דרושים » תוכנה » Senior ML Engineer

Requirements:
Advanced degree (M.Sc. or Ph.D.) in Electrical Engineering, Physics, Applied Mathematics, Computer Science, or a related quantitative discipline.
5+ years of hands-on experience in developing and deploying machine learning, signal processing, or algorithmic solutions, with emphasis on raw or low-level data (e.g., sensor data, audio, video streams, or medical imaging).
Proven expertise in time-series analysis and handling large-scale, complex datasets from acquisition to production deployment.
Strong Python programming skills, with the ability to write clean, modular, and testable production-grade code.
Demonstrated experience deploying ML/DSP pipelines into production environments, ideally in high-availability systems.
Familiarity with ML/DL frameworks such as PyTorch, TensorFlow, scikit-learn, and gradient-boosting libraries (e.g., XGBoost, LightGBM).
Strong collaboration and communication skills, with the ability to work effectively across interdisciplinary teams including software engineers, physicists, and external stakeholders.

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:
What Experience Will Drive to Success:
* Bachelors degree in data Science, Computer Science, Computer Engineering, or related field.
* 2+ years of experience in AI/ML engineering, with a proven track record of building and deploying ML & AI systems.
* Strong programming skills in Python and experience with ML frameworks such as TensorFlow, PyTorch, and Scikit-Learn.
* Hands-on experience with Big Data processing frameworks (Apache Spark, Dask, Ray).
* Hands-on experience with LLMs and AI Frameworks (LangChain, OpenAI, HuggingFace, LangGraph, etc.)
* Experience with Git and Jenkins.
* Strong problem-solving skills, a passion for innovation, and a self-driven mindset.
* Excellent communication and collaboration skills.
* Familiarity with AWS AI/ML services and cloud-based deployments (Advantage).
* Experience working with MLOps tools, including model registry, experiment tracking, and model serving (Advantage).
What We Are Looking For Independent and Self-Driven: Were building an AI Department from the ground up, so we need someone who is 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: Appdome is 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 Appdome. You should be able to adapt to changing requirements and quickly solve problems in a fast-paced, dynamic environment. Can-Do Attitude: Were looking for motivated individuals who take the initiative, face challenges head-on, and can work independently while contributing to team success. About the Company: Appdome'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 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.

Requirements:
Experience developing large scale systems. Experience with filesystems, server architectures, distributed systems, SQL and No-SQL. Experience with Spark and Airflow / other orchestration platforms is a big plus.
Highly skilled in software engineering methods. 5+ years experience.
Passion for ML engineering and for creating and improving platforms
Experience with designing and supporting ML pipelines and models in production environment
Excellent coding skills in Java & Python
Experience with TensorFlow a big plus
Possess strong problem solving and critical thinking skills
BSc in Computer Science or related field.
Proven ability to work effectively and independently across multiple teams and beyond organizational boundaries
Deep understanding of strong Computer Science fundamentals: object-oriented design, data structures systems, applications programming and multi threading programming
Strong communication skills to be able to present insights and ideas, and excellent English, required to communicate with our global teams.
Bonus points if you have:
Experience in leading Algorithms projects or teams.
Experience in developing models using deep learning techniques and tools
Experience in developing software within a distributed computation framework.

Requirements:
MSc/Ph.D. in Statistics, computer science, data science or a related field
5+ years of experience of exploring, building and deploying ML and data systems in production
Strong programming skills in Python focusing on ML frameworks such as Sklearn, XGBoost or TensorFlow
Experience with distributed and stream processing, Cloud ML infrastructure and feature store tools
Expertise in supervised and unsupervised machine learning models (e.g., classification, anomaly detection or clustering)
Experience writing code in Agile, CI/CD-based production environments
Proficient in communicating technical and research ideas and collaborating effectively across teams and organizational stakeholders
Experience in Fintech solutions is a big advantage

Requirements:
Experience developing large scale systems. Experience with filesystems, server architectures, distributed systems, SQL and No-SQL. Experience with Spark and Airflow / other orchestration platforms is a big plus.
Highly skilled in software engineering methods. 5+ years experience.
Passion for ML engineering and for creating and improving platforms
Experience with designing and supporting ML pipelines and models in production environment
Excellent coding skills in Java & Python
Experience with TensorFlow a big plus
Possess strong problem solving and critical thinking skills
BSc in Computer Science or related field.
Proven ability to work effectively and independently across multiple teams and beyond organizational boundaries
Deep understanding of strong Computer Science fundamentals: object-oriented design, data structures systems, applications programming and multi threading programming
Strong communication skills to be able to present insights and ideas, and excellent English, required to communicate with our global teams.
Bonus points if you have:
Experience in leading Algorithms projects or teams.
Experience in developing models using deep learning techniques and tools
Experience in developing software within a distributed computation framework.

Requirements:
Strong problem-solving mindset, with a passion for continuous innovation.
5+ years of professional experience in Data Science/ML Engineering roles, including at least one role with a tenure of two years or more in the same organization.
Masters or Ph.D. degree in Computer Science, Engineering, or a related field.
Demonstrated accountability and stakeholder management: Capable of gathering requirements and translating them into actionable, data-driven solutions, while taking full ownership of the outcomes.
Proven track record of deploying ML solutions to production, adhering to proper MLOps practices throughout the model lifecycle.
Working Experience with LLMs, usage in domain-specific problems.

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:
4+ years of hands-on experience in software engineering (Backend preferably in Python).
2+ years of experience in machine learning pipelines on cloud environments.
Knowledge in statistics and machine learning techniques.
Proven ability to lead product feature development, from concept to production.
Experience with large scale, high performance, production environments.
Experience working with SQL and NoSQL databases.
Experience in AWS cloud environment.
Advantages:
Bs.c / Ms.c in Computer Science / Software Engineering.
Experience with ML Frameworks such as PyTorch, TensorFlow and MLFlow.
Experience with Deep Learning, NLP and LLM pipelines (RAG and agentic systems).

Requirements:
5+ years of experience building large-scale distributed systems or platforms, preferably in ML or data-intensive environments
Proficiency in Python with strong software engineering practices, familiarity with data structures and design patterns
Deep understanding of orchestration systems (e.g., Kubernetes, Airflow, Argo) and distributed computing frameworks (e.g., Ray, Spark, Dask) and
Experience with GPU compute infrastructure, containerization (Docker), and cloud-native architectures
Proven track record of delivering production-grade infrastructure or developer platforms.
Solid grasp of ML workflows, including model training, evaluation, and inference pipelines