Advanced Package Technology Development Iot Mts Jobs

EnCharge AI is a leader in advanced AI hardware and software systems for edge-to-cloud computing. EnCharge’s robust and scalable next-generation in-memory computing technology provides orders-of-magnitude higher compute efficiency and density compared to today’s best-in-class solutions. The high-performance architecture is coupled with seamless software integration and will enable the immense potential of AI to be accessible in power, energy, and space constrained applications. EnCharge AI launched in 2022 and is led by veteran technologists with backgrounds in semiconductor design and AI systems. We are an ambitious AI hardware startup building next-generation accelerators with massive compute density. To achieve aggressive Power, Performance, and Area (PPA) targets on accelerated tapeout schedules, we require a robust, highly automated, and heavily optimized physical implementation and signoff flow. The Role As a Staff / Senior Staff CAD & Methodology Engineer, you will be the resident expert in Innovus and Tempus, responsible for developing, debugging, and continually accelerating our RTL-to-GDSII and timing signoff flows. You will work closely with Physical Design and STA leads to eliminate bottlenecks, automate manual tasks, and push the limits of EDA capabilities at advanced process nodes. Key Responsibilities Flow Architecture & Automation: Architect, develop, and maintain a highly automated, robust, and scalable physical design and signoff flow from synthesis through GDSII, optimized for AI accelerator architectures. Innovus Methodology: Drive advanced physical design methodologies in Cadence Innovus. Optimize recipes for floorplanning, placement, Clock Tree Synthesis (CTS), routing, and power grid implementation to squeeze out maximum PPA. Tempus Signoff Integration: Own the STA and timing signoff methodology using Cadence Tempus. Implement and optimize Distributed Multi-Scenario Analysis (DMSA), advanced OCV methodologies, and automat

EnCharge AI is a leader in advanced AI hardware and software systems for edge-to-cloud computing. EnCharge’s robust and scalable next-generation in-memory computing technology provides orders-of-magnitude higher compute efficiency and density compared to today’s best-in-class solutions. The high-performance architecture is coupled with seamless software integration and will enable the immense potential of AI to be accessible in power, energy, and space constrained applications. EnCharge AI launched in 2022 and is led by veteran technologists with backgrounds in semiconductor design and AI systems. About the Role EnCharge AI is seeking a highly skilled and experienced AI Compiler Engineer to spearhead the efforts in developing and optimizing graph compilers tailored to cutting-edge AI and ML workloads. You will collaborate with hardware architects, and AI researchers to enhance performance, optimize computation graphs, and enable efficient model deployment on EnCharge’s Inference Accelerators. Responsibilities Architect, design, and implement optimizations for AI model execution on graph compilers to improve performance, reduce latency, and maximize hardware utilization. Work closely with ML researchers, hardware engineers, and software developers to design and deploy AI models, understanding and addressing hardware-specific challenges. Work on performance optimizations for neural network models, such as layer fusion, operator fusion, and graph-level transformations. Develop compiler optimizations and passes that convert high-level AI models (e.g., from TensorFlow, PyTorch) into intermediate representations (IR). Implement parsing, semantic analysis, and IR generation for deep learning frameworks. Research and integrate the latest advancements in compiler design, ML model optimizations, and hardware acceleration into graph compilers. Provide leadership, mentorship, and technical guidance to a team of engineers focused on graph compiler optimizations. Qual

EnCharge AI is a leader in advanced AI hardware and software systems for edge-to-cloud computing. EnCharge’s robust and scalable next-generation in-memory computing technology provides orders-of-magnitude higher compute efficiency and density compared to today’s best-in-class solutions. The high-performance architecture is coupled with seamless software integration and will enable the immense potential of AI to be accessible in power, energy, and space constrained applications. EnCharge AI launched in 2022 and is led by veteran technologists with backgrounds in semiconductor design and AI systems. About the Role EnCharge AI is seeking a Senior NPU Architect to join our Architecture Team. In this role, you will collaborate with a team of NPU and system architects, hardware engineers, and software teams to define and optimize key features in our AI accelerator with the cutting-edge in-memory computing technology. You will contribute to designing a holistic AI HW/SW solution that has the best performance and efficiency on the market for the latest AI/ML workloads, such as LLMs, diffusion models, CNNs, and more. Responsibilities Define and develop the spec, architecture, and micro-architecture of key architecture modules (such as the in-memory compute unit, on-chip network, and memory orchestration units) based on the requirements of the workloads and software deployment flow Contribute to the modeling of aforementioned key architecture modules in our C++ simulation framework to ensure a functional implementation of the features Collaborate with the design verification team to deliver a strategy and infrastructure for the testing of the architecture features within said modules Work with the software team and other architects to analyze the performance and efficiency of the architecture modules for key workloads, identify performance bottlenecks, and guide architectural decisions Stay up to date with the latest trends and research in AI workloads, architectures, an

Zoox is building the world's most advanced self-driving hardware and software solution. The efficiency demands of such a system require an expert fine tuning of both the compute hardware architecture as well as the algorithms and middleware that runs on it to achieve maximum throughput at the most optimal power levels. The Software Performance team keeps the main onboard computer healthy and performant to ensure that our on-bot autonomy software meets its latency targets while also accommodating its safety goals. We are responsible for the efficient allocation of onboard compute resources (CPU/GPU/Memory/accelerators) ensuring contention is minimized and the autonomy stack executes harmoniously. As the Onboard Execution team leader within the Performance team, you will lead a highly specialized team of software performance engineers in aggressively optimizing on-bot software runtime. This is a high impact role that sits at the intersection of ML Platform, Core, and Autonomy Software - ensuring that efficient compute utilization is a central tenet emphasized across the organization. In this role, you will: Manage a team of 8-to-10 engineers focused on optimizing the software performance of the on-bot autonomy software stack. Partner with Autonomy, ML Platform, Middleware, Sensors, and Hardware Architecture teams to meet strict system response (latency) and compute utilization targets. Achieve alignment between cross-functional leaders across the Software organization on compute resource allocations and budgets. Hire, grow, and develop talent in the realm of performance optimization. Build self-service force-multiplier frameworks & workflows that empower developers to deliver efficient & performant software. Qualifications BS in computer science, computer engineering, or related field Proficiency with C++ & concurrent (parallel) execution systems Deep knowledge and unde

EnCharge AI is a leader in advanced AI hardware and software systems for edge-to-cloud computing. EnCharge’s robust and scalable next-generation in-memory computing technology provides orders-of-magnitude higher compute efficiency and density compared to today’s best-in-class solutions. The high-performance architecture is coupled with seamless software integration and will enable the immense potential of AI to be accessible in power, energy, and space constrained applications. EnCharge AI launched in 2022 and is led by veteran technologists with backgrounds in semiconductor design and AI systems. Senior Emulation Engineer Location: India - Remote Job Description: At EnCharge AI, we are building the next generation of AI compute silicon — purpose-built for high-performance, low-power, and scalable AI inference. As an Emulation Engineer, you will play a critical role in validating complex AI accelerator architectures on emulation platforms before tape-out. This position is ideal for someone passionate about bridging the gap between hardware and software in fast-paced, deep tech environments. Responsibilities: • Set up and maintain Siemens Veloce emulation and prototyping platforms • Adapt SoC designs for Emulation and Prototyping • Develop and debug emulation testbenches and system-level environments • Support pre-silicon validation, power/performance analysis, and early software bring-up. Participate in silicon bring-up and validation. • Collaborate with design and verification teams to isolate design issues and accelerate debug. • Optimize performance of the emulation workloads and reduce turnaround time. • Work with firmware/software teams to enable use of emulators for OS and driver testing. Required Background: • BS/MS/Ph.D. in EE, CS, or related field with 7+ years of SoC design experience. • Experience with emulation platforms (Veloce, Palladium, or ZeBu) and FPGA-based prototyping systems (proFPGA, HAPS, or Protium) • Experience with emula

EnCharge AI is a leader in advanced AI hardware and software systems for edge-to-cloud computing. EnCharge’s robust and scalable next-generation in-memory computing technology provides orders-of-magnitude higher compute efficiency and density compared to today’s best-in-class solutions. The high-performance architecture is coupled with seamless software integration and will enable the immense potential of AI to be accessible in power, energy, and space constrained applications. EnCharge AI launched in 2022 and is led by veteran technologists with backgrounds in semiconductor design and AI systems. Physical Design Engineer (2-4 Years Experience) We are looking for a high-caliber Physical Design Engineer to join our fast-paced startup team. This role is designed for "top 1%" talent—engineers from tier-1 universities (IIT/NIT/BITS or equivalent) who possess a relentless "go-getter" attitude and the critical thinking skills required to solve complex, next-generation silicon challenges. If you are eager to move beyond standard digital flows into the future of AI-driven automation , this is your playground. Key Responsibilities End-to-End Ownership: Drive RTL-to-GDSII implementation, including floorplanning, placement, CTS, routing, and physical verification (LVS/DRC/ERC). Performance Optimization: Execute high-performance design closure focusing on PPA (Power, Performance, Area) targets in advanced process nodes ( 3nm or below) Static Timing Analysis (STA): Perform comprehensive timing closure, including signal integrity, crosstalk analysis, and CPPR (Common Path Pessimism Removal) optimization. Power Integrity: Conduct IR-drop analysis (Static/Dynamic) and EM (Electromigration) checks to ensure robust power delivery. Innovation: Develop and integrate AI/ML-based automation scripts to optimize the physical design flow and reduce turnaround time. Qualifications &am

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. About the Team The Finance Data Science team owns the forecasting systems that power Snowflake’s revenue planning and long-term financial strategy. Our work supports corporate planning, executive decision-making, and investor reporting, and we partner closely with Product and Sales to understand customer behavior and product impact. We operate at the intersection of machine learning, statistical research, and corporate finance, building production-grade forecasting infrastructure that is foundational to how the company plans and operates. The Role As a Senior Data Scientist, you will independently lead high-impact modeling initiatives and build production-ready forecasting systems for core financial metrics. You will work on complex, open-ended problems at the intersection of machine learning and business strategy, translating real-world financial questions into rigorous, scalable models. What You’ll Do Design and implement advanced time-series and probabilistic models (e.g., hierarchical models, state-space models, Bayesian approaches, multivariate forecasting). Contribute to internal tooling and shared infrastructure that enables scalable forecasting and analytics. Establish best practices for model evaluation, backtesting, uncertainty quantification, and scenario simulat

EnCharge AI is a leader in advanced AI hardware and software systems for edge-to-cloud computing. EnCharge’s robust and scalable next-generation in-memory computing technology provides orders-of-magnitude higher compute efficiency and density compared to today’s best-in-class solutions. The high-performance architecture is coupled with seamless software integration and will enable the immense potential of AI to be accessible in power, energy, and space constrained applications. EnCharge AI launched in 2022 and is led by veteran technologists with backgrounds in semiconductor design and AI systems. Staff/Senior Staff Physical Design Floorplan & PDN Lead Experience: 10–14 Years Location: Bangalore/2 days to work Department: RTL-to-GDSII / Physical Implementation Role Overview We are seeking a high-caliber Staff or Senior Staff Physical Design Engineer with a specialized mastery of Floorplanning and Power Delivery Network (PDN) design. You won’t just be pushing buttons; you will be the architectural bridge between RTL/Systems and the final GDSII. This role requires a visionary who understands how a single floorplan decision ripples through the entire PPA (Power, Performance, Area) spectrum. As a technical lead, you will own the chip-top floorplan for complex, large-scale SoCs or Sub-chips, driving strategies that balance aggressive performance targets with robust power integrity. Key Responsibilities Architectural Floorplanning: Lead chip-level floorplanning, including macro placement, pin assignment, and partition definition for multi-million gate designs. Strategic PDN Design: Architect and implement complex Power Delivery Networks. You will define the metal stack usage and grid density to support high-performance cores while minimizing routing congestion. EMIR Mastery: Perform exhaustive IR-drop (Static/Dynamic) and Electromigration (EM) analysis. You must be able to diagnose root causes and propose ar

EnCharge AI is a leader in advanced AI hardware and software systems for edge-to-cloud computing. EnCharge’s robust and scalable next-generation in-memory computing technology provides orders-of-magnitude higher compute efficiency and density compared to today’s best-in-class solutions. The high-performance architecture is coupled with seamless software integration and will enable the immense potential of AI to be accessible in power, energy, and space constrained applications. EnCharge AI launched in 2022 and is led by veteran technologists with backgrounds in semiconductor design and AI systems. Job Title: Staff/ Senior Staff Physical Design Engineer (Technical Lead) Experience: Staff 8-10 years Senior Staff 11-13 years Location: Bangalore Hybrid/Remote or Remote in India The Role We are seeking a high-impact Staff/ Senior Staff Physical Design Engineer to serve as a Technical Lead for our next-generation silicon products. This is a "player-coach" role designed for a versatile expert who is equally comfortable architecting a convergence strategy as they are mentoring a small team of engineers. You will own the physical delivery of a major sub-chip or complex block, pushing the absolute limits of PPA (Power, Performance, Area) . As a Staff/Senior Staff lead, you are expected to be the "anchor" of the project—assertive in your decision-making, highly analytical in your debugging, and adept at managing stakeholders to ensure we hit our tape-out milestones without compromise. Key Responsibilities Technical Leadership: Lead a small team of PD engineers, providing technical direction, workload management, and architectural oversight for a sub-chip or partition. SOC clocking , FEV/VCLP specialized skills are preferred. Complex Block/Sub-chip Ownership: Take personal hands-on ownership of the most critical, high-congestion, or timing-critical blocks in the desi

EnCharge AI is a leader in advanced AI hardware and software systems for edge-to-cloud computing. EnCharge’s robust and scalable next-generation in-memory computing technology provides orders-of-magnitude higher compute efficiency and density compared to today’s best-in-class solutions. The high-performance architecture is coupled with seamless software integration and will enable the immense potential of AI to be accessible in power, energy, and space constrained applications. EnCharge AI launched in 2022 and is led by veteran technologists with backgrounds in semiconductor design and AI systems. Job Title: Senior Physical Design Engineer Experience: 4–7 Years Focus: Block-Level RTL-to-GDSII & PPA Optimization Location: Bangalore Hybrid The Role We are looking for a high-energy, technically curious Physical Design Engineer to join our advanced silicon team. This isn't a role for someone who wants to just "push buttons" on a vendor flow. We need a driver—someone with 4–6 years of experience who has lived through the trenches of quality tape-outs and is hungry to take full ownership of complex partitions. You will be expected to work with a high degree of independence, using your analytical skills to bridge the gap between a standard recipe and a world-class PPA result . You should be comfortable following expert lead direction while maintaining the "question the status-quo" mindset when you see a more efficient path. Key Responsibilities Partition Ownership: Lead the physical implementation of complex blocks from Synthesis and Floor-planning through to CTS, Routing, and Sign-off. PPA Recipe Development: Don't just run the flow—optimize it. You will perform deep-dive analysis on timing paths, power profiles, and congestion to derive custom optimization strategies. Automation-First Mindset: Use Tcl and Python to automate repetitive tasks, build custom analysis scripts, and enhan

EnCharge AI is a leader in advanced AI hardware and software systems for edge-to-cloud computing. EnCharge’s robust and scalable next-generation in-memory computing technology provides orders-of-magnitude higher compute efficiency and density compared to today’s best-in-class solutions. The high-performance architecture is coupled with seamless software integration and will enable the immense potential of AI to be accessible in power, energy, and space constrained applications. EnCharge AI launched in 2022 and is led by veteran technologists with backgrounds in semiconductor design and AI systems. Job Title: Principal Physical Design Engineer (RTL-to-GDSII) Experience: 14+ Years Technology Focus: Sub-5nm (3nm/2nm) Location: Bangalore Hybrid The Vision We are seeking a Principal Physical Design Engineer who thrives on complexity and rejects the "black box" approach to EDA tools. This role is for a First Principles thinker who questions the status quo. If a standard flow isn't yielding the desired PPA (Power, Performance, Area), you dive into the PDK, the tool algorithms, and the methodology to find a better way. You are responsible for transforming raw RTL into world-class silicon by eliminating systemic bottlenecks and building a scalable, predictable path to GDSII. Key Responsibilities Full-Flow Ownership: Lead the implementation of massive, high-speed blocks/SoCs from Synthesis through Sign-off using the Cadence Digital Suite . PPA Optimization: Push the theoretical limits of the PDK and tools. You will analyze and optimize the interplay between library cells, metal stacks, and tool engines to squeeze out every millivolt and picosecond. Methodology & Scalability: Build and refine a "Push-Button" style execution methodology that is robust, repeatable, and minimizes manual "human-in-the-loop" iterations. Cross-Functional "Left-Shift": Collaborate with RTL, Architecture, and DFT te

EnCharge AI is a leader in advanced AI hardware and software systems for edge-to-cloud computing. EnCharge’s robust and scalable next-generation in-memory computing technology provides orders-of-magnitude higher compute efficiency and density compared to today’s best-in-class solutions. The high-performance architecture is coupled with seamless software integration and will enable the immense potential of AI to be accessible in power, energy, and space constrained applications. EnCharge AI launched in 2022 and is led by veteran technologists with backgrounds in semiconductor design and AI systems. Job Description : Lead DFT Engineer (Edge Computing) Developing silicon for Edge Computing isn't just about speed; it’s about balancing high-performance data processing with extreme power efficiency and reliability in remote environments. As the Design for Test (DFT) Lead, you will be the architect of our testing strategy, ensuring our data center chips are flawlessly manufacturable and resilient enough for edge deployment. Key Responsibilities Architectural Leadership: Define and implement the end-to-end DFT architecture for complex SoCs, including Hierarchical DFT, Scan compression, Boundary Scan and MBIST. Edge-Specific Reliability: Develop strategies for In-System Test (IST) and power-on self-test (POST) to ensure chip health in remote edge data centers. Implementation & Flow: Oversee scan insertion, ATPG (Stuck-at, Transition, Path Delay), and Memory /Logic BIST. Cross-Functional Synergy: Collaborate with Design, Physical Design, and Yield teams to ensure high test coverage while minimizing area overhead and power impact as well as timing analysis . Post-Silicon Validation: Lead the bring-up and debug phase on ATE (Automated Test Equipment) to root-cause silicon failures and optimize test time. Technical Requirements Experience: 12+ years in DFT, with at least 2 years in a leadership or principal role. Tools: Mastery of industry-standard

EnCharge AI is a leader in advanced AI hardware and software systems for edge-to-cloud computing. EnCharge’s robust and scalable next-generation in-memory computing technology provides orders-of-magnitude higher compute efficiency and density compared to today’s best-in-class solutions. The high-performance architecture is coupled with seamless software integration and will enable the immense potential of AI to be accessible in power, energy, and space constrained applications. EnCharge AI launched in 2022 and is led by veteran technologists with backgrounds in semiconductor design and AI systems. About the Role EnCharge AI is seeking a highly skilled Device Driver Engineer to design and implement high-performance driver stack for our cutting-edge AI accelerator hardware. In this role, you will work closely with hardware, firmware, and AI software teams to develop low-latency, high-bandwidth communication between the host system and AI accelerator. Responsibilities Develop, optimize, and maintain Linux/Windows PCIe device drivers for AI accelerators. Implement low-level hardware interactions, DMA, memory management, and interrupt handling. Work on driver optimizations to reduce latency and improve throughput for AI workloads. Debug and troubleshoot PCIe protocol, kernel panics, crashes, and performance bottlenecks. Collaborate with hardware, firmware, and AI software teams to define driver interfaces. Ensure compliance with PCIe standards (Gen4/Gen5), SR-IOV, BAR memory mapping, and IOMMU. Support virtualization (VFIO, SR-IOV, DPUs) and containerized environments (Kubernetes, Docker, etc.). Develop tools for profiling, debugging, and monitoring driver performance. Contribute to open-source kernel modules if applicable. Qualifications Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or a related field. 3+ years of experience in device driver development for Linux and/or Windows. Strong experience with PCIe-based hardware, including BAR

EnCharge AI is a leader in advanced AI hardware and software systems for edge-to-cloud computing. EnCharge’s robust and scalable next-generation in-memory computing technology provides orders-of-magnitude higher compute efficiency and density compared to today’s best-in-class solutions. The high-performance architecture is coupled with seamless software integration and will enable the immense potential of AI to be accessible in power, energy, and space constrained applications. EnCharge AI launched in 2022 and is led by veteran technologists with backgrounds in semiconductor design and AI systems. About the Role EnCharge AI is looking for an Embedded SW Engineer to develop the firmware for our Edge AI processors. The candidate must possess an excellent understanding of computer architecture and operating system concepts including, but not limited to, memory management, virtualization and PCIe address space. The role includes designing and developing the core Firmware for various parts of the SOC. The candidate must possess strong communication skills to interface with Runtime, Architecture and H/W teams. Responsibilities Develop the critical pieces of EAI Firmware used to deploy inference jobs on EAI processors Validate different IP blocks on the SOC Evaluate and integrate third-party device drivers to interface with EnCharge’s SW stack Work closely with the Runtime, Hardware and Architecture teams define the driver architecture Qualifications Bachelors in EE/CS Advanced programming skills in C/C++ for operating system kernel & systems development Understanding of RISC-V architecture is a plus Exposure to PCIe BAR and IOMMU architecture Exposure to virtualization and hypervisor technologies Deep understanding of operating systems concepts, data structures, x86-64 and accelerator architectures Experience with low-level debug tools as well as emulators and simulators Experience running, analyzing, and tuning system performance benchmarks Excellent verb

EnCharge AI is a leader in advanced AI hardware and software systems for edge-to-cloud computing. EnCharge’s robust and scalable next-generation in-memory computing technology provides orders-of-magnitude higher compute efficiency and density compared to today’s best-in-class solutions. The high-performance architecture is coupled with seamless software integration and will enable the immense potential of AI to be accessible in power, energy, and space constrained applications. EnCharge AI launched in 2022 and is led by veteran technologists with backgrounds in semiconductor design and AI systems. About the Role EnCharge AI is seeking an AI Runtime Engineer to develop and optimize the execution stack for our next-generation AI accelerator. In this role, you will work on low-latency, high-performance runtime software that enables efficient execution of deep learning models on specialized hardware. You will collaborate with hardware, compiler, and AI framework teams to deliver optimized AI inference and training performance across cloud and edge environments. Responsibilities Develop and optimize the AI runtime software stack for executing deep learning workloads on AI accelerators. Implement task scheduling, memory management, and kernel execution strategies for efficient computation. Optimize data movement between host and device using PCIe, DMA, shared memory. Design and implement high-performance APIs for AI Inference frameworks such as OpenVino, ONNX Runtime, vLLM Work on graph execution optimizations, including kernel fusion, pipelining, tensor tiling, and caching. Integrate runtime components with AI compilers (LLVM, MLIR, XLA, TVM) for optimized execution. Ensure scalability and reliability of the AI runtime for cloud-based and edge AI deployments. Qualifications Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or a related field. 3+ years of experience in developing low-level runtime software for AI accelerators, GPUs, or