דרושים » תוכנה » NLP Data Scientist

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:
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:
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:
5+ years of experience in applied data science or machine learning roles, with a strong focus on personalization, recommender systems, or predictive modeling.
Advanced degree (MS/PhD) in Computer Science, Machine Learning, Statistics, or a related field, or equivalent hands-on experience.
Proficiency in Python and ML frameworks
Strong grounding in data pipelines and working knowledge of tools such as SQL, Spark, Airflow, and modern MLOps stacks.
Experience building real-time or near-real-time recommendation systems at scale.
Bonus points for working with conversational agents, LLM-based systems (e.g. RAG, prompt engineering), or user embeddings.
Passion for crafting user-centric AI, and curiosity about human behavior in the context of travel
Ability to communicate technical concepts clearly and collaborate cross-functionally with product, design, and engineering teams.

Requirements:
BSc in Computer Science or a related field.
6+ years of experience building and deploying ML systems in production environments.
Proficiency in Python and production frameworks like FastAPI, Databricks, SageMaker, and MLflow.
Proven track record in deploying and maintaining ML/LLM services (APIs, microservices, serverless, or containerized).
Strong understanding of software engineering fundamentals: object-oriented design, testing, version control, CI/CD, and performance optimization.
Experience working with agentic workflows or LLM-based agents.
Ability to work independently and break down complex, ambiguous problems into structured solutions.
Strong communication skillsable to explain technical concepts to both technical and non-technical stakeholders.
Advantages:
Hands-on experience with Kubernetes, Airflow, Spark, ArgoCD, and Docker.
Experience working with databases such as Elasticsearch, vector databases, PostgreSQL, and SQL.
Experience fine-tuning or integrating open-source LLMs in production environments (e.g., RAG, LoRA, agent frameworks).
Contributions to open-source ML or MLOps projects.

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:
6+ years of experience as a Backend and/or Machine Learning Engineer.
Bachelors degree in Computer Science or a related field from a leading university.
Proficiency in Python and Java or C#.
Experience with ML and Generative AI frameworks such as LLMs, LangChain, Hugging Face, TensorFlow, or PyTorch.
Deep understanding of software architecture and deployment patterns (e.g., microservices).
Strong problem-solving skills and the ability to quickly develop working solutions.
Excellent communication and collaboration capabilities.
Self-starter attitude with a passion for continuous learning.
Bonus if you have:
M.Sc. in Computer Science, Software Engineering, or a related field.
Experience developing and scaling LLM-powered applications.
Familiarity with DevOps practices including CI/CD pipelines and cloud infrastructure.

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. Preferred Qualifications:
* Background in academic or industrial research in AI.
* Familiarity with the e-commerce domain and related data challenges.
* Previous experience leading projects in a DS capacity.

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:
Natural scientific curiosity and ability to handle complex problems
At least 6 years of experience in hands-on data science projects
High proficiency in python and at least good familiarity with SQL
Advanced degree (MSc or PhD) in Machine Learning, Computer Science, Electrical Engineering, Physics, Statistics, Applied Mathematics, or a related field or equivalent military experience required
Deep understanding of probability, statistics, and machine learning models with a proven track record of selecting, modifying, and applying advanced algorithms to solve practical problems
Demonstrated ability to run end-to-end research POCs, from conceptualization to solutions, including designing, executing, analyzing, and concluding research methodologies and outcomes
Good communication skills, with the ability to convey complex research findings clearly and effectively to both technical and business audiences
Preferred
Background in the cybersecurity domain
Experience with recommender systems
Experience working with big data platforms (e.g., GCP)
Experience with LLM-based algorithm design
Familiarity with cloud-native architectures and services for data processing.