לוח משרות דרושים מהנדסים במרכז

Requirements:
Requirements
* At least 3 years of software development experience, including 2+ years of hands-on C/C++ programming.
* Strong understanding of operating system internals (memory management, processes, system calls).
* Genuine curiosity and passion for understanding how systems work at a fundamental level; self-driven learner who is eager to explore new technologies independently.
* Great team player who knows how to push independently when needed. Advantages
* Experience with Android or iOS internals.
* Experience with reverse engineering tools such as IDA, Ghidra, or similar.
* Familiarity with assembly and the ARM instruction set.
* Experience with NDK/JNI (Android) or low-level iOS development.
* Knowledge of cybersecurity concepts and techniques. About the company Appdome's mission is to protect every mobile app in the world 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 controls, 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. Leading financial, healthcare, m-commerce, consumer, and B2B brands use Appdome to upgrade mobile DevSecOps and protect Android & iOS apps, mobile customers, and businesses globally. Today, Appdome's customers use our platform to secure over 50,000+ mobile apps, with protection for over 2 billion mobile end users projected. Appdome is 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:
• BSc in Electrical/Aerospace/Mechanical/Computer or Software Engineering is a threshold requirement. (Bachelors in Physics/Math/Computer Science with relevant experience will also be considered.) • MSc in Systems/Electrical/Aerospace Engineering is an advantage. • At least two years as Systems Engineer/Technical Manager/Technical Product Manager in a technology company. • At least two years of hands on experience in research and development roles (or similar academic experience). • Strong MS Office (including MS Project) Skills. • Strong Presenting and Leadership abilities. • Experience with Aerospace/Military/C4I/C2 systems design and development is an advantage. • Valid Level 3 Security Clearance is a an advantage.

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:
● At least 3 years of managerial experience leading development teams up to production web applications, including monitoring and maintenance
● BSc in Computer Science or equivalent
● 7+ years of backend engineering experience, including 5+ years working with Python in production environments.
● Expertise in designing and building scalable systems with Cloud Architecture in a SaaS company
● Strong experience with async programming, REST APIs, microservices, and testing.
● Experience leading teams working on high-availability, distributed systems.
● Demonstrated ability to make architectural decisions and evaluate technical trade-offs.
● Understanding of CI/CD pipelines and IaC tools (Terraform, Helm)
● Knowledge of Celery orchestration, event-driven architectures, or streaming frameworks (RabbitMQ).
● Capable of leading technical aspects, complex projects, and a distributed, cross-functional (front-end and back-end) R&D team.
● Exceptional communication skills and high proficiency in English.
Advantages:
● Experience working with Python frameworks like Django and FastAPI
● Experience with RabbitMQ
● Experience with Celery
● Experience with Redis

Requirements:
Native-level Ukrainian or Russian
BSc in Computer Science or equivalent
8+ years of software engineering experience, including 5+ years of Python in production
3+ years in an R&D team lead, leading cross-functional teams (backend, frontend, and QA) in a production environment
Proven experience managing and leading remote teams in a fully distributed, remote-only environment
Proven experience working in a product-based company (not project/outsource)
Strong experience with Python backend development in a SaaS environment, including cloud-based, scalable, and high-availability distributed systems
Strong knowledge of REST APIs, microservices, asynchronous programming, and testing
Hands-on experience with CI/CD pipelines and Infrastructure-as-Code (e.g., Terraform, Helm)
Solid understanding of software architecture, design patterns, and technical trade-offs
Proven ability to lead projects end-to-end, from requirements and design through development and production
Excellent communication skills and high proficiency in English
Technical Experience:
Python frameworks: Django, FastAPI
Databases: PostgreSQL, MSSQL
Messaging & async processing: Celery, RabbitMQ
Caching & performance: Redis
Cloud platforms and services (Azure - advantage)
Familiarity with event-driven architectures and distributed systems
Strong grasp of KISS, DRY, SOLID, OOP principles
Advantages:
Experience with Azure cloud services
Experience with Excel Add-ins or data-heavy applications
Startup or high-growth SaaS company experience

Requirements:
6+ years software engineering experience; 4+ years building AI/ML systems.
Prior experience as a technical lead or engineering manager.
Deep understanding of agentic architectures and tool-based AI systems.
Hands-on experience with MCP and agent tool integration.
Experience with LangChain, LangGraph, or equivalent frameworks.
Strong background in LLM evals, observability, and production AI quality.
Solid experience with RAG pipelines, vector databases, and retrieval systems.
Strong Python background and system design experience.

Requirements:
3+ years of experience delivering production-grade ML/AI systems
Strong Python skills and solid understanding of the ML lifecycle
Experience with GPU infrastructure, containerization (Docker) and cloud platforms
Familiarity with microservice architectures and API development
Hands-on experience with LLM pipelines and agent orchestration frameworks (LangGraph, LlamaIndex, etc.)
Knowledge of experiment tracking tools (Weights & Biases, MLflow, or similar)
Background in scalable ML infrastructure, distributed computing, and workflow orchestration frameworks (Ray, Kubeflow, Airflow)
Experience with multi-node training (advantage)
Collaborative mindset with startup-level ownership and pragmatism

Requirements:
5+ years of experience in software engineering or ml engineering with significant focus on ML systems or backend infrastructure
Strong proficiency in Python and deep learning frameworks (PyTorch)
Hands-on experience with LLM inference engines (vLLM, TensorRT-LLM, Triton Inference Server)
Deep understanding of transformer architectures and LLM-specific optimizations (attention mechanisms, KV-cache, quantization techniques like GPTQ, AWQ, GGUF)
Experience with distributed training/fine-tuning frameworks (Ray, DeepSpeed, FSDP)
Ability to build developer-facing tools and platforms with clear APIs and documentation
Understanding of GPU performance profiling and optimization
Familiarity with LLM evaluation methodologies and benchmarking

Requirements:
6+ years software engineering experience with 4+ years applied ML.
Prior experience as a technical lead or engineering manager.
Deep understanding of ML training, evaluation, and deployment lifecycles.
Strong experience with ML frameworks and large-scale data pipelines.
Proven ownership of ML evals, monitoring, and drift detection in production.
Experience with distributed training and performance optimization.
Strong experience with feature stores, model registries, and experiment tracking.
Experience deploying and operating ML systems on Kubernetes or similar platforms.
Strong Python background and system architecture expertise.
Experience managing cross-functional ML initiatives and stakeholders.

Requirements:
5+ years of experience in infrastructure engineering, platform engineering, or DevOps, preferably supporting ML or data-intensive workloads
Experience designing and operating hybrid cloud architectures (on-premise + cloud) with focus on data/model synchronization
Familiarity with model registry solutions (MLflow or cloud-native registries) and artifact management at scale
Experience with GPU compute infrastructure, device plugins, and resource scheduling (e.g., NVIDIA GPU Operator)
Proficiency in IaC tools (Terraform) and GitOps practices (ArgoCD)
Experience with monitoring and observability stacks (Prometheus, Grafana, ELK)
Familiarity with ML workflows to understand workload characteristics and requirements

Requirements:
4+ years software engineering; 2+ years production AI/ML systems.
Hands-on experience with agentic architectures and tool calling.
Practical experience with MCP.
Experience with LangChain, LangGraph, or equivalent frameworks.
Proven experience designing and operating LLM evals.
Strong Python and API design skills.
Familiarity with RAG pipelines, vector databases, and embedding-based retrieval systems (indexing, chunking, filtering, relevance tuning).

Requirements:
6+ years in software engineering, data engineering, platform engineering, or distributed systems, with hands-on experience building and operating data infrastructure at scale.
Streaming & ingestion - Technologies like Flink, Structured Streaming, Kafka, Debezium, Spark, dbt, Airflow/Dagster
Open data lake/lakehouse - Table formats like Iceberg, Delta, or Hudi; columnar formats; partitioning, compaction, schema evolution, time-travel
Serving & retrieval - OLAP engines like ClickHouse or Trino; vector databases like Milvus, Qdrant, or LanceDB; low-latency stores like Redis, ScyllaDB, or DynamoDB
Databases - OLTP systems like Postgres or MySQL; document/search engines like MongoDB or ElasticSearch; serialization with Avro/Protobuf; warehouse patterns
Platform & infra - Kubernetes, AWS, Terraform or similar IaC, CI/CD, observability, incident response
Performance & cost - JVM tuning, query optimization, capacity planning, compute/storage cost modeling
Engineering craft - Java/Scala/Python, testing, secure coding, AI coding tools like Cursor, Claude Code, or Copilot

Requirements:
5+ Years as a Data Scientist with proven production-level impact.
Masters degree in Computer Science, Mathematics, Statistics or Engineering (PhD is a plus but not required).
Experience conducting applied research and working with Transformers, open-source LLMs, or other advanced deep learning architectures.
Strong programming skills in Python and familiarity with modern ML tooling and frameworks.
Excellent problem-solving abilities and a strong experimental mindset.
Effective collaborator with strong communication skills.
High curiosity and a passion for learning new technologies, methods, and domains.