דרושים » AI » Staff Data AI Engineer

Requirements:
A bachelor's degree or higher in Computer Science, Data Science, or a related field
Proven experience in developing LLM-based application architectures
Proficiency in ML along with relevant tools, processes, and frameworks, such as TensorFlow, PyTorch, Keras, natural language processing (NLP), and reinforcement learning from human feedback (RLHF)
Proficiency in LLM-related tools, processes, and frameworks, including OpenAI Models and APIs, Hugging Face Transformers, LangChain, vector databases, and prompt management tools like PromptPerfect/PromptBase and Guardrails
Experience with cloud platforms, such as AWS, Google Cloud, or Azure
Proficiency in Python programming
Experience deploying LLM-based applications in a production environment
Excellent problem-solving and analytical skills
Strong communication skills and the ability to collaborate effectively in a team.

Requirements:
Bachelors degree in Computer Science or a related technical field, or equivalent experience.
4+ years of experience in product management, with a proven track record in SaaS or AI-driven products.
1+ years of hands-on experience building agents based on large language models (LLMs).
Deep knowledge of AI agent frameworks, including but not limited to vibe coding, prompt engineering, and multi-step agent workflows.
Experience with no-code/low-code integration platforms is a plus.
Strong product management skillsdefining product vision, setting strategy, prioritizing features, and driving cross-functional alignment using tools like Jira.
Demonstrated ability to create enablement content, deliver training, and lead product demos for technical solutions.
Excellent interpersonal and communication skills; adept at collaborating with engineers, product managers, sales engineers, and customers.
Passion for innovation, curiosity about emerging AI trends (accessibility is a plus), and a data-driven approach to experimentation.

Requirements:
5+ years of experience in AI/ML engineering or applied machine learning roles.
Proven experience designing, developing, and scaling production-grade AI systems (LLMs, conversational AI, or agent-based systems preferred), preferably based on known agents frameworks such as LangChain, LangGraph
Advanced proficiency in Python and experience writing clean, maintainable, and testable code.
Strong background in prompt engineering, LLM orchestration, and model evaluation.
Demonstrated ability to drive technical initiatives across disciplines (engineering, product, and data science).
Excellent communication skills with the ability to translate complex ideas into practical solutions.
Ability to work in cross-functional teams and communicate technical decisions clearly.

Requirements:
Bachelors or Masters degree in Computer Science, Cybersecurity, AI/ML, or related field
3+ years in security research, application security engineering
Hands-on with LLMs, prompt engineering
Proficient in Python
Deep understanding of SAST/SCA tools (e.g. SonarQube, Snyk) and their outputs
Familiarity with container security tooling (Docker, Kubernetes, Trivy)
Strong data analysis skills for evaluating model outputs and security telemetry
Excellent written and verbal communication; ability to distill complex topics for diverse audiences
Collaborative mindset; experience working across research, engineering, and security teams

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:
What Experience Will Drive to Success
* Bachelors degree in data Science, Computer Science, Computer Engineering, or related field.
* 3+ years of hands-on software development experience.
* 1+ years of experience in AI engineering, with a proven track record of building and deploying AI systems.
* Strong proficiency in Python.
* Experience with AI frameworks and protocols such as LangChain, LangGraph, OpenAI, MCP, A2A, etc..
*  Solid understanding of LLM integration and prompt engineering for complex reasoning.
* Experience with Git and Jenkins.
* Strong problem-solving skills, a passion for innovation, and a self-driven mindset.
* Excellent communication and collaboration skills.
*  Hands-on experience with Big Data processing frameworks (Advantage).
*  data science experience or familiarity with applied Machine Learning (Advantage). What We Are Looking For Independent and Self-Driven: Were building an AI Department from the ground up, so we need someone 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: we are 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 our company. You should be able to adapt to changing requirements and quickly solve problems in a fast-paced, dynamic environment. Can-Do Attitude: Were seeking motivated individuals who take the initiative, face challenges head-on, and can work independently while contributing to the team's success. About the Company: our 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 us, 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 customers use our platform to secure over 50,000+ mobile apps, with protection for over 1 billion mobile end users projected.

Requirements:
* 5+ years of experience as a backend Engineer or similar role, specifically building and operating production-grade, scaled APIs and microservices.
* Experience with Generative AI concepts and Large Language Models (LLMs).
* Proven self-learner with the ability to quickly grasp new technologies and complex domains.
* Hands-on experience with Kubernetes (K8s) and cloud platforms (AWS, GCP).
* Experience with CI/CD pipelines and integrating automated tests
* Proven ability to solve complex technical problems and make data -driven decisions.
* Excellent communication and collaboration skills, with a track record of working effectively in a team-oriented environment.
* Hands-on experience with observability tools such as Prometheus, OpenTelemetry etc. Bonus Points:
* Familiarity with Go programming language.
* Experience working within an Infrastructure or Core Engineering team.
* Experience with LLM orchestration frameworks like LangChain.
* Familiarity with prompt engineering, prompt optimization techniques, and managing system prompts.

Requirements:
Proven software development experience, with hands-on familiarity with modern IDEs, developer tools, and workflows.
Deep interest in AI and its applications in software engineering including copilots, AI-assisted programming, and code generation.
Demonstrated ability to take initiative, experiment, and lead change across teams.
Strong communication and collaboration skills comfortable influencing engineers and managers alike.
Ability to think strategically and translate AI potential into practical engineering wins.
Experience in R&D organizations or platform/DevEx roles advantage.
Prior experience with AI tooling, prompt engineering, or LLM-based integrations advantage.

Requirements:
5+ years of proven experience in AI / ML roles that include both research and production hands on work
5+ years of experience writing production-grade code in Python using modern paradigms such as Event Driven Architectures, microservices, and the like
Proficiency in building, training, running, and evaluating deep learning models using Hugging Face, Pytorch, Tensorflow, or similar frameworks
Proficiency in building production-grade Generative AI applications using techniques such as multi-agent architectures, RAG and fine tuning
Experience with the entire ML model lifecycle, from ideation all the way to productization
Experience with MLOps frameworks such as Amazon SageMaker, Vertex AI or similar for building end-to-end ML pipelines
Deep understanding of ML theory and the techniques to apply it in the real world, such as tuning, feature and error analysis, cross-validation, and over/underfitting
Bachelor's degree or higher in Computer Science or a similar computational discipline
Excellent problem-solving abilities and analytical skills
Strong communication and team collaboration skills.

Requirements:
2+ years of experience as an AI engineer or applied ML engineer working with LLMs (e.g. OpenAI, Claude, Mistral, etc.).
Proven experience with LangChain and/or LangGraph to build real-world AI agents or workflows.
Proficiency in Python/Type script, with hands-on experience in LLM frameworks and orchestration tools.
Experience designing and deploying autonomous agents, memory modules, and tool-using systems.
Familiarity with vector databases (FAISS, Pinecone, Weaviate, etc.) and knowledge retrieval systems.
Solid understanding of NLP workflows, prompt engineering, and tokenization strategies.
Experience with RESTful APIs and backend data integration.
Strong debugging, problem-solving, and architectural design skills.
Experience with Typescript, especially in AI agent or tool integration.
Prior experience deploying AI in production systems.
Familiarity with MLOps and CI/CD pipelines for AI-based applications.
Experience working with cloud platforms (AWS / GCP, or Azure).
MSc in Machine Learning, Computer Science, or a related technical field.