לוח משרות דרושים NLP/Machine Learning עבודה היברידית

Join as the first engineer and researcher behind GenAI Protect, building LLM-powered discovery, classification and policy-enforcement services that secure enterprise generative-AI usage.
Key Responsibilities
Design and implement scalable inference services (Python/FastAPI, Triton, ONNX) with GPU orchestration.
Develop and fine-tune transformer models for prompt inspection, PII/red-flag detection and intent analysis.
Collect datasets, build evaluation pipelines and drive continuous model improvement.
Collaborate with Threat-Intel and Product to respond to emerging GenAI attack vectors.
Publish internal/external tech blogs; help hire and mentor future AI-security engineers.

We are looking for a Senior Data Scientist with deep expertise in Large Language Models (LLMs), Deep Learning, and Neural Networks to join our Threat Research group, located in our Tel Aviv Office. Our Threat Research group is composed of elite researchers and developers. We research applications, DDoS, and database attacks, develop algorithms for new products, and drive innovation and thought leadership in cybersecurity.
Key Responsibilities :
Serve as the technical lead for projects involving LLMs, deep learning, and neural networks focused on cybersecurity applications.
Design, train, fine-tune, and deliver LLMs and advanced deep learning models for tasks such as anomaly detection, threat classification, and automated analysis of security data.
Drive hands-on research from ideation through prototyping to scalable production systems.
Collaborate with product and engineering teams to integrate advanced AI models into security solutions.
Analyze complex, high-dimensional security data (including text, logs, network traffic, and more) to identify emerging threats and attack patterns.
Mentor and guide other data scientists and contribute to the teams technical growth.
Represent in the AI and security communities through thought leadership, publications, presentations, and patents.

We are seeking a highly motivated and experienced LLM/ML Agentic AI Researcher to lead the technical development of our agentic AI interpretation framework. This hands-on role involves designing, building, and optimizing AI agents that interpret complex biological data and generate coherent, insightful narratives explaining therapeutic mechanisms.

You will be at the forefront of developing a sophisticated scientific reasoning system that leverages Large Language Models (LLMs) to provide structured, biologically-grounded explanations. Collaborating closely with immunologists, machine learning researchers, and technical leadership, you'll shape how we derive insights at a systems level, pushing the boundaries of AI in biology.

Location: Ramat Gan, Israel (hybrid model)

What will you do?
Architect & Develop: Design, implement, and iterate on core AI agents using LLMs and Chain-of-Thought reasoning for creating a scientific reasoning system.
Integrate Biological Knowledge: Effectively access and incorporate biological databases (internal and external databases as tools) ensuring model interpretations are rooted in real biological mechanisms.
Solve Complex NLP Challenges: Innovate solutions to synthesize multiple information sources into cohesive, scientifically robust narratives. Structure advanced prompts and refine LLM interactions to achieve narrative coherence and clarity.
Robustness & Testing: Produce clean, well-documented, maintainable Python code with clear testing protocols, ensuring reliability and accuracy of the agent outputs.
Stay Ahead of Trends: Continuously explore emerging LLM technologies, APIs, and best practices to enhance our interpretation framework.
Effective Collaboration & Communication: Clearly articulate technical concepts to both technical and non-technical stakeholders, effectively integrate feedback from immunologists and researchers, and iterate rapidly to refine the interpretation framework.

We are seeking a highly skilled Machine Learning Engineer to enable a large team of deep learning engineers, data scientists and computational biologists.

We are looking for a driven candidate to expand our model observability software, lead the optimization of GPU infrastructure, and ensure efficient collaboration with data engineering. The ideal candidate will have development skills in python, deep expertise in cloud infrastructure, high-performance computing, and AI workload optimization. This role involves designing robust GPU management systems, automating model performance metrics, and supporting researchers with the tools they need to train and deploy machine learning models effectively.

Location: Ramat Gan, Israel (hybrid role)

What will you do?

GPU Infrastructure Optimization:
Design and implement strategies to maximize the efficient utilization of GPU resources across the organization.
Develop tools and processes for GPU allocation, workload management, and performance monitoring in alignment with selected infrastructure tools.
Monitor and fine-tune GPU performance to ensure optimal throughput for machine learning workloads.
Model Observability:
Build and maintain a robust system for automated reporting of key model performance metrics.
Integrate with diverse data sources to create customizable dashboards for monitoring performance across datasets.
Set up anomaly detection systems and alerts to ensure timely identification of performance degradation.
Enhance the existing benchmarking suite for seamless evaluation of datasets in federated data lakes.
Collaboration and Support:
Partner with machine learning scientists, data engineers, and DevOps teams to enable researchers to efficiently train and deploy models.
Provide technical guidance and support for effectively utilizing available infrastructure and tools.
Technology Research:
Stay updated with the latest advancements in GPU technologies, ML infrastructure best practices, and model performance metrics.
Evaluate and recommend new tools, technologies, and approaches to enhance the efficiency of the ML enablement platform.
Git and Code Ownership:
Implement best practices for Git workflows, code versioning, and safe release processes.
Foster a culture of high-quality, collaborative development within the engineering team.

We are looking for a Machine Learning Engineer.
Responsibilities:
Join Finaloops core activities, contributing to impactful data development and insights retrieval projects.
Collaborate closely with domain experts and developers to enhance data-driven features.
Own and manage data features throughout their lifecycle, including design, implementation, monitoring, and iteration.
Define and track key performance indicators (KPIs) for the team and the company, promoting a data-driven approach.

We are looking for a highly skilled and motivated Machine Learning Engineer to join our Data Science Engineering team. The ideal candidate will have a deep understanding of machine learning infrastructure and solutions, enabling data scientists and engineers to efficiently develop, deploy, and maintain models in production by delivering a scalable and high-quality solution. This role requires a combination of technical expertise, strong problem-solving skills, and the ability to collaborate effectively with cross-functional teams.

What Youll Do:
Develop and maintain machine learning infrastructure and solutions to support the efficient development, deployment, and maintenance of models in production.
Collaborate with data scientists, engineers, and subject matter experts to deliver high-quality, production-ready machine learning models.
Design and implement software architecture for machine learning solutions.
Optimize model deployment and serving using industry best practices with CPU, GPU, and external APIs.
Work with containerized environments such as Kubernetes and Docker.
Utilize AWS for cloud-based machine learning solutions.
Conduct unit testing and ensure continuous integration and continuous deployment (CI/CD) practices are followed.
Collaborate with the DevOps team to establish best practices for MLOps.
Work in a production environment and closely with data science teams to ensure seamless model deployment and maintenance.
Stay updated with the latest advancements in machine learning and related technologies.

We are seeking a hands-on Tech Lead to be the first technical hire for our newly formed ML team. This is a unique ground-floor opportunity to build something from scratch and have direct influence on the technical direction of our ML capabilities. This role combines deep technical expertise with foundational leadership, requiring someone who can architect solutions, establish technical standards, and lay the groundwork for future team growth. As our founding ML tech lead, you'll have the opportunity to shape our technology choices, define our technical practices, and build the fundamental skill set that will guide the team as we scale.

What youll do: 
Shape the technical foundation: As our first ML hands on hire, choose and establish the team's core technology stack, frameworks, and development practices together with the ML leader.
Build from the ground up: Design and implement our initial ML infrastructure, data pipelines, and model deployment frameworks.
Define technical standards: Establish coding standards, best practices, and processes that will guide future team members.
Hands-on development: Lead by example through direct development and deployment of ML models and data science solutions.
Partner with stakeholders: Work closely with business teams to identify initial ML opportunities and build foundational proof-of-concept models.
Establish MLOps practices: Set up our model development, testing, deployment, and monitoring workflows from scratch.
Recruit and onboard: As the team grows, play a key role in technical interviews and help onboard new ML engineers and data scientists.
Create team culture: Help establish the team's technical culture, learning practices, and collaboration methods.
Technology evaluation: Research and select the tools, platforms, and technologies that will form our ML tech stack.
Document and share knowledge: Create foundational documentation and knowledge-sharing practices for the growing team.

Location: Tel Aviv, Israel.

Hybrid.

Full-time.

We are seeking a dynamic Data Scientist with a strong data science experience and flair for AI Pre Sales to join our team. This hybrid role combines technical expertise in AI and data science with the ability to identify, pitch, and present AI/ML solutions for our clients. The ideal candidate is an accomplished data scientist who can design and execute AI/ML models to meet complex client needs while able to demonstrate and clearly explain business benefits and practical implementations to customers.
Key Responsibilities:
Data Science and Technical Consulting (Primary Focus)
Data Analysis & Insights: Perform advanced data analysis on structured and unstructured datasets to generate actionable business insights.
Model Development & Validation: Design, develop, and validate machine learning models and algorithms tailored to client use cases.
Proof-of-Concept (PoC) Development: Lead the creation of AI/ML PoCs to demonstrate the feasibility and impact of proposed solutions.
Advanced Analytics Advisory: Provide expert guidance on applying predictive analytics, natural language processing (NLP), computer vision, and other AI techniques to solve complex business challenges.
Solution Integration: Assist clients in seamlessly integrating AI/ML solutions into their workflows, ensuring measurable impact and ROI.
Model Optimization: Continuously fine-tune and optimize deployed models to ensure scalability, performance, and accuracy over time.
Technical Innovation: Stay ahead of AI/ML trends, tools, and frameworks, and proactively suggest innovative approaches to enhance client outcomes.
Business Translation of AI/ML: Serve as a bridge between technical teams and business stakeholders, translating AI/ML solutions into clear, actionable business terms.
Sales Support (Secondary Focus)
Lead client discussions to uncover pain points and articulate AI/ML-driven solutions with measurable business value.
Create and deliver compelling presentations, proposals, and technical demonstrations to prospective clients.
Collaborate with internal teams to align client requirements with technical capabilities.
Drive end-to-end pre sales cycles, including requirement understanding, product / solution customization, business oriented demo flows and stories preparation, presentations to technical and business stakeholders.