דרושים » תוכנה » data Scientist /AI Detection Research

Requirements:
What Experience Will Drive to Success:
* Bachelors degree in data Science, Computer Science, Computer Engineering, or related field.
* 2+ years of experience in AI/ML engineering, with a proven track record of building and deploying ML & AI systems.
* Strong programming skills in Python and experience with ML frameworks such as TensorFlow, PyTorch, and Scikit-Learn.
* Hands-on experience with Big Data processing frameworks (Apache Spark, Dask, Ray).
* Hands-on experience with LLMs and AI Frameworks (LangChain, OpenAI, HuggingFace, LangGraph, etc.)
* Experience with Git and Jenkins.
* Strong problem-solving skills, a passion for innovation, and a self-driven mindset.
* Excellent communication and collaboration skills.
* Familiarity with AWS AI/ML services and cloud-based deployments (Advantage).
* Experience working with MLOps tools, including model registry, experiment tracking, and model serving (Advantage).
What We Are Looking For Independent and Self-Driven: Were building an AI Department from the ground up, so we need someone who is proactive, takes ownership, and thrives in a startup-like environment. Passion for Innovation: Whether its building scalable data infrastructure or creating advanced AI models, we are looking for someone passionate about solving complex challenges and delivering innovative solutions. Collaboration Skills: Appdome is all about teamwork. You will collaborate with engineers, data scientists, and product teams to build impactful solutions. Strong communication and interpersonal skills are key. Adaptability and Problem-Solving: Things move quickly at Appdome. You should be able to adapt to changing requirements and quickly solve problems in a fast-paced, dynamic environment. Can-Do Attitude: Were looking for motivated individuals who take the initiative, face challenges head-on, and can work independently while contributing to team success. About the Company: Appdome's mission is to protect every mobile app worldwide and its users. We provide mobile brands with the only patented, centralized, data -driven Mobile Cyber Defense Automation platform. Our platform delivers rapid no-code, no-SDK mobile app security, anti-fraud, anti-malware, anti-cheat, anti-bot implementations, configuration as code ease, Threat-Events threat-aware UI / UX control, ThreatScope Mobile XDR, and Certified Secure DevSecOps Certification in one integrated system. With Appdome, mobile Developers, cyber and fraud teams can accelerate delivery, guarantee compliance, and leverage automation to build, TEST, release, and monitor the full range of cyber, anti-fraud, and other defenses needed in mobile apps from within mobile DevOps and CI/CD pipelines.

Requirements:
Were looking for someone whos not just a great engineer, but a passionate innovator who puts their soul into solving tough problems and delivering value.
* 4-5+ years of experience in researching, developing and delivering ML solutions in production-scale environments.
* Solid foundation knowledge of data science, Machine Learning, and statistics.
* Demonstrated analytical thinking and a deep understanding of data - its structure, context, and the insights it can unlock.
* Strong Python programming skills with fluency in AI/ML frameworks: Scikit-learn, TensorFlow, PyTorch, Hugging Face, LangChain, etc.
* Expertise in working with large-scale datasets using SQL, Spark, or similar tools.
* Proven success translating product or business needs into working AI systems.
* Fast learner, creative, and comfortable working in a dynamic startup environment.
* Good communication skills, able to explain complex ideas and findings to both technical and business audiences. Bonus Points (Preferred)
* Experience with cybersecurity-related data or product domains.
* Hands-on knowledge in working with LLMs and building AI agents.
* Familiarity with AWS cloud environment and MLOps (ML Orchestration, Docker, Kubernetes, MLflow, etc.). This position is also open to Security Researchers with data and AI experience who are looking to expand in AI. Ready to Empower the Future? At Cynet, you wont just be another data Scientist. Youll be a thought leader. A builder. An innovator. This is a unique opportunity to envision and shape how AI defends tomorrows digital landscape. If you're ready to dive deep, move fast, and create meaningful impact - wed love to meet you Apply now and lets build the future of cybersecurity together.

Requirements:
Proven strong expertise (8+ years) as a data scientist and machine-learning researcher.
Proven strong expertise (8+ years) in Python, with a production-level design and coding skills and hands-on experience with coding machine learning / statistical modeling based solutions
M.Sc. in Computer Science, Mathematics, Engineering or a related field, with strong theoretical background in supervised & unsupervised modeling and various other statistical modeling techniques
High-level experience with databases approaches, such as SQL and document-oriented (e.g. MongoDB) and big data
Experience in data analysis and visualization
Strong problem solving and critical thinking skills
Can-do approach
Background in Cybersecurity - an advantage
Theoretical and practical background in Generative AI - an advantage

Requirements:
MSc/Ph.D. in Statistics, computer science, data science or a related field
5+ years of experience of exploring, building and deploying ML and data systems in production
Strong programming skills in Python focusing on ML frameworks such as Sklearn, XGBoost or TensorFlow
Experience with distributed and stream processing, Cloud ML infrastructure and feature store tools
Expertise in supervised and unsupervised machine learning models (e.g., classification, anomaly detection or clustering)
Experience writing code in Agile, CI/CD-based production environments
Proficient in communicating technical and research ideas and collaborating effectively across teams and organizational stakeholders
Experience in Fintech solutions is a big advantage

Requirements:
Requirements
BSc in Computer Science, Engineering, Mathematics, Physics, or a related quantitative field. MSc is an advantage.
3+ years of hands-on experience in NLP roles with demonstrated production deployment of ML models.
At least 1 year of experience with LLMs (e.g., OpenAI, HuggingFace, Cohere, Anthropic, or similar).
Strong programming skills in Python with practical use of ML and NLP frameworks (e.g., HuggingFace Transformers, spaCy, scikit-learn).
Familiarity with prompt engineering principles, including prompt tuning, template construction, and response evaluation.
Experience with model monitoring and optimization in real-world settings.
Understanding of model limitations, prompt sensitivity, and output consistency.

Advantages:
Knowledge of ML-Ops practices and model deployment pipelines.
Experience with LLM safety, bias mitigation, or prompt hardening strategies.
Exposure to multilingual or multimodal prompting.
Familiarity with compliance frameworks in healthcare or other regulated environments (e.g., HIPAA, SOC2).

Requirements:
M.Sc. or PhD. in Computer Science, Mathematics, Engineering or a related field
5+ years of hands-on experience developing and deploying machine learning models into production
Strong background in ML, Deep Learning, NLP, preferably with a focus on audio/video transcription and analysis
Experience in leveraging large-scale compute resources, including distributed GPUs, to train, test, and evaluate models
Proficiency in programming languages such as Python, and experience with relevant libraries and frameworks (OpenCV, TensorFlow, PyTorch, etc.)
Excellent verbal and written communication skills.

Requirements:
Advanced degree (M.Sc. or Ph.D.) in Electrical Engineering, Physics, Applied Mathematics, Computer Science, or a related quantitative discipline.
5+ years of hands-on experience in developing and deploying machine learning, signal processing, or algorithmic solutions, with emphasis on raw or low-level data (e.g., sensor data, audio, video streams, or medical imaging).
Proven expertise in time-series analysis and handling large-scale, complex datasets from acquisition to production deployment.
Strong Python programming skills, with the ability to write clean, modular, and testable production-grade code.
Demonstrated experience deploying ML/DSP pipelines into production environments, ideally in high-availability systems.
Familiarity with ML/DL frameworks such as PyTorch, TensorFlow, scikit-learn, and gradient-boosting libraries (e.g., XGBoost, LightGBM).
Strong collaboration and communication skills, with the ability to work effectively across interdisciplinary teams including software engineers, physicists, and external stakeholders.

Requirements:
5+ years of experience in data science, with experience in managing full-cycle projects from initial concept to production deployment.
PhD in Computer Science, Data Science, Statistics, Mathematics or a related field .
Comprehensive understanding of machine learning and deep learning principles and techniques, including hands-on experience.
Specialized expertise in NLP (Transformers, LLMs) and computer vision (multimodality is an advantage).
Ability to write production-ready code.
Publications and talks at leading conferences - an advantage.

Requirements:
An M.Sc. degree in computer science, statistics, or a related field is a must; a Ph.D. degree is an advantage.
At least 3 peer-reviewed publications in reputable academic journals or conferences.
5+ years of experience in leading and managing data science and machine learning projects, preferably at the intersection of AI and cybersecurity.
Experience and hands-on familiarity with distributed cloud systems.
Strong knowledge of deep learning models and common model architectures such as transformer models, LLMs, CNNs, RNNs. Knowledge of programming languages that are used in AI researchlike Pythonand experience with AI frameworks (e.g., Hugging Face, LangChain, OpenAI, scikit-learn, TensorFlow, PyTorch).
Proven ability to work independently in a fast-paced environment and come up with creative solutions to challenging problems.
Excellent communication (both written and verbal) and presentation skills.

Requirements:
Minimum of 5 years of experience as a Back End developer.
Deep knowledge of Generative AI principles, including Large Language Models (LLMs) and RAG techniques and, modern deployment architectures.
Ability to lead team to design services, modules, APIs, and folder structures that enable REST API communication and facilitate a plug-and-play approach for various agent pods (compatible with langgraph, pydanticAI, etc.)
Practical Implementation: Hands-on experience in implementing and integrating new ideas and tools within the GenAI landscape.
Programming and Tools: Proficiency with Python, PySpark, Langchain, LlamaIndex, RAG, ChromaDB, QDrant, Weaviate, Neo4j, Knowledge Graphs, AWS Bedrock, GCP Vertex, Azure OpenAI, Git/GitHub, Docker, SQL, FastAPI, PyTorch/TensorFlow, and Pydantic.
Cloud Platforms: Experience with managed cloud services provided by hyperscalers such as AWS, Azure, or GCP.
Excellent problem-solving and analytical skills. Degree in Computer Science, Artificial Intelligence, Machine Learning or a related field.
Advanced level of English.
Working Israeli permit- a must
B.A/M.Sc. in Data Science, Computer Science, Mathematics, Statistics, etc- an advantage