דרושים » תוכנה » AI Research Scientist

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:
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:
3+ years in Data Science, with industry experience in building and optimize AI/ML models
Specialized expertise in modern machine learning methods related to Natural Languages Processing (Transformers, Embeddings, LLMs)
Experience deploying AI/ML services and applications on at least one major cloud platform (Azure, AWS, GCP)
Pratrical skills using modern ML and Generative AI frameworks (Langchain, PyTorch, Tensorflow, Hugging Face and other open-source/ APIs and similar)
Experience with LLM applications and techniques, such as Retrieval-Augmented-Generation (RAG), Chane-of-Thought (CoT) prompting, and open-source LLMs fine tuning
Ability to write production ready code, with strong expertise in designing and implementing ML pipelines
Excellent problem-solving skills with a critical and creative mindset
Exceptional communication skills and a collaborative approach to teamwork
BSc, master or PhD in appropiate technology field (Computer Science, Electrical Engineering, Statistics, Applied Math, etc.)
A Big Plus If You Have:
Extensive experience in integrating and working with vector databases (e.g. Elastic, Milvus and more) for high-performance similarity search, semantic search and embeddings management.
Experience with building continuous integration and monitoring for Machine Learning applications.

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:
MS or PhD in Computer Science/ Electrical Engineering
15+ Years of extensive machine learning / deep learning research or work experience.
Knowledge of application areas such as natural language processing and speech processing.
Excellent programming skills in some rapid prototyping environments such as Python.
Expertise with deep learning frameworks such as PyTorch.
A track record of research excellence demonstrated in publications at leading conferences and journals.
Ways to stand out from the crowd:
Strong C++ programming skills.
Systems software engineering knowledge and expertise in optimizing software for computational performance.
Contribution to open source software projects.

Requirements:
Masters/Ph.D. in Computer Science, Electrical Engineering, Machine Learning, information systems engineering, or related field.
5+ years of hands-on experience with developing & maintaining production class Machine Learning projects aimed towards solving business problems.
High proficiency in Python
Hands-on proficiency with modern generative AI models, prompt engineering, multi-agents, and RAG architectures. Also, a solid understanding of transformers, optimized fine-tuning techniques, and evaluation methodologies of LLMs while using relevant frameworks (Hugging Face, LangChain, LlamaIndex, etc)
Familiarity with embedding models and vector databases - advantage
Experience in data exploration and visualization.

Requirements:
Requirements:
Ph.D. in Computer Science, Machine Learning, or a related field, or equivalent industry experience.
At least 5 years experience as algorithm developer or researcher.
Proven track record in generative modeling, specifically diffusion-based models for image and/or video generation.
Strong proficiency in Python and deep learning frameworks such as PyTorch or JAX.
Solid understanding of probabilistic modeling, score-based generative methods, and denoising diffusion techniques.
Experience with large-scale model training and high-performance computing environments.
Publications in top AI/ML conferences or journals.

Preferred Qualifications:
Experience in latent diffusion, video generative models, or multi-modal generation (e.g., text-to-image/video).
Contributions to open-source generative modeling libraries.
Familiarity with model evaluation metrics and benchmarking protocols for generative content.
Prior experience in a startup or fast-paced R&D environment.

Requirements:
- Bachelors degree in data Science, Computer Science, Computer Engineering, or related field. - 2+ years of experience in data Science roles. - Proven experience managing AI/ML project lifecycles from conception to deployment. - Deep understanding of classic ML, deep learning, and LLMs. - Strong proficiency in Python and experience with frameworks such as PyTorch, Scikit-Learn, and TensorFlow. - Hands-on experience with low-level programming in C / C ++. - Team player with strong collaboration and communication skills. - Quick learner with ability to adapt to new tools, methods, and frameworks. Preferred Qualifications: - Background in mobile app research or development ( Android / IOSgreenTxtBg!). - Image processing experience. - Reverse engineering experience with tools like IDA, gdb, and lldb. - Knowledge of OS internals. - Cybersecurity background with understanding of threat landscapes and attack vectors. About the Company:our company'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 our company, 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. Leading financial, healthcare, m-commerce, consumer, and B2B brands use our company to upgrade mobile DevSecOps and protect Android & IOS apps, mobile customers, and businesses globally. Today, our company's customers use our platform to secure over 50,000+ mobile apps, with protection for over 1 billion mobile end users projected.
we are an Equal Opportunity Employer. We are committed to diversity, equity, and inclusion in our workplace. We do not discriminate based on race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other characteristic protected by law. All qualified applicants will receive consideration for employment without regard to any of these characteristics.

Requirements:
B.Sc./M.Sc. in Electrical Engineering, Computer Engineering, Computer Science, or equivalent experience.
5+ years of experience in VLSI CAD tool development, with a strong focus on integrating AI/ML techniques into EDA workflows.
Proficiency in Python and at least one AI/ML framework (such as TensorFlow, PyTorch, or scikit-learn).
Hands-on experience with VLSI physical design and familiarity with industry-standard EDA tools (e.g., Synopsys, Cadence).
Knowledge of data preprocessing, feature engineering, and model deployment as applied to VLSI design challenges.
Experience developing and maintaining automation scripts (Python, Perl, Tcl, Make).
Strong analytical skills in evaluating the impact of AI solutions on design quality, performance, and productivity.
Excellent communication skills and the ability to work cross-functionally in a fast-paced environment.
Self-motivation, attention to detail, and a track record of delivering robust solutions to production.
Ways to stand out from the crowd:
Demonstrated experience deploying AI/ML models in production VLSI CAD environments.
Contributions to open-source AI/EDA projects or publications in relevant conferences/journals.
Deep understanding of VLSI design challenges-such as timing closure, power optimization, or yield enhancement-and how AI can address them.
Experience with cloud-based or distributed compute environments for large-scale AI training and inference.
Strong ownership, curiosity, and a passion for continuous learning and innovation.

Requirements:
At least 4-5 years of experience in building production grade backend software systems
Understanding of microservice design and architecture
Strong experience in designing, building and maintaining scalable infrastructures including deployment, DBs, communication
Strong proficiency in Python
Understanding of Machine Learning lifecycle and best practices for AI
Excellent problem-solving abilities, coupled with a creative and strategic mindset
Proven ability to work effectively in a team setting