דרושים » AI » ASIC AI/ML Engineer, Annapurna Labs, MLA SOC, Methodology & Infrastructure

We are at the forefront of AI-driven innovation in VLSI design automation. Join us to shape the future of semiconductor design with cutting-edge AI tools and make a significant impact in a collaborative, high-performance environment. Are you ready to push the boundaries of whats possible in VLSI CAD? Come be part of our pioneering team!

What you'll be doing:
You will be responsible for developing and integrating advanced CAD solutions and automation flows using AI and machine learning for VLSI design, verification, and implementation.
Work closely with design, verification, and CAD teams to identify areas for improving VLSI workflows using advanced tools and methods.
Research, prototype, and deploy AI-based algorithms.
Develop and maintain scripts and automation infrastructure to enable seamless adoption of AI tools in the VLSI design process.
Continuously review emerging AI technologies and methodologies to keep our CAD environment up-to-date.
Provide technical support and training to engineering teams on AI-enabled CAD flows and best practices.

Required Machine Learning Engineer II - GenAI Applications
26947
About the team:
This opening is for the GenAI Applications Team within the Data & AI Marketplace department.
The GenAI Applications team is responsible for designing and delivering agentic, ML-powered solutions for some of our most impactful products, including booking search experiences, trip planning, and trip helpfulness. The team builds AI-driven applications and conversational agents, such as chatbots and intelligent assistants, that significantly enhance the end-to-end customer experience.
Role Description:
As a Machine Learning Engineer, you will work closely with experienced engineers and ML scientists to build scalable, production-grade GenAI applications. Your work will focus on designing, training, and deploying ML systems leveraging LLMs,, recommendation systems, and agent-based architectures, using state-of-the-art technologies. These solutions will directly power customer-facing experiences and play a key role in shaping the future of AI-driven travel products.
Key Job Responsibilities and Duties:
Deploying machine learning models: Design, develop and deploy in collaboration with scientists, scalable machine learning models and algorithms that provide content related insights and generative AI applications, ensuring scalability, efficiency, and accuracy.
Evaluating possible architecture solutions by taking into account cost, business requirements, emerging technologies, and technology requirements, like latency, throughput, and scale.
Generative AI Development: Contribute to the development of generative models such as GPT (Generative Pre-trained Transformer) variants or similar architectures for creative content generation, Q&A, chatbots, translation or other innovative applications.
Deployment and integration: Work closely with software engineers to integrate machine learning models into production systems. Ensure seamless deployment and efficient model inference in real-time environments. Collaborate with DevOps to implement effective monitoring and maintenance strategies.
Owning a service end to end by actively monitoring application health and performance, setting and monitoring relevant metrics and acting accordingly when violated.
Maintain clean, scalable code, ensuring reproducibility and easy integration of models into production environments, including CI/CD.
Collaborate with multidisciplinary teams: Collaborate with product managers, data scientists, and analysts to understand business requirements and translate them into machine learning solutions.

We are on an expedition to find you, someone who is passionate about creating intuitive, out-of-this-world production-grade AI systems and ML pipelines to join our AI group. You'll be responsible for designing, building, deploying, and maintaining production-grade AI systems and ML pipelines. Youll work closely with data scientists to translate research into scalable solutions and manage model deployment in both cloud and on-prem GPU environments.
:Responsibilities
Design, build, and deploy production-grade ML models, AI agents, and end-to-end pipelines across cloud and on-prem GPU environments.
Maintain and optimize ML systems for performance, scalability and reliability, including model validation, inference speed, and resource efficiency.
Develop monitoring and observability tools such as alerts and performance metrics to ensure system stability in production.
Create and integrate APIs for ML services within microservice-based architectures.
Drive adoption of best practices for CI/CD, observability, and reproducibility in ML systems.

In this role, you'll be responsible for designing and implementing evaluation, validation and optimization of GenAI systems. You will define, design and develop LLMs as judges to evaluate task and system outputs across multiple applications, create datasets for benchmarking and evaluation and help design robust and scalable evaluation pipelines for both onine and offline GenAI systems.
:Responsibilities
Design, develop and apply state-of-the-art techniques for evaluating and validating AI agents and/or workflows.
Develop and implement LLM-as-a-Judge (or similar) for different tasks and roles for GenAI systems and tools.
Design and implement evaluation pipelines and benchmark datasets for evaluating model quality, relevance and system consistency for various applications.
Optimize and maintain judge LLMs to evaluate outputs for different use cases such as chatbots, RAG systems, cybersecurity experts and investigators.
Define evaluation KPIs and metrics for both models, systems and tools.
Validate and optimize datasets for various use cases.
Ensure the reliability, efficiency, and scalability of evaluation tools and pipelines for both online and offline use cases.
Work closely with AI/ML engineers to make evaluations a part of the production pipelines of GenAI applications.
Collaborate with cross-functional teams including product, research and data science.
Stay up to date with the latest developments in AI, machine learning, focusing on LLMs, exploring how emerging technologies can be applied to improve our evaluation and validation pipelines.

We are seeking an experienced Generative AI Engineer to join our AI squad at our company. This is a unique opportunity to wear multiple hats - serving as both a developer of cutting-edge GenAI solutions and an advisory expert helping organizations transform their AI capabilities. You'll build end-to-end GenAI projects from conception to production while staying at the forefront of this rapidly evolving field.
Key Responsibilities
GenAI Development & Implementation
End-to-End Development: Build GenAI solutions from POC through production deployment, handling all backend development responsibilities
Client Engagement: Participate in technical discussions with clients, gather requirements, and help translate business visions into feasible technical solutions through presentations and consultations
Backend Development: Design and implement production-grade microservices architectures for GenAI applications using Python
Cloud Implementation: Deploy and manage GenAI solutions across GCP, Azure, and AWS platforms, leveraging cloud-native AI services
Cross-functional Collaboration: Work closely with project managers, full-stack developers, and Power Automate teams to deliver complete solutions
System Evaluation: Assess and optimize production-grade GenAI systems for performance, scalability, and reliability
Continuous Learning & Innovation
Technology Scouting: Continuously explore and evaluate new GenAI models, frameworks, and techniques as they emerge
Best Practices Development: Establish and refine methodologies for GenAI solution development and deployment.

we are looking for a AI/ML/Software Engineer.
Here, you will tackle ever-evolving challenges and leverage the dynamic AI landscape to craft solutions that transform the cybersecurity industry. You'll have the chance to build cutting-edge models and AI systems for cybersecurity. You'll gain deep expertise in the fields of both AI and security, engaging with all facets of Generative AI techniques and their deployment in production environments. You will collaborate with a talented team of researchers, engineers and security experts, and play a pivotal role in developing groundbreaking AI solutions. Shape the future of AI for Security with us and make an enduring impact on AI adoption across the world!
Develop and train cutting-edge AI models for the security domain.
Develop a platform for AI data processing, training, fine tuning, evaluation and other AI related needs.
Develop agentic systems that automate and uplift security operations.
Author blog posts, white papers and research papers related to developments in AI for the security landscape.
Collaborate with cross-functional teams of researchers and engineers to translate research ideas into products.
Contribute to our groups culture as an early member of the team.

Required Senior Machine Learning Engineer I - GenAI Applications
20031
Leadership/Team Quote:
This opening is for the GenAI Infra team in the Marketplace AI department.
The GenAI Infra team builds the Agents platform which is used for all agnetic and non-agentic flows. This team is responsible for both the GenAI agents and the orchestration around them, helping support applications such as the AI Trip Planner, Free text search, etc.
Role Description:
As Senior Machine Learning Engineer, youll work with top notch engineers and data scientists from the team on bringing it to the next level and enabling optimal user experience. The work will focus on building, deploying and serving GenAI capabilities (Agents, Tools and the orchestration between them) using the most advanced technologies and models.
Key Job Responsibilities and Duties:
Deploying machine learning models: Design, develop and deploy in collaboration with scientists, scalable machine learning models and algorithms that provide content related insights and generative AI applications, ensuring scalability, efficiency, and accuracy.
Evaluating possible architecture solutions by taking into account cost, business requirements, emerging technologies, and technology requirements, like latency, throughput, and scale.
Generative AI Development: Contribute to the development of generative models such as GPT (Generative Pre-trained Transformer) variants or similar architectures for creative content generation, Q&A, translation or other innovative applications.
Deployment and integration: Work closely with software engineers to integrate machine learning models into production systems. Ensure seamless deployment and efficient model inference in real-time environments. Collaborate with DevOps to implement effective monitoring and maintenance strategies.
Owning a service end to end by actively monitoring application health and performance, setting and monitoring relevant metrics and acting accordingly when violated.
Maintain clean, scalable code, ensuring reproducibility and easy integration of models into production environments, including CI/CD.
Collaborate with multidisciplinary teams: Collaborate with product managers, data scientists, and analysts to understand business requirements and translate them into machine learning solutions.

Were hiring a ML Engineer to accelerate AI-driven innovation across Stamplis B2B SaaS platform.
Youll be at the forefront of building intelligent systems that power core product experiences and automate internal operations, driving efficiency, speed, and scale across the organization. This is a high-impact, hands-on role in a fast-growing, AI-first company where machine learning is a foundational pillar, not a bolt-on feature. You'll partner with product, engineering, and operations teams to design and implement powerful ML and LLM-based solutions that make a measurable difference.
What You Will Do:
Build Intelligent Systems: Design and develop ML/LLM-powered solutions that solve real-world challenges across Stamplis product and internal workflows.
Own Full Lifecycles: Take projects from concept all the way to production, including model training, evaluation, integration, and monitoring.
Leverage State-of-the-Art Tools: Work with leading frameworks like LangChain, Hugging Face, TensorFlow, and PyTorch to deliver cutting-edge functionality.
Collaborate Cross-Functionally: Partner with product managers, engineers, and stakeholders to embed AI capabilities into user-facing features and backend services.
Ship at Scale: Build and maintain scalable APIs and services, integrating best practices in CI/CD, observability, and cloud infrastructure.
Report with Impact: Share progress, challenges, and results clearly with technical and executive stakeholders.

we are a fast-growing AI powered mobile games publishing company by Unity. We work with game studios worldwide to help them build, scale, and operate successful mobile games using cutting-edge technology.Were looking for a Staff AI Engineer to join our growing AI and engineering group. This is a highly impactful role for someone who wants to shape how AI is embedded across products, platforms, and business operations-from early experimentation to production-scale systems.
As a Staff AI Engineer, youll operate end-to-end: identifying opportunities, designing solutions, and delivering real business value using modern AI and LLM-based systems.
What you'll be doing:
Design, build, and deploy AI-powered solutions across Supersonics products and internal platforms
Partner closely with product, data, engineering, and business stakeholders to identify and execute high-impact AI use cases
Architect and implement agentic workflows using frameworks such as LangChain, LangGraph, or equivalent
Integrate and operate LLMs via SDKs, including prompt design, structured outputs, tool/function calling, and guardrails
Lead technical decisions around AI evaluation, monitoring, observability, and quality measurement
Own AI initiatives from concept through production, including iteration, scaling, and long-term maintenance
Stay up to date with emerging AI technologies, models, and best practices, and help bring them into production thoughtfully

We are looking for a highly skilled AI Engineer with a strong engineering mindset to bridge the gap between research and production.
In this role, you will be responsible for validating AI models developed by our Data Science team against real-world production systems, and then leading their optimization, deployment, and ongoing maintenance.
You will be part of the R&D team, working closely with engineers, data scientists, and product managers to ensure our AI solutions are scalable, reliable, and deliver long-term value.
If you enjoy working at the intersection of AI and engineering - bringing models to life in production, optimizing for performance, and building reliable systems - this role is for you!
Responsibilities
Lead the transition of AI models from proof-of-concept to full-scale production, ensuring they meet architectural, scalability, and performance standards.
Build observability and troubleshooting tools for AI services in production, including logging, performance tracking, and failure analysis pipelines.
Optimize inference performance, including latency, resource usage, and throughput, while maintaining model quality.
Manage model versioning and deployment readiness, including handoff processes, rollback plans, and configuration management.
Partner with the Data Science team to assess model readiness for production, validate input and output compatibility, and ensure assumptions align with real-world system behavior.
Collaborate cross-functionally with DevOps, backend engineers and data scientists to ensure scalable, secure, and cost-effective deployment of ML models.