דרושים » AI » Software Developer- AI & Innovation group 22854

Requirements:
3+ years of experience in MLOps, ML infrastructure, or AI platform engineering.
2+ years of hands-on experience in ML pipeline automation, large-scale model deployment, and infrastructure scaling.
Expertise in deep learning frameworks (like PyTorch, TensorFlow, JAX) and MLOps platforms (like Kubeflow, MLflow, TFX).
Proven track record of building production-grade ML systems that scale to billions of predictions daily.
Deep knowledge of Kubernetes, cloud-native architectures (AWS/GCP), and infrastructure as code (Terraform, Helm, ArgoCD).
Strong software engineering skills in Python, Bash, and Go, with a focus on writing clean, maintainable, and scalable code.
Experience with observability & monitoring stacks (Prometheus, Grafana, Datadog, OpenTelemetry).
Strong background in security, compliance, and model governance for AI/ML systems.
Leadership & Execution:
Proven ability to lead high-impact engineering teams in a fast-paced AI environment.
Ability to drive technical strategy while remaining hands-on in critical areas.
Strong cross-functional collaboration skills, working closely with research and engineering teams.
Passion for automation, efficiency, and designing scalable self-service MLOps solutions.
Experience in mentoring and coaching engineers, fostering a culture of innovation and continuous learning.
It Would Be Great If You Have:
Experience working with LLMs and large-scale generative AI models in production.
Expertise in optimizing model inference latency and cost at scale.
Contributions to open-source MLOps tools or AI infrastructure projects.

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:
4+ years of hands-on experience as a Full-Stack Developer.
Proficiency in React, TypeScript, Node.js or Go (or any modern backend framework), and Python.
Solid backend experience working with APIs, micro services, and cloud-native infrastructure.
A hands-on builder who thrives on learning fast, testing ideas, and refining through iteration.
Excellent communication and collaboration skills in a cross-functional team environment.
Strong production mindset with focus on troubleshooting, observability, and quality monitoring.
Nice-to-Have:
Experience integrating AI technologies.
Experience in growth-focused or data driven product teams.
Understanding telemetry, analytics, and A/B testing frameworks.
Background in cybersecurity, SASE, or network/cloud security products.

Requirements:
B.Sc. in Computer Science or a related field.
5+ years of experience in backend software development, including system design and architecture.
Proficiency in at least one backend programming language (We write in Go).
Strong understanding of microservices architecture, RESTful APIs, and relational databases.
Deep familiarity with Kubernetes and the cloud-native ecosystem.
Demonstrated ability to tackle complex technical challenges and deliver high-quality solutions.
Ways to stand out from the crowd:
Expertise in Kubernetes internals and advanced cloud-native technologies.
Hands-on experience with HPC or AI/ML platforms.
Familiarity with AI inference workloads and performance optimization.
Proficiency in Linux, with knowledge in networking, security, storage, and virtualization.

Requirements:
Minimum of 4 years of experience in software development within a cloud environment
Strong proficiency in designing and developing scalable, distributed systems
Experience with Kubernetes (K8s), cloud infrastructure (AWS, GCP, or Azure), and cloud-native development practices
Solid understanding of performance optimization, troubleshooting, and functional/non-functional testing
Proficiency in Python, Go, or other backend programming languages
Experience with CI/CD pipelines, infrastructure as code (Terraform / Pulumi, Helm, ArgoCD) advantage
Hands-on experience with AI/ML development, including monitoring ML models, evaluating performance

Requirements:
Requirements:
5+ years of experience as a backend/software engineer, preferably in Python, Go, or Java.
Strong experience with designing APIs, building microservices, and integrating third-party services.
Familiarity with ML workflows: model serving, feature extraction, and batch vs real-time inference.
strong architectural/design skills, including working with message queues like Kafka, relational and NoSQL databases, and distributed systems.
Experience deploying services in containerized environments (e.g., Docker, Kubernetes).
Proficient with cloud-native tools or on-prem equivalents (e.g., logging, tracing, metrics).
Knowledge of data processing frameworks (e.g., Pandas, Spark, Airflow) is a plus.
Comfortable reading and working with Python-based ML code (scikit-learn, TensorFlow, PyTorch, etc.).
Strong ownership mindset and a collaborative attitude.

Nice to Have:
Experience with model versioning and ML serving frameworks (e.g., MLflow, Seldon, Triton).
Understanding of data privacy/security implications in model and data pipelines.
Experience working in cross-functional teams with data scientists and product owners.

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.

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

Requirements:
5+ years of experience in software engineering, applying modern design patterns and best practices.
You write clean, maintainable, and well-documented code.
Proven hands-on experience with Generative AI technologies.
Solid experience working with cloud platforms (e.g., AWS, GCP, Azure).
Deep understanding of production environments, including testing methodologies, monitoring, and deployment processes.
Strong debugging skills: you can identify, diagnose, and resolve issues while improving code readability and system reliability.
A proactive team player with strong organizational skills and a get things done attitude.
Proficient in Python and SQL.
Familiarity with software development best practices, Git, CI/CD, and modern DevOps principles.
Bachelors degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.

Requirements:
8+ years of software engineering experience, including development of a scalable server-side application
Proven Experience with cloud platforms (e.g. GCP / AWS / Azure)
Experience with the AI world, including various models, frameworks, and prompting
Understands and can integrate Generative AI solutions into backend architectures
Experience with a variety of database technologies
Experience with distributed cloud products
Advanced:
Experience with Go and Python
Experience with Kubernetes / Docker.