דרושים » חשמל ואלקטרוניקה » Senior Software Engineer, CPU Performance Modeling Engineer

Design, develop, test, deploy, maintain, and improve Central Processing Unit (CPU) software modeling and other software tools.
Manage project priorities, deadlines, and deliverables.
Collaborate with hardware and software CPU architecture teams, SOC performance modeling team, and other Google Software teams.

We're proud to be our engineers' engineers and love voiding warranties by taking things apart so we can rebuild them. We keep our networks up and running, ensuring our users have the best and fastest experience possible.
Responsibilities
Define the System on a Chip (SoC)/block level design document such as interface protocol, block diagram, transaction flow, pipeline, etc.
Perform Register-Transfer Level (RTL) development (e.g., coding and debug in Verilog, SystemVerilog), function/performance simulation debug and Lint/CDC/FV/UPF checks.
Participate in synthesis, timing/power closure and Application-specific integrated circuit (ASIC) silicon bring-up.
Participate in test plan and coverage analysis of the block and SoC level verification.
Communicate and work with multi-disciplined and multi-site teams.

As a Technical Program Manager for Silicon Development, you will use your technical and management experience to lead the development and execution of complex, multidisciplinary SoC projects. You will plan programs and manage their execution from early concepts through development to tape-out and production. You will collaborate closely with architecture, design, verification, physical implementation and manufacturing teams throughout the SoC execution life cycle. This includes making technical decisions for the chip designs and methodology, driving project schedules, identifying risks and communicating them to all stakeholders, and managing partner teams.

Behind everything our users see online is the architecture built by the Technical Infrastructure team to keep it running. From developing and maintaining our data centers to building the next generation of platforms, we make product portfolio possible. We're proud to be our engineers' engineers and love voiding warranties by taking things apart so we can rebuild them. We keep our networks up and running, ensuring our users have the best and fastest experience possible.

Responsibilities
Plan, coordinate, and deliver custom silicon products.
Assess complexity and scope out the project, generate task lists, build a project timeline and work with the teams to make it into reality.
Lead the data-driven schedules and milestones, track the progress, proactively identify potential future issues, and identify mitigations with the team leaders.
Drive technical, budgetary, and schedule trade-off discussions with cross-functional teams.
Manage project execution and issues through design, development, test, manufacturing, deployment and sustaining activities for silicon and hardware products.

empowers organizations of all sizes to improve loyalty and business outcomes by creating the best experiences for their customers and employees. Through Cloud, the AI-powered Experience Orchestration platform, organizations can accelerate growth by delivering empathetic, personalized experiences at scale to drive customer loyalty, workforce engagement, efficiency and operational improvements.

We employ more than 6,000 people across the globe who embrace empathy and cultivate collaboration to succeed. And, while we offer great benefits and perks like larger tech companies, our employees have the independence to make a larger impact on the company and take ownership of their work. Join the team and create the future of customer experience together.

We are seeking an experienced and motivated Senior Software Engineer to lead the development of key software features within our data-intensive cloud platform. In this role, you will have the opportunity to solve complex technical challenges, influence system design, mentor junior developers, and take ownership of high-impact projects.

Key Responsibilities
Design and architect medium-to-large scale software modules using design patterns, and OOP principles.
Lead development efforts for core features, ensuring performance, scalability, and maintainability.
Collaborate with cross-functional teams to define requirements, contribute to high-level architecture, and ensure product alignment.
Conduct and lead code reviews, provide technical mentoring to junior engineers, and promote best practices.
Ensure test coverage through thorough unit, integration, and performance testing.
Troubleshoot production issues and lead the resolution of complex technical problems.
Optimize CI/CD pipelines and contribute to release planning and automation.

Contribute to CPU front-end designs, emphasizing micro-architecture and RTL design for next generation CPU.
Propose performance enhancing micro-architecture features with efficiency in mind. Work with architects and performance teams for trade-off studies.
Deliver designs that meet power, performance, and area (PPA) goals with production quality.
Interpret techniques into design constructs and languages in order to provide guidance to and participate in the performance modeling effort.

Were looking for a Senior Data Platform Engineer to join our Data Platform team. The ideal candidate will have extensive experience with data engineering, specifically with Kafka and Elasticsearch, to design and maintain our data platforms. You will work closely with cross-functional teams to ensure the scalability and reliability of our data solutions.

Job Summary:
As a Senior Data Platform Engineer, you'll be responsible for design, development, maintenance, troubleshooting, and implementation of our big data architecture. Your expertise in Elastic, Kafka, and Java will be critical in ensuring the scalability and performance of our data systems.

What youll do:

Implement data processing pipelines using Kafka for real-time data streaming.
Optimize and manage search capabilities using Elastic technologies.
Collaborate with product managers, data analysts, and other stakeholders to gather requirements and translate them into technical specifications.
Oversee code reviews, ensure best practices in coding and data handling, and maintain high-quality standards in software development.
Stay up-to-date with emerging trends and technologies in big data and recommend improvements to our architecture and processes.
Troubleshoot and resolve issues in a timely manner to minimize downtime and ensure system reliability.

Collaborate with Architecture, Design and Verification teams to develop new product bring-up, validation, characterization, qualification strategies and manufacturing test solutions for new High Performance Computing (HPC) products in advanced process technologies.
Verify test solutions on pre-silicon models (simulation or emulation) and develop ATE test modules, DC tests, binning, production and characterization flows.
Develop and validate test programs on Automated Test Equipment (ATE) platforms for new product integration (NPI) in preparation for high volume manufacturing (HVM), working with ATE vendors.
Support product, volume data analysis of screening and characterization data, test time and yield improvements, assess test escapees and Return Materials/Merchandise Authorizations (RMAs), localize failures, implement containment measures and partner with design, manufacturing, quality and reliability teams to root cause and implement corrective actions.
Develop tools, flows and methodologies to improve and automate the testing.

Required Software Engineer, Machine Learning
We are embarking on the most transformative change to its business and technology in company history, and our Machine Learning Engineers are at the forefront of this evolution. By leading crucial projects and initiatives that have never been done before, you have an opportunity to help us advance the way people connect around the world.
The ideal candidate will have industry experience working on a range of recommendation, classification, and optimization problems. You will bring the ability to own the whole ML life cycle, define projects and drive excellence across teams. You will work alongside the worlds leading engineers and researchers to solve some of the most exciting and massive social data and prediction problems that exist on the web.
Software Engineer, Machine Learning Responsibilities
Play a critical role in setting the direction and goals for a sizable team, in terms of project impact, ML system design, and ML excellence
Adapt standard machine learning methods to best exploit modern parallel environments (e.g. distributed clusters, multicore SMP, and GPU)
Re-evaluate the tradeoffs of already shipped features/ML systems, and you are able to drive large efforts across multiple teams to reduce technical debt, designing from first principles when appropriate
Leading a team from a technical perspective to develop ML best practices and influence engineering culture
Be a go-to person to escalate the most complex online/production performance and evaluation issues, that require an in depth knowledge of how the machine learning system interacts with systems around it
Develop highly scalable classifiers and tools leveraging machine learning, data regression, and rules based models
Suggest, collect and synthesize requirements and create effective feature roadmap
Code deliverables in tandem with the engineering team.

Develop and execute comprehensive validation plans for Google's custom silicon, covering functional, performance, power, and reliability aspects.
Design and build scalable validation test infrastructure, including hardware setups, software frameworks, and automation tools on Emulation and/or FPGA platforms.
Lead the debugging and resolution of complex silicon issues, collaborating with cross-functional teams such as design, architecture, software, and firmware.
Analyze validation data to identify trends, root causes, and opportunities for improvement in silicon quality and reliability.
Build and mentor a high-performing team of silicon validation engineers, fostering a culture of collaboration, innovation, and technical excellence.

We are looking for a Senior Data Scientist.
The Data Science department plays a pivotal role in our company, generating value by developing algorithms and analytical production-grade solutions. We leverage advanced techniques and algorithms to provide maximum value from data in all shapes and sizes (such as classification models, NLP, anomaly detection, graph theory, deep learning, and more). As a Data Scientist, you will assume the classic data-science role of an end-to-end project development and implementation practitioner. Being part of the team requires a mix of hard quantitative and analytical skills, solid background in statistical modeling and machine learning, a technical data-savvy nature, along with a passion for problem-solving and a desire to drive data-driven decision-making.
What You'll Be Doing:
Data Exploration and Preprocessing: Collect, clean, and transform large, complex data sets from various sources to ensure data quality and integrity for analysis
Statistical Analysis and Modeling: Apply statistical methods and mathematical models to identify patterns, trends, and relationships in data sets, and develop predictive models
Machine Learning: Develop and implement machine learning algorithms, such as classification, regression, clustering, and deep learning, to solve business problems and improve processes
Feature Engineering: Extract relevant features from structured and unstructured data sources, and design and engineer new features to enhance model performance
Model Development and Evaluation: Build, train, and optimize machine learning models using state-of-the-art techniques, and evaluate model performance using appropriate metrics
Data Visualization: Present complex analysis results in a clear and concise manner using data visualization techniques, and communicate insights to stakeholders effectively
Collaborative Problem-Solving: Collaborate with cross-functional teams, including product managers, data engineers, software developers, and business stakeholders to identify data-driven solutions and implement them in production environments
Research and Innovation: Stay up to date with the latest advancements in data science, machine learning, and related fields, and proactively explore new approaches to enhance the company's analytical capabilities