestion (up to 1TB per hour), continuous ML training pipelines, and real-time prediction systems.
Develop and evolve CI/CD pipelines, DevOps automation, and infrastructure-as-code practices.
Work closely with engineering and data science teams, taking full ownership from design through production and ongoing operations.
Continuously evaluate and introduce improvements to our infrastructure stack, tooling, and operational practices.

we are looking for a Senior DevOps Engineer - ML Platform.
AI Engineering's ML-Platform team goal, is to deliver a modern infrastructure and solutions to enhance Algorithm development life cycle and shorten our delivery times. We are an independent group, consisting of excellent and experienced engineers with diverse skills in algorithms, software, and infrastructure. We strive to implement a DevOps culture allowing our engineers to easily collaborate on large-scale products.
We develop cross-company products that enable the research and deployment of state-of-the-art algorithms.
What will your job look like?
Build and maintain infrastructure for large‑scale AI and HPC workloads across on‑prem and cloud environments
Operate and enhance our multi‑cloud, multi‑cluster scheduling platform
Develop automation, tooling, and platform services und Bash
Troubleshoot complex issues across the stack: compute, networking, storage, orchestration, and distributed systems
Improve reliability of critical systems
Collaborate with ML, data, and backend teams to support evolving platform needs
Drive best practices in CI/CD, infrastructure-as-code, and system design
Participate in on‑call rotations for critical infrastructure components