
EnCharge AI provides efficient, low‑power AI computing solutions that let businesses run advanced models from edge devices to the cloud. The company designs analog in‑memory computing chips and pairs them with hardware and software systems to accelerate dense matrix operations and reduce compute, power, and space requirements. Its product stack targets edge-to-cloud deployments and power‑constrained applications, integrating with existing AI workflows and system software for inference and model deployment. Founded in 2022 by semiconductor and AI systems veterans, EnCharge reports large-scale production experience, patents, and sustainability-focused efficiency gains.

EnCharge AI provides efficient, low‑power AI computing solutions that let businesses run advanced models from edge devices to the cloud. The company designs analog in‑memory computing chips and pairs them with hardware and software systems to accelerate dense matrix operations and reduce compute, power, and space requirements. Its product stack targets edge-to-cloud deployments and power‑constrained applications, integrating with existing AI workflows and system software for inference and model deployment. Founded in 2022 by semiconductor and AI systems veterans, EnCharge reports large-scale production experience, patents, and sustainability-focused efficiency gains.
Founded: 2022
Headquarters: Santa Clara, California
Tech focus: Analog in-memory AI accelerators and software for edge-to-cloud
Recent funding: Series B > $100M (announced Feb 2025)
Energy- and space-constrained AI inference acceleration for edge-to-cloud deployments.
2022
Data and Analytics
21700000
Emergence from stealth with $21.7M
22600000
Raised $22.6M to commercialize chips
100000000+
Series B announced as more than $100M
“Includes both financial and strategic investors such as Tiger Global, Samsung Ventures, CTBC/HH-CTBC, AlleyCorp, and others”
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Senior Simulation Architect
Locations: Bangalore / Remote (Any where in India )
Job Description:
Simulation Architect
We are looking for a Simulation Architect to lead the design, development, and
optimization of our C++ NPU architecture simulator, including creation of scalable multi-
hardware, and software teams to explore current- and next-generation NPU designs.
You will lead the architecture simulator’s infrastructure, performance, scalability, and
usability, ensuring it serves as a robust platform for both architecture exploration, hardware
implementation and verification, and workload performance analysis. You’ll work closely
with architects, designers, and software engineers to evolve the simulator into a world-
class infrastructure supporting future product designs.
Key Responsibilities
• Architecture Simulator Infrastructure Leadership
Design, maintain, and evolve the NPU simulator framework to ensure its
performance, scalability, and reliability
• Performance Optimization
Profile and improve simulator runtime performance to accelerate design iteration
and enable larger and more complex workloads using multiple threads/cores
• Scalability
Architect and implement multi-NPU simulation model, including modeling of inter-
NPU communication, synchronization and shared or distributed memory systems
• Developer Enablement
Build infrastructure and APIs that make it easy for (a) architects and other simulator
developers to add new components and features, and (b) hardware designers and
verification engineers to gather necessary implementation details
• User Experience Tools
Develop supporting tools, scripts, and automation to simplify workload analysis and
information gathering
• Cross-Team collaboration
Partner with architects, performance analysts, and software engineers to define
requirements and prioritize improvements
Required Background
• Strong software engineering background, with expertise in C++, Python, and
scalable simulation frameworks• Experience in developing or maintaining hardware architecture or performance
simulators
• Experience with parallel programming models such as pthreads and MPI
• Strong system design and debugging skills
• Familiarity with performance profiling, parallelization, and simulation optimization
techniques
• Excellent communication and collaboration skills across multi-disciplinary teams
Nice to Have
• Experience in NPU, GPU, or AI accelerator architecture
• Familiarity with machine learning workloads
Contact:
Uday
Mulya Technologies
muday_bhaskar@yahoo.com
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