דרושים » תוכנה » Computational Linguist (NLU)

We are looking for data scientists that are passionate about applied and theoretical research in the realm of computational linguistics. As a data scientist, you will join us on our quest to develop novel approaches for generalized AI that can understand and generate natural language. As such, you will study linguistics and mathematical phenomena in order to create new state-of-the-art NLP models that can be applied on, and generalize across multiple domains and use cases.

We are seeking a highly skilled and experienced Senior NLP Researcher to join our AI research team and drive the development of Dream's next-generation large language models (LLMs). The ideal candidate will have a strong background in NLP, deep learning, and applied research, with a passion for innovating and pushing the boundaries of generative AI technologies.

Responsibilities
Conduct cutting-edge research in natural language processing and large language models.
Design, train, and optimize large-scale neural network models for advanced applications.
Transition research projects from ideation through deployment and scaling.
Collaborate closely with cross-functional teams, including domain experts, product managers, and engineers, to deliver impactful AI solutions.
Define and contribute to the AI and NLP product roadmap.

As an NLP Data Scientist, a leader in AI-driven healthcare technology, you will play a critical role in developing intelligent language-based systems that directly support our core mission. Youll lead efforts in designing, evaluating, and deploying state-of-the-art Natural Language Processing (NLP) and Large Language Model (LLM) capabilities in production. From prompt engineering and NLU model development to model optimization and monitoring, your work will impact real-world outcomes and shape the future of digital health solutions. This role bridges applied machine learning, linguistics, and GenAI innovationideal for those who want to build solutions that matter.

What Youll Do:

Develop and maintain Natural Language Understanding (NLU) models integrated into key company products.

Design and iterate on prompt templates and strategies using techniques such as few-shot, zero-shot, and chain-of-thought prompting.

Apply best practices from prompt engineering, including answer engineering (e.g., extractors, verbalizers, formatting).

Evaluate model outputs using modern benchmarking techniques (e.g., self-consistency, prompt ensembles).

Collaborate with cross-functional teams (engineering, product, clinical) to tailor LLM-based systems to practical use cases.

Monitor and improve model performance post-deployment with a focus on stability, safety, and domain alignment.

Contribute to the internal prompt engineering knowledge base and stay up to date with the latest research and community best practices.

we are searching for world-class researchers in deep learning and natural language processing (NLP) to join our Conversational AI research team. Our team is pushing the boundaries of generative AI by building state-of-the-art large language models (LLM). We work on new neural architectures to enable LLM with very long context, on applying LLM to solve complicated math and coding problems, and on improvement LLM robustness. If you are passionate about the latest research and technologies revolutionizing generative AI and want to explore creative new paradigms for applied foundation models such as reasoning agents, this team will be a great fit for you. After building prototypes that demonstrate the promise of your research, you will collaborate with product teams to apply your ideas into industry-leading real-world applications.
What you will do:
Lead the research on new deep learning algorithms and techniques for efficient LLM inference
Develop new architectures for advanced large language models
Design and adapt foundation AI models to downstream tasks such as math and code reasoning.
Contribute these new models to Nemo framework
Construct and curate datasets for large-scale machine learning, for learning from human preferences, and for specific domains of applications.
Work closely with product and hardware architecture teams to integrate your research and developments into products.

We are looking for a Senior ML Engineer.
Responsibilities:
As a Senior Machine Learning engineer at Substrata, you will be working directly with our Head of R&D and will take a major role building our Pragmatic Intelligence Engine using and experimenting with S.O.T.A Deep Learning architectures, including: Multi-Layer Perceptron Neural Network, LSTM, mLSTM, CNN, RNN, VDCNN, etc.

Were searching for a passionate and experienced hands-on AI Architect to join our team.
With a wide array of responsibilities and corresponding impact, youll help spearhead our product offering and wear multiple hats at a fast-growing, dynamic, early-stage company.
Responsibilities:
Design, develop, and drive design processes and products that incorporate Generative AI (LLMs), models and knowledge Retrieval in order to help patients across the US.
Design and define data pipelines and evaluation pipelines.
Coach teams on best practices for datasets and building data sets.
Build applicative AI in production on a large scale.
Build solutions for different mediums including voice products with minimal latency and high accuracy.
Build an internal tool system to allow scientific evaluation.
Implement and lead new AI strategies by designing and implementing complex functionality and/or integrating with 3rd parties.
Continuously improve our existing NLP capabilities to help patients across the US answer any question, schedule appointments with their doctor, refill their prescriptions, and much more.
Use best practices and SOTA from the AI industry but also push the envelope to new heights.

Were seeking a passionate Senior Data Scientist to join our AI team. With a wide array of responsibilities and corresponding impact, youll help spearhead our new product offering and the world-class AI conversation product impacting millions of patients.
Responsibilities:
Design, develop, and drive design processes and products that incorporate Generative AI (LLMs), models and knowledge Retrieval in order to help patients across the US.
Design and define data pipelines and evaluation pipelines.
Build applicative AI in production on a large scale.
Build solutions for different mediums, including voice products with minimal latency and high accuracy.
Provide a scientific evaluation of the quality of our models..
Continuously improve our existing NLP capabilities to help patients across the US answer any question, schedule appointments with their doctor, refill their prescriptions, and much more.
Use best practices and SOTA from the AI industry, but also push the envelope to new heights.

We are looking for an experienced Software Engineer with GenAI/ML knowledge to join our AI/ML Applications team. In this role, you'll be responsible for designing, building, deploying, and maintaining production-grade AI systems and GenAI pipelines. You'll translate cutting-edge data science research into practical, scalable solutions, handling model/agent deployment both in cloud environments and on-premise. Youll optimize and implement workflows, and AI agents to ensure high performance and reliability in production environments.

Responsibilities
Design, implement, and deploy AI-driven applications, AI workflows, and LLM-based agents into production.
Build, manage, and maintain robust GenAI systems.
Optimize system performance, including robustness, scalability, communication protocols and resource utilization both on cloud and on-premises.
Develop and maintain services, APIs and integrate ML models into microservices-based applications.
Collaborate with cross-functional teams including data science, backend, DevOps, and platform teams.
Stay up to date with the latest developments in AI and related fields, focusing on LLMs, exploring how emerging technologies can be applied to improve products and services.

we are looking for an outstanding Software Engineer to join our SW SIMX Verification Team. You will be part of a team developing tests and platforms for a next-generation Switch simulation, work closely with SW R&D teams, performance team, and gain a deep understanding of building advanced networking simulation solutions. You will lead feature verification from design through implementation to framework integration, develop robust infrastructure, and work collaboratively with cross-functional teams.
What youll be doing: 
In this role, you will work closely with developers to test new components including crafting and executing unit, functional, and performance tests
Develop a verification environment using C/C++/Python to qualify the product from functional and performance perspectives
Analyse coverage measures to identify verification holes and to show progress toward product development and releases
Identify and write all types of coverage measures for stimulus and corner cases
Be responsible for verification of system design and software using advanced verification methodologies. 

Are you passionate about harnessing cutting-edge data science techniques to protect the world from cyber threats? Do you thrive in the dynamic world of cybersecurity? If so, we invite you to join our innovative and forward-thinking team at our company, where you'll have the opportunity to shape the future of cybersecurity and impact millions of customers.
As a Principal Data Scientist, you will apply your expertise in data analysis, machine learning, and cybersecurity to build new defense techniques against cyber-villains. You will be a driving force in designing and developing groundbreaking, ML-based security solutions that block attacks even before they begin.
Your Impact
Contribute to a diverse and highly skilled research group that pioneers state-of-the-art technologies to protect our customers
Utilize analytical rigor, statistical methods, programming, and data modeling to analyze vast amounts of data, applying your cybersecurity knowledge to guide our focus and approach
Decompose complex problems scientifically and provide actionable insights and recommendations to both technical and non-technical stakeholders
Lead and collaborate on end-to-end projects within the team and across engineering and product teams, from initial ideation to final deployment.