לוח משרות דרושים הייטק AI

Requirements:
2+ years of experience in applied AI, ML research, or systems involving language models.
Solid experience as a software engineer, with preference for full-stack development background to ensure strong domain understanding.
Proven experience in data science and algorithmic development.
Deep understanding of transformer-based LLMs, vector retrieval, and prompt engineering.
Familiarity with building agents is a plus, but not requiredwe will support your training in this emerging space.
Experience with Python and working with LLM APIs or fine-tuning pipelines.
Familiarity with tools like Docker, cloud environments (AWS/GCP), and scalable infrastructure.
Advantage: Experience in developer tooling, compilers, or software engineering workflows.
Advantage: Research or publications in AI planning, LLM agents, or program synthesis.

Requirements:
M.Sc. in Computer Science or related field.
Minimum 3 years of hands-on security R&D AI, application or network or cloud.
Strong Python programming skills with a focus on production-level code.
Proven ability to work both independently and collaboratively in a team environment.
Self-starter DNA you should be able to thrive on autonomy, move fast, and communicate well with stakeholders at every level.

Requirements:
2 + years as a leader of engineering or data science teams, with a track record of shipping data-intensive tools or services to production.
6 + years hands‑on building data-driven solutions with Python and SQL.
Experience deploying services using cloud-based infrastructure and data tools such as PostgreSQL, Databricks, and Spark.
Strong understanding of the key concepts and usage of modern AI tools such as LLMs, RAG systems, and AI agents.
Solid software engineering fundamentals (including design patterns, data structures, and version control) and familiarity with Agile practices.
Proven ability to manage project scope, timelines, and cross‑team dependencies.
Comfort implementing rapid, iterative development processes while also prioritizing quality, reliability, and maintainability.
Excellent command of English, both verbal and written, and comfortable presenting technical topics to non‑technical stakeholders.
Its even better if you have:
Proficiency with CI/CD tools and practices, containers, serverless architectures, and automated testing and monitoring.
Experience deploying models to production using leading machine learning frameworks such as TensorFlow or PyTorch.
Experience with Agile development processes and project management in JIRA.
Expertise in machine learning metrics and monitoring.
Experience with geospatial analysis, government data, survey research, or civic tech applications.
Demonstrated success hiring and developing technical talent.
Contributions to open‑source projects or an advanced degree in a relevant field.

Requirements:
MSc in Computer Science, Engineering, or a related field
Focus on AI, ML, or DS.
5+ years of experience in DS roles, with a strong emphasis on building and deploying machine learning models in production environments.
Expertise in Python and SQL.
Experience with machine learning frameworks such as TensorFlow or PyTorch.
Familiarity with cloud platforms (e.g., AWS, GCP) and containerization tools (e.g., Docker, Kubernetes).
Proven experience in developing, fine-tuning, and deploying ML models, particularly in NLP.
Ability to translate complex business problems into data-driven solutions.
Excellent verbal and written communication skills, with the ability to convey complex technical concepts to non-technical stakeholders.

Requirements:
MSc in Computer Science/Engineering or related field with a focus on applied statistics, AI, machine learning, or related fields - a must.
6+ years of production environment experience, working with predictive and probabilistic models, clustering algorithms, classification models, search and recommendation techniques - a must.
Proven record for successful production implementation of translating product/business requirements into a technical solution.
Team player, Ability to handle several tasks simultaneously.
Strong knowledge in Python, SQL, and NoSQL.
Spark and Big data technologies experience an advantage.
Research experience - an advantage.
Experience with e-commerce - an advantage.

Requirements:
4+ years of product management experience, ideally with a focus on AI/ML, NLP, or infrastructure/platform products.
Strong technical background in ML infrastructure, data systems, or engineering;
Experience building or scaling systems based on large language models or unstructured data processing.
Strong understanding of the AI/LLM ecosystem - including model deployment, evaluation, prompt orchestration, and data pipelines.
Proven track record of leading cross-functional teams to deliver technically complex products with measurable impact.
Excellent communication and collaboration skills, especially in technical environments.
Ability to operate in ambiguity.
Ability to drive clarity through structured thinking and sharp execution.
Background in ML infrastructure, AI products, or applied research is a plus.

Requirements:
1+ years leading projects and teams in tech, product ops, or support tech
Strong experience with chatbot tools and prompt optimization (Experience with Forethought is a big plus)
Manage AI projects, tools, and team delivery within Customer Care
Strong analytical and problem-solving skills
Detail-oriented and data-driven mindset
Strong communicator with a bias for action and improvement
Strong organizational and collaboration skills
Hands-on with support tools (zendesk, Salesforce, analytics tools, etc.)

Requirements:
- 3-6 years of experience in software development, with a strong foundation in backend or full-stack development.
- Proficiency in integrating AI technologies, such as LLMs, into software solutions.
- Experience developing scalable, cloud-based distributed systems in microservices architecture.
- Familiarity with version control systems, especially Git, and collaborative development workflows.
- Strong understanding of secure coding practices and principles.
- Excellent communication skills, fast learner, results-driven, and a strong team player.
Desired qualifications:
- Hands-on experience with tools like GitHub Copilot, Claude, or Cursor.
- Experience with AWS services like S3, Lambda, and Bedrock.
- Experience working with Cloud Native designs and ecosystem (Docker, Kubernetes, Helm).
- Background in cybersecurity or a strong understanding of security best practices.
- Experience with big data technologies and processing large datasets.

Requirements:
6+ years writing backend code, with at least 2-3 years in TypeScript or modern JavaScript.

Solid experience with NestJS (modules, DI, guards, testing utilities).

Hands-on PostgreSQL: schema design, indexing, partitioning, and query optimisation.

Production use of Elasticsearch or OpenSearch: indexing strategies, ILM.

Practical familiarity with Temporal (or a similar workflow engine such as Cadence or Step Functions) - nice to have

Comfortable deploying and debugging services on AWS and working with IaC tools.

Good testing habits (unit, integration, e2e) and an eye for clean, readable code.

Clear written and spoken communication; willingness to give and receive constructive feedback.

Requirements:
6+ years of experience in DevOps, MLOps, or infrastructure roles with a focus on ML model delivery.

Proven hands-on experience deploying GPU-based models (LLMs, vision, transformers) using vLLM or Triton.

Deep knowledge of AWS EKS and Kubernetes, with practical experience configuring Karpenter and KEDA for auto-scaling GPU workloads.

Experience building pipelines using Jenkins, GitHub Actions, and managing releases for ML and application codebases.

Familiarity with AWS SageMaker, ClearML, or similar platforms for ML orchestration and experimentation.

Strong scripting and automation skills in Python, Bash, and working knowledge of containerization (Docker).

Solid grasp of networking, IAM, and cloud security fundamentals.

Requirements:
Must-Have Qualifications

Hands-on experience with LLM-based product development, including prompt design, tuning, or evaluation

Proven ability to design and iterate on prompts for models like GPT-4, Claude, or LLaMA, including few-shot and CoT techniques

Proficiency with Python and prompt-engineering libraries or platforms (e.g., LangChain, LlamaIndex, vector DBs)

Strong understanding of NLP, ML, or data science fundamentals especially around generation, embeddings, and evaluation

Comfortable working closely with engineers and PMs to bring AI features to production

Excellent communication skills, with the ability to explain complex model behavior to technical and non-technical stakeholders

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.