35 Gpu Jobs - Page 2

About the Role We are seeking an experienced Software Architect with a strong background in designing and implementing scalable, high-performance systems. As a Software Architect you will play a key role in shaping the technical direction of our products, defining architectural best practices, and collaborating closely with cross-functional teams to deliver state-of-the-art AI-driven solutions. This is what you are responsible for Lead the architectural design and implementation of scalable, reliable, and high-performance software systems for AI, AI Compiler and edge computing applications. Collaborate with product managers, software engineers, and hardware engineers to ensure alignment of technical decisions with business objectives. Define and maintain architectural best practices, guidelines, and documentation for the software engineering team. Evaluate and recommend technologies, frameworks, and tools to optimize the performance and scalability of our solutions. Mentor and provide technical leadership to the engineering team, fostering a culture of collaboration and innovation. Participate in code reviews, design discussions, and technical roadmap planning to ensure high-quality delivery. Drive continuous improvement in system architecture and development processes to support the companys growth and evolving requirements. Necessary qualifications 8+ years of experience in software architecture, system design, and development of scalable, distributed systems. Proven experience in designing edge-based solutions, compilers, runtime, firmware. Strong programming skills in modern languages such as Python, C++ or similar language. Expertise in designing high-performance, low-latency systems for AI/ML workloads. Strong understanding of software development methodologies, DevOps practices, and CI/CD pipelines. Familiarity with hardware-software co-design, embedded systems, and edge computing solutions is a plus. Excellent problem-solving and communication skills, with the ability to explain complex technical concepts to both technical and non-technical stakeholders. Preferred qualifications Experience with AI frameworks (e.g., TensorFlow, PyTorch) and understanding of AI/ML pipelines. Knowledge of hardware accelerators (e.g., GPUs, NPUs) and optimization for low-power AI inferencing. Experience working in a fast-paced, startup environment is a plus.

Please find below JD: Hands-on experience with testing and validating Server hardware platforms (Dell, HPE, Supermicro etc.); however, experience with Dell PowerEdge servers is highly preferred. Installation and configuration of various ancillaries such as NIC, HBAs, RAID Controllers & related firmware • Good exposure to in-band and out-of-the-band system management, GPUs Ability to handle and manage large-scale test labs with the above-mentioned hardware and components Good exposure to server validation. Preferably with functional and component integration testing. Well-versed with test planning, test execution monitoring, preparing informative dashboards to showcase technical progress, forward-looking plans and anticipating, and highlighting risks with testing. Excellent in communicating with all stakeholders and mentoring and guiding the project team on the technical front. Experience in Storage, COMMS (Networking), GPU, iDRAC Experienced to configure test beds or servers in lab and execute test cases. Experience running automation test cases. JIRA, Confluence, Qtest. 5 days working from customer lab, no WFH.

Scientist - Machine LearningAt ABB, we are dedicated to addressing global challenges. Our core values: care, courage, curiosity, and collaboration - combined with a focus on diversity, inclusion, and equal opportunities - are key drivers in our aim to empower everyone to create sustainable solutions.Write the next chapter of your ABB story. This position reports to Research Department Manager Your role and responsibilities In this role, you will have the opportunity to explore emerging technologies, creates intellectual property, and strengthens existing and future ABB offerings. We also provide R&D consultancy services to ABB Divisions and reap the benefits of open innovation by collaborating with Universities and startup companies. You will work in dynamic and creative teams, with a wide range of experience and expertise, carrying out applied research projects developing software engineering techniques to build intelligent systems for process industries.The work model for the role is Hybrid. #LI-HybridThis role contributes to the India Corporate Research Center (INCRC), located in Bangalore.You will be mainly accountable for: Use cases and requirements gathering in cooperation with ABBs business divisions and end customers for data-driven solutions. Evaluating and developing of mathematical algorithms and machine learning libraries for applications related to Industrial Process Automation business. Identifying and evaluating multiple design approaches and corresponding architectural solutions with a design rationale for machine learning systems. Developing proof of concepts, prototypes, and supporting pilot evaluation and productization of solutions. Adapting and optimizing machine learning algorithms to better utilize GPU and distributed clusters. Communicating project results to experts and non-expert audiences. Creating Intellectual Property - Invention disclosures and publishing in scientific conferences and journals. Living ABBs core values of safety and integrity, which means taking responsibility for your own actions while caring for your colleagues and the business. Qualifications for the role Ph.D. in a topic related to AI/ML in engineering from a reputed University with a good publication record and with a minimum of two years of relevant industrial research or post-doctoral experience. Proficiency in one or more programming languages and corresponding ML frameworks and libraries for interacting with industrial data. Good knowledge of supervised, unsupervised, semi-supervised, reinforcement learning techniques, time-series analysis, signal processing and related areas. Exposure to design, implementation and deployment of industrial machine learning systems with MLOps and efficient use of GPUs is preferred. Should have ability to collaborate and communicate effectively in English with internal and external partners including academic community.

We are looking for a highly skilled Python Backend Developer with a minimum of 4+ years of experience. The candidate will develop and scale platforms to run real-time computer vision models, productionize machine learning models with API designs, and deploy models using Django or any UI. This role requires expertise in Python, Kubernetes, Docker, cloud platforms (Azure, GCP, or AWS), CI/CD, and RESTful APIs. The ideal candidate should have experience building and maintaining ML systems, working with GPU/CPU usage, and performing load, unit, and regression testing. Proficiency in FastAPI, strong communication skills, and the ability to adapt to fast-changing environments are essential.

Key Responsibilities: Design & Develop AI Models : Create and implement machine learning models and algorithms to solve business challenges. Data Processing & Analysis : Analyze large datasets, preprocess data, and apply statistical techniques to improve model accuracy. Deep Learning & NLP : Work with advanced AI techniques such as neural networks, reinforcement learning, and natural language processing to build intelligent systems. Model Optimization : Optimize models for performance, scalability, and efficiency using techniques such as hyperparameter tuning and model deployment. Collaboration : Collaborate with software engineers, data scientists, and business teams to integrate AI solutions into applications and platforms. Testing & Validation : Test and validate AI models, ensuring their effectiveness, and continuously improve them based on feedback and new data. Documentation : Write clear documentation for models, algorithms, and code to ensure maintainability and scalability. Research : Stay updated with the latest advancements in AI technologies and research to apply cutting-edge techniques. Required Skills and Experience: Model Hosting and Deployment: Strong experience with deploying and managing machine learning models in production environments. Server Infrastructure: Proficient in building and managing servers to host and serve models for scalable access. APIs: Expertise in developing and deploying RESTful APIs for model inference. Redis & Celery: Solid experience with Redis for caching and Celery for task management and background job processing. PostgreSQL: Strong knowledge of PostgreSQL for data management and querying in the context of ML applications. Model Repositories: Experience with version control and repositories for machine learning models, including integration with Git or similar platforms. Cloud Platforms: Experience with cloud services (e.g., AWS, GCP, Azure) for deploying and managing models at scale. Preferred Skills: Familiar with CI/CD pipelines for AI models to ensure automated testing, deployment, and updates. Experience with containerization technologies such as Docker and Kubernetes for deployment and orchestration. Familiarity with frameworks like TensorFlow Serving, TorchServe, or similar for serving models in production. Knowledge of model monitoring tools and logging frameworks. Ability to work in a fast-paced, collaborative environment with cross-functional teams. Knowledge in consumer and server grade GPU to handle CUDA compatability issues.

Responsibilities: Design new kubernetes clusters with High Availability and multi replica sets Implement GPU support within Kubernetes to optimize AI/ML workloads. Develop kubernetes deployment yaml files for Micro services including kubernetes based databases deployments Knowledge on RK2 and CAPI based Kubernetes cluster deployments Knowledge on APISIX routing deployment and debugging issues with routing tables Knowledge on Kubernetes cluster and pod health monitoring and debug issues on production environments Hands on Knowledge of setting new kubernetes cluster and micro service bring up on Virtual Machine and stand alone node environment Build Kubernetes observability onto prometheus and Grafana Visualization. Required Skills and Qualifications: Minimum 3 years industry experience, with 2+ dedicated kubernetes experience Proficiency in scripting languages (e.g., Python, Bash, Go-lang) for automation and orchestration. Extensive experience with Kubernetes cluster creation, management, and optimization and apisix routing Hands-on experience with GPU support in Kubernetes on Openstack VM technology Hands on Database deployment using kubernetes Developing monitoring agents for kubernetes and visualization on Grafana Strong knowledge of OpenStack and its integration with Kubernetes

Hiring: SoC (System-on-Chip) Architect / MCU (Microcontrollers) Architect Location: Noida & Hyderabad Experience: 10-25 years Work Mode: Hybrid (3 days in office) We are seeking an experienced SoC or MCU architect to join our team. This role presents an exciting opportunity to drive innovation in high-performance SoCs and MCUs while collaborating with cross-functional teams to define and implement cutting-edge semiconductor solutions. Key Responsibilities: Define and develop SoC/MCU architecture, translating product requirements into detailed technical specifications. Lead chip implementation, ensuring product compliance through verification, validation, characterization, and testing. Drive automotive SoC/MCU development with expertise in high-performance SoCs, vehicle computers, software-defined vehicles (SDVs), and MCUs. Optimize execution strategies by improving team structures, methodologies, and tools for enhanced efficiency and quality. Evaluate and make strategic decisions on IP selection, including make-versus-buy analysis. Collaborate with system architects, SoC design teams, software engineers, and business leaders to establish common methodologies and best practices. Engage with external stakeholders, manage supplier relationships, participate in technical conferences, and contribute to industry standards. Develop and implement training programs, ensuring the dissemination of best practices and lessons learned. Apply Now! Click on the Apply button or share your resume with Heena at heena.k@randstad.in Tag your connections who might be interested! Join us and shape the future of semiconductor technology!

• Proficient in CPU architecture (ARM knowledge is desirable), Verilog, SystemVerilog and possess strong debugging skills. • Experience on CPU unit/microarchitecture verification • Should have worked on complex coverage driven verification projects Required Candidate profile • Experience - 8-15 Years • Experience of collaborating with cross-functional teams

• Experience in IP verification. • Main EDA Verification tools platforms for both simulation & Formal verification; • Competence in Python and TCL/TK scripting languages, Object Orienting Programming languages Required Candidate profile • Knowledge Bus protocols like AMBA AXI/AHB, & Common communication protocols. • Knowledge of Formal verification methodologies & SVA will be plus • Skills: AMBA AXI/AHB, Verification, System Verilog

• Experience in IP verification. • Main EDA Verification tools platforms for both simulation & Formal verification; • Competence in Python and TCL/TK scripting languages, Object Orienting Programming languages Required Candidate profile • Knowledge Bus protocols like AMBA AXI/AHB, & Common communication protocols. • Knowledge of Formal verification methodologies & SVA will be plus • Skills: AMBA AXI/AHB, Verification, System Verilog