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We're looking for a Data Science Tech Lead to take technical and delivery ownership of this team, a hands-on senior IC role. You'll set research direction, own client-facing delivery end-to-end, and drive how the team builds and scales its use of GenAI tooling and agentic capabilities. You'll work closely with other data scientists & analysts and partner daily with Solutions, Implementation, and Engineering. This role comes with real latitude to shape research direction and influence our product offering and roadmap - not just execute against a backlog.

What you will do
1. Research Direction

Set the technical research agenda for our tabular prediction models.
Guide how we incorporate temporal signal - case history, lag features, schedule snapshots- without defaulting to time-series techniques that don't fit our data.
Own our strategy for extracting value from unstructured data sources via LLMs - feature extraction, embeddings, or fine-tuning - balancing accuracy, cost, and constraints like latency and privacy.
Set standards for experimentation, evaluation, and model guardrails.
2. Client Project Delivery

Own DS delivery end-to-end across concurrent client engagements - from discovery through modeling, validation, and go-live.
Partner with Solutions and Implementation on discovery and rollout; represent Data Science in client meetings, presenting results directly to stakeholders.
Ensure delivery lands inside the product, on timeline, coordinating with Engineering on productionization.
Track delivery risk across the client portfolio, flagging blockers and scope changes early.
3. GenAI Tooling & Team Capability

Build the team's onboarding and delivery playbook for new use-cases and encode it as reusable Claude skills/agents
Turn repeatable steps in the DS workflow into standardized, shared tooling.
Raise the team's GenAI fluency through mentoring on Claude Code and related tooling.

You will take ownership of the search infrastructure for Ask us - a financial intelligence platform powered by LLMs. Your main goal is to ensure our AI agents can find the exact financial data they need (articles, transcripts, news) in milliseconds. You will work on the Retrieval layer of our RAG architecture, combining traditional text search with modern vector search techniques.

Tech Stack: Elasticsearch (v8+), Python (FastAPI, Asyncio), OpenAI Embeddings, LangChain, LangSmith.

What You'll Do:
Search Engine Development: Design and implement Hybrid Search strategies. You will figure out how to best combine "keyword matching" (finding specific tickers like 'AAPL') with "semantic search" (finding concepts like 'revenue growth').
Relevance Tuning: You are responsible for the quality of search results. You will build systems to measure and improve how well the search engine answers user queries (using tools like LangSmith).
Vector Search & RAG: Manage the integration of OpenAI embeddings into Elasticsearch. You will solve challenges related to indexing long documents (e.g., earnings transcripts) so the AI retrieves only the most relevant parts.
Performance Optimization: Optimize Elasticsearch queries and index settings to ensure low latency, even for complex queries with many filters.
Python Backend: Develop and maintain the Python services that build queries and process results. We use FastAPI and Asyncio heavily.

We are looking for a Senior Backend Engineer specialized in Generative AI to design agent workflows, optimize interactions with models (OpenAI, AWS Bedrock), and ensure the reliability of non-deterministic systems in production.

Tech Stack: Python (Asyncio), FastAPI, LangChain, LangGraph, Pydantic, Elasticsearch, AWS Bedrock / OpenAI API, LangSmith.

What You'll Do:
Agent Architecture: Design and implement complex agent orchestration logic using LangGraph. You will define state management, conditional routing, and error handling within the agent graph.
Tool Engineering: Build and optimize the tool layer (function calling) that allows LLMs to interact with internal financial APIs and databases accurately.
Performance Optimization:
-Reduce end-to-end latency through asynchronous processing and streaming (SSE).
-Implement semantic caching strategies to minimize API costs and response time.
-Optimize token usage without sacrificing answer quality.
Observability & Evaluation: Implement automated evaluation pipelines using LangSmith. You will be responsible for setting up regression testing for prompts and agents to measure quality (correctness, faithfulness) before deployment.
Advanced RAG: Refine retrieval strategies. Work on hybrid search implementation (Keyword + Vector), re-ranking, and query expansion to feed the most relevant context to the model.

In this role, you will be a key contributor to the design and implementation of AI Graph Compiler software stack for Neural Processing Units (NPUs). You will take part in defining software architecture, implementing performance-critical components, and enabling efficient execution of advanced neural networks under tight power, memory, and latency constraints.

You will work closely with hardware and system architects, software and hardware engineers, influencing both software and hardware decisions. You will design and implement major parts of NPU embedded solutions, actively promoting AI capabilities to the customers.

What will you do:

Own and design key components of the AI Graph Compiler software stack for NPU-based systems.

Optimize inference performance (latency, throughput, memory footprint, power) for edge deployments.

Collaborate on HW-SW co-design, influencing NPU architecture.

Support IP evaluations and silicon bring-up, root-cause complex HW/SW issues, and influence development methodologies.

Mentor junior engineers and contribute to technical best practices.

In this role, as Senior Team Leader of the AI NPU Simulator, you will lead a Group developing a major part of AI simulation framework, in the core of our AI software offering. The AI NPU simulator enables the execution of state-of-the-art LLMs, Generative AI models, and neural networks with exceptional performance, impacting multiple hardware and software teams across the company.

You will drive the development of robust, scalable, and efficient simulation software, working closely with global Architecture, VLSI, and Software teams to shape next generation of AI solutions.

We are looking for an exceptional hands-on leader with strong technical expertise, proven experience leading software teams, and a track record of delivering complex, state-of-the-art products on time and with high quality. The ideal candidate is execution-driven, innovative, and passionate about building high-performing teams and cutting-edge AI technology.



Responsibilities

Manage and lead two teams (Development + Validation) .

Be accountable for the simulation lifecycle, including architecture, development, validation, and release.

Lead development of advanced simulation models for AI processors.

Own delivery of complex, multi-release roadmaps.

Ensure strong alignment between hardware design, compiler behavior, and simulation models.

Drive system-level correctness and performance accuracy.

Support system bring-up, debugging, and customer-facing activities when needed

In this role, you will learn and deeply understand the AI fundamentals and create tools that simulate AI neural network processor implementation.

In addition, you will perform in-depth analysis and optimization to the simulator, to ensure simulator performance and accuracy for various processors architectures.

The project is using C/C++ OOP as main development language as well as python for AI neural network.

Development platforms are Linux and Windows based.

Responsibilities:

Taking part of innovative, agile, top-notch Software organization, designing Neural Network Processor (NPU) simulator in close collaboration with the architecture, algorithms, system and hardware teams.

Design and develop simulation software solutions allowing customers to run most advanced AI networks efficiently on NPU software simulation.

We are seeking a high-impact motivated Software Architect to join our team and help shape the future of our advanced neural network AI Software Toolchain over AI computing processors.

Responsibilities

Lead Software Architecture specification and supervise design for the most advanced Software Toolchain handling state-of-the-art Neural Processing Unit operation.

Collaborate proactively with Product, Architecture, VLSI and Software teams to promote software leadership over various markets and compute SoCs.

Explore and translate state-of-the-art neural network and AI applications requirements into software architecture flows, encompassing hardware, software, tools and other components.

Evaluate architecture proposals, internal and external IP features and provide influential and inspirational leadership across hardware and software to align all parties to a common vision of architecture & technology development.

Represent with high technical credibility in customer meetings, appropriately incorporating feedback.

Boost velocity of development teams by providing technical guidance and by constantly looking ahead to anticipate and resolve future challenges.

Conduct experiments, invent and drive development of supporting tools such as simulators, models, profilers, and other methods as required.

Engage with engineering leadership and product planning stakeholders to develop technology roadmap.

We are looking for a software student that will take part in our software projects and practical research activities.

You will have the opportunity to learn and gain experience related to many aspects of software and hardware. In addition, we encourage you to have your final academic project done here.

responsibilities:

Maintaining, updating and debugging existing software tools, primarily in Python. This part is around 70% of the expected activity.

Taking part in architectural research and development. Including: developing test cases, executing and presenting results.

Modeling, running, and analyzing AI neural networks to evaluate their behavior and performance on Cevas DSP processors and AI accelerators.



We are looking for a CAD/Emulation Graduate Engineer to join our infrastructure team. This position is designed as an entry-level role for a recent graduate, providing hands-on experience with advanced VLSI CAD/Emulation and infrastructure



Key Responsibilities

Develop and maintain automation scripts for front-end Emulation and VLSI CAD flows and automation.

Support execution and releases of VLSI artifacts while marinating advanced CAD flows.

Assist in improving infrastructure efficiency and tool integration.

Work with version control systems and CI/CD pipelines for regression and build environments.

Own and rule top notch emulation methodologies and procedures.

Lead a team of compiler engineers responsible for open source based toolchain and graph compiler. You will be a hands-on team leader - driving architecture decisions, guiding engineers, and delivering compiler capabilities across all hardware targets. Our team embraces an AI-agentic development flow, leveraging AI coding agents to accelerate engineering productivity, and we are looking for a leader who champions this approach.

Responsibilities

Lead development of open source based toolchain targeting custom DSP and NPU architectures. Drive design and delivery of graph compilation flows: transformations, operator mapping, and code generation. Champion AI-agentic development practices within the team - integrating AI coding agents into day-to-day engineering workflows. Mentor engineers and conduct code reviews; build a high-quality engineering culture. Collaborate with hardware architecture, algorithms, and software teams globally. Own team planning, prioritization, and on-time delivery of toolchain features. Contribute hands-on to design, implementation, and performance tuning in C++ and Python.

Lead the development of Sensing SDK, a core software toolkit that integrates a broad set of computer vision, audio, and voice libraries, along with AI operators. The SDK is specifically designed and optimized for latest NPUs and DSPs - NeuPro-M, NeuPro-Nano and SensPro2 - positioning it as a cornerstone of sensing and AI platform.

Key Responsibilities:

Lead and mentor a team of software engineers developing Sensing AI SDK. Architect and implement high-performance sensing SW components for AI, vision, Audio and voice optimized for vectorize SIMD execution. Collaborate with compiler and DevOps teams to ensure efficient development and deployment. Drive technical excellence through code reviews, design discussions, and continuous improvement. Own the SDK roadmap, planning, and delivery cycles. Engage with customers to enable successful pre-sale processes, support integration and gather feedback.

In this role, as Embedded Software Team Leader, you will lead a team owning a key part of NPU AI software stack, a complex, multi-layered system spanning the Host (SDK, runtime, APIs, and UMD/KMD drivers) and the NPU IP (embedded firmware). This stack is at the heart of the AI software offering, with deep impact on multiple hardware and software teams ability to execute state of the art LLM, Generative AI and Neural Networks with extraordinary performance. Reporting to the AI Software SDK Senior Team Leader, you will lead a team of creative and result oriented enthusiasts that invent, design, and implement software that enables smooth connectivity between the NPU and Host CPU.



Responsibilities:

Lead and manage the Embedded Software engineering team, ensuring high performance and productivity.

Own the design, development, and implementation of your component within NPU AI software stack, aligned with the AI Software SDK group's technical strategy, architecture, and roadmap and its automated CI and release process.

Collaborate with cross-functional teams to integrate solutions. Provide technical guidance and mentorship to team members.

Ensure project timelines and deliverables are met.

Conduct performance reviews and support professional development of team members.

Collaborate globally with architects, HW teams, NPU teams, and other developer teams

As the R&D Technical Project Manager you will lead large-scale, multidisciplinary programs developing Neural Network Processor (NPU) and AI IP products.

You will lead cross-functional engineering teams (30+ engineers) across architecture, algorithms, VLSI, embedded software, SW tools, and systems, ensuring seamless execution from Product Requirements Document (PRD) to production-ready delivery for leading SoC makers and OEM customers.

You will also act as the primary interface between customers, product team , and internal R&D teams , balancing technical leadership, strategic execution, and organizational excellence in a global, multi-site environment.

Responsibilities

Be accountable for successful planning and delivery, in quality, on time under budget, of all R&D programs & products in the AI Division, covering architecture, algorithms, hardware IP, embedded software, SW tools, and integration tasks.

Accountable for the definition and deployment of the AI Division Program development processes.

Program Planning and Execution

Own end-to-end planning and delivery for complex AI processor IP programs that include hardware design, embedded SW, and SW development tools.

Build and manage integrated schedules across RTL, verification, firmware, drivers, toolchain, and documentation.

Drive execution across concepts, design, verification, bring-up, and customer release phases.

Manage program POR, program priorities, and change control process.

Track dependencies between IP architecture, firmware readiness, SDK/toolchain availability, and customer enablement deliverables.

Define and manage program KPIs: schedule, quality metrics, and customer satisfaction.

As a senior compiler engineer, you will own the design and development of open source based toolchain and graph compiler. You will drive technical solutions end-to-end, deliver compiler capabilities across all hardware targets, and help mentor engineers. Our team embraces an AI-agentic development flow, leveraging AI coding agents to accelerate engineering productivity, and we are looking for engineers who champion this approach.

Responsibilities:

Design and develop open source based toolchain targeting custom DSP and NPU architectures.

Drive design and delivery of graph compilation flows: transformations, operator mapping, and code generation.

Champion AI-agentic development practices - integrating AI coding agents into day-to-day engineering workflows.

Own complex components end-to-end, from architecture and design through implementation and delivery.

Provide technical guidance and mentorship to engineers; conduct code reviews.

Collaborate with hardware architecture, algorithms, and software teams globally.

Analyze and optimize toolchain output for performance and correctness across processor families.

Join an agile team working on the most advanced wireless communication solutions, focused on the latest communication standards. You will define the architecture for future products and optimize modem solutions for hardware implementation.

Responsibilities:

Research and define architecture for advanced communication standards.

Define PHY System specifications and architecture for future solutions.

Define low-power architecture.

Work closely with the functional teams (Algorithm, HW/SW, RF, Validation, etc.), from early algorithm study to system validation.

Participate in integration and testing of wireless system solutions, spanning embedded SW, HW and radio.

Support customers engagement and product deployment.