דרושים » מדעים מדוייקים » NLP /LLM Engineer בחברת סטארט-אפ בתחום הבינה המלאכותית

Data Integrity group is at the forefront of real-time analytics, using machine learning and artificial intelligence to balance low latency and impeccable data accuracy.

Responsibilities:

Lead the development and deployment of advanced analytical models to solve complex problems, leveraging advanced statistical techniques.
Design and develop NLP models for tasks such as Named Entity Recognition, Classification, Text Similarity, Clustering and other tasks.
Collaborate with cross-functional teams, including engineers and product managers, to understand business challenges and design data-driven solutions.
Analyze large and complex data sets, applying mathematical theories and statistical methods, to produce actionable insights.
Stay current with emerging trends in data science and statistics and evaluate their applicability to business problems.
**It is possible to work from the offices in Ramat Gan and Ashkelon**

We are looking for an Algo-Dev Engineer to join one of our research teams. You will be working closely with our researchers, assisting them in achieving their research objective while developing tools and optimizing models in both offline and online environments.
Areas of responsibility include data-handling, deep dive into algo code, design, implementation, and deployment of technologies designed to enable innovative algo-trading projects and support existing and ongoing initiatives.
In this role you will :
Be involved in the execution of a significant new project, with high-end performance requirements and a deep understanding of the low-level implementation.
Participate end-to-end in research support, system architecture, implementation, simulation, testing and production.
Be responsible for designing and implementing research environments, offline and online data sources, coding machine learning algorithms, testing and deployment of solutions.
Collaborate with algorithmic and SW teams across the group to overcome our unique challenges.

Join the forefront of innovation as a fullstack Generative AI Engineer, where cutting-edge technology meets transformative solutions.
we're not just developing products; we're revolutionizing the accessibility domain with the power of generative AI.
Our mission is to make digital products universally accessible, leveraging the latest advancements in AI technology.
This is your chance to be part of a groundbreaking journey, creating end-to-end products that are not only technologically advanced but will also make the digital world accessible to everyone.
Your Impact & Responsibilities:
Design, develop and implement products that incorporate generative models, knowledge retrieval and task specific prompt engineering
Find creative solutions to bypass existing LLM blindspots and weakness
Research and stay updated with the latest trends and advancements in Generative AI
Deliver solutions to production in collaboration with backend and frontend teams

We are looking for experienced, creative and impact-oriented Algorithm Developers to join our team!

As an Algorithm Developer you will be responsible for building the algorithms powering our platform and our consumer applications (Wordtune Suite). You will be part of a multi-disciplinary team that also includes engineers and product professionals, all working together to bring our products to life.

You will take part in the full life cycle of our development process, deeply understand the problem we are solving, come up with algorithmic approaches for solving these problems, devise strategies for collecting necessary training data, train and evaluate large language models and other machine learning models and also be in charge of deploying these solutions in production.

ROLE AND RESPONSIBILITIES
Build the algorithms that power our various products
Develop production-grade solutions to challenging product-driven NLP tasks by combining deep language models, classical ML/NLP and algorithms
Collaborate with product, sales and customer success teams to define success criteria and translate them into quantitative measures and objectives
Devise innovative strategies for collecting training and evaluation data
Train and evaluate models in realistic production scenarios
End-to-end ownership of the algorithmic components of our products, from design, through implementation and monitoring in production