דרושים » הנדסה » data Scientist AI Platform

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:
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. At our company, were not about checklists. If you dont meet 100% of the requirements for this role but still feel passionate about the position and think you have the right skills and qualifications to excel at it, we want to hear from you.

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.

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:
Minimum 3 years of professional experience in Data Science roles
Hands-on experience in networking and/or cybersecurity domains
Strong foundation in classical machine learning methods (supervised, unsupervised learning, clustering)
Practical experience with deep learning frameworks such as TensorFlow or PyTorch, including NLP techniques
Proven experience deploying models on cloud platforms like AWS, Azure, or Google Cloud
Excellent analytical, problem-solving, and communication skills
Self-motivated, collaborative, and able to work independently
How to Stand Out
Experience building agentic systems using Retrieval-Augmented Generation (RAG), including tool orchestration, benchmarking frameworks, and vector databases (e.g., FAISS, Pinecone)
Prior experience working in a fast-paced, high-growth environment
Advanced degree (MSc or PhD) in Computer Science, Statistics, Mathematics, or a related quantitative field.

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:
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:
8+ years of experience in data engineering, software engineering, or MLOps, with hands-on leadership in designing modern data platforms and distributed systems.
Proven experience implementing GenAI applications or infrastructure (e.g., building RAG pipelines, vector search, or custom LLM integrations).
Deep understanding of big data technologies (Kafka, Spark, Iceberg, Presto, Airflow) and cloud-native data stacks (e.g., AWS, GCP, or Azure).
Proficiency in Python and experience with GenAI frameworks like LangChain, LlamaIndex, or similar.
Familiarity with modern ML toolchains and model lifecycle management (e.g., MLflow, SageMaker, Vertex AI).
Experience deploying scalable and secure AI solutions with proper attention to privacy, hallucination risk, cost management, and model drift.
Ability to operate in ambiguity, lead complex projects across functions, and translate abstract goals into deliverable solutions.
Excellent communication and collaboration skills, with a passion for pushing boundaries in both data and AI domains.

Requirements:
M.Sc. or Ph.D. in Computer Science, Mathematics, Engineering or a related technical field.
5+ years of experience in NLP, machine learning or deep learning.
2+ years of experience managing ML/AI or software engineering teams
Excellent understanding of Deep Learning and modern NLP fundamentals, including Transformers, LLMs, RAG and Agents.
Hands-on experience with deep Learning frameworks (Pytorch, Tensorflow or JAX) and other relevant libraries (HuggingFace, vLLM, etc.).
Experience with LLM fine-tuning and deployment at scale on distributed GPU clusters.
Familiarity with STT / ASR models and common audio / speech processing methods.
Strong software engineering skills in Python.
Leadership
Proven ability to lead high-impact teams in a fast-paced applied research environment.
Experience defining and executing ambitious technical roadmaps and contributing to strategic technical decisions.
Passion for mentorship, team-building, and fostering a culture of innovation.
Strong cross-functional collaboration skills and the ability to work closely with PMs, engineers, and other stakeholders.

Requirements:
Must:
BSc in Computer Science or related degree, or equivalent practical experience.
4+ years of hands-on experience as a software Engineer
Strong proficiency in Python and experience with AI/ML libraries (e.g., PyTorch, TensorFlow, Hugging Face).
Experience with AI APIs (OpenAI, Anthropic, Google AI, Microsoft AI) and integrating them into engineering workflows
Hands-on experience with developer productivity tools, AI-enhanced automation, and knowledge management systems
Strong problem-solving skills and ability to build AI-powered solutions that engineers love to use.
Nice to Have:
Deep understanding of LLMs, RAG (Retrieval-Augmented Generation), fine-tuning, and prompt engineering.
Experience with data pipelines, embeddings, and vector databases for AI-powered search and automation.
Experience working with cloud-based AI platforms and scalable AI architectures
Knowledge of containerization (Docker, Kubernetes) and CI/CD pipelines for deploying AI applications.
Experience with AI Ops, observability tools, and monitoring AI applications in production.
Familiarity with LangChain, AutoML, MLOps frameworks, and workflow automation tools.
A background in software engineering, DevOps, or developer tooling.
Strong entrepreneurial mindset, able to identify opportunities, move fast, and drive AI adoption in a high-impact environment.
Published research, open-source contributions, or side projects demonstrating innovative AI applications.
Why Join Us?
This role is for builders, problem-solvers, and AI enthusiasts who want to push the boundaries of engineering productivity with AI. Youll be at the forefront of AI-powered platform engineering, shaping how our company leverages AI to supercharge innovation, efficiency, and automation.
If youre looking to build game-changing AI platforms, experiment with cutting-edge tech, and make a real impactjoin us!