---
title: 'AI Compiler Engineer at EnCharge AI'
canonical: 'https://feeny.ai/job/ai-compiler-engineer-encharge-ai-india-t36t6zr2xn3m'
type: 'job'
last_seen: '2026-09-05'
---

# AI Compiler Engineer at EnCharge AI

- **Company:** EnCharge AI
- **Location:** India
- **Posted:** 2025-07-10
- **Last confirmed live:** 2026-09-05
- **Apply:** https://job-boards.greenhouse.io/enchargeai36/jobs/4008053009

## Job description

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.

## Qualifications

- Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or related field (Ph.D. preferred).
- 3+ years in compiler development, with a strong focus on AI or ML graph compilers.
- Proficiency in AI graph compiler frameworks (e.g., MLIR, Torch-FX)
- Solid background in hardware architectures (e.g., GPUs, TPUs, ASICs) and optimization techniques such as fusion, quantization, and tiling.
- Familiarity with neural networks operators and code generation.
- Strong understanding of intermediate representations, code parsing, and semantic analysis in compiler design.
- Proficiency in C++, Python, or other programming languages commonly used in compiler development.
- Open-source contributions to AI software frameworks and libraries is a plus
- Demonstrated experience leading and mentoring engineering teams with successful project delivery.

EnchargeAI is an equal employment opportunity employer in the United States.

## About EnCharge AI

## Company Overview
- **One-liner**: EnCharge AI develops analog in-memory computing hardware and software to deliver high-efficiency, low-cost AI inference from edge devices to cloud data centers.
- **Entity Type**: Private (Series B – II stage)
- **Headquarters**: Santa Clara, California, United States
- **Founded**: 2022
- **Founders**: Naveen Verma, Ph.D. (CEO) and Kailash Gopalakrishnan, Ph.D. (CTO)

## Core Business
- **Primary industry**: AI semiconductor hardware and embedded software products
- **Target customers**: B2B – enterprises deploying AI at scale, edge-device manufacturers, cloud service providers, and defense/industrial sectors
- **Mission**: Democratize advanced AI by enabling deployment beyond cloud infrastructure to local servers and mobile devices, while slashing costs and environmental impact

## Products & Services
- **Analog In-Memory Computing GPUs & Digital AI Accelerators**: Custom silicon (chiplets, ASICs) and standard-form-factor PCIe cards that perform AI inference using analog computation for orders-of-magnitude better energy efficiency and compute density.
- **Software Stack**: Seamless orchestration layer that supports on-device and cloud deployment, enabling model portability, quantization, and compiler optimizations across EnCharge’s hardware.
- **Edge-to-Cloud Platforms**: Integrated solutions for power-, space-, and cost-constrained environments, covering autonomous systems, smart devices, data center inference, and private on-premise AI.

## Market Standing
- **Valuation / Market Cap**: Not publicly disclosed
- **Key Metrics**: Annual Revenue ~$10M (LinkedIn estimate) | Total Funding $162.9M
- **Notable Investors & Partners**: Tiger Global Management (led $100M Series B, Mar 2025), Anzu Partners (led $21.7M Series A, Dec 2022), DARPA ($18.6M grant, Mar 2024), and others including corporate/institutional backers.
- **Growth Signals**: 
  - 58.6% YoY headcount growth (75 employees, as of mid-2025)
  - 39 active job openings spanning hardware, compiler, and AI architecture roles
  - 150+ patents granted, 300+ technical publications
  - Talent inflows from Intel, IBM, Cerebras, AMD, Meta, Microsoft

## Competitive Advantages
- **Analog In-Memory Computing Moa**t: A proprietary compute architecture that uses charge-domain analog circuits, validated silicon, and leverages existing semiconductor supply chains.
- **Record Efficiency**: Claims 20× higher TOPS/W, 9× higher compute density (TOPS/mm²), 10× lower total cost of ownership, and 100× lower CO₂ emissions compared to leading cloud/GPU alternatives.
- **Deep IP Portfolio**: 150+ granted patents and 300+ publications from 20+ years of foundational research by the founding team (Princeton, IBM, etc.).
- **End-to-End Solution**: Full-stack hardware and software (compiler, quantization, runtime) designed for seamless edge-to-cloud orchestration without vendor lock-in.

## Strategic Focus
- Scale production and customer deployments of their analog in-memory compute chips for high-volume edge and data center inference.
- Expand software ecosystem to support mainstream AI frameworks (PyTorch, TensorFlow, ONNX) and enable easy drop-in replacement for existing GPU-accelerated workloads.
- Deepen partnerships with defense (DARPA) and enterprise cloud providers, emphasizing data privacy, security, and sustainability.
- Double down on sustainability messaging (100× lower CO₂) to meet ESG mandates in enterprise AI procurement.

## Why Work Here
- **Mission-Driven Impact**: Opportunity to make AI accessible to the “99%” by dramatically reducing energy and cost barriers. Work is cited as a “once-in-a-lifetime” chance by leadership.
- **World-Class Team**: Colleagues include industry luminaries from Princeton, IBM, and top semiconductor houses; 57% of staff are in technical roles (engineering, research, compiler).
- **Culture of Collaboration & Innovation**: The careers page highlights integrity, growth, and collaborative problem-solving in a fast-paced startup environment.
- **Comprehensive Rewards**: Benefits package includes typical startup perks; equity likely offered given funding stage.
- **Work Policy**: Hybrid presence indicated by offices in Santa Clara, Canada, Germany, Norway, South Korea, and India. Remote flexibility likely for some roles.
- **Active Hiring**: 39 open positions across DFT, physical design, compiler engineering, and NPU architecture – strong signal of scaling and technical investment.

## Sources
1. [EnCharge AI Official Website](https://www.enchargeai.com/)
2. [EnCharge AI Careers Page](https://www.enchargeai.com/careers)
3. [EnCharge AI About Us (Leadership & Founders)](https://www.enchargeai.com/about-us)
4. [EnCharge AI LinkedIn Company Page](https://www.linkedin.com/company/encharge-ai)
5. [CB Insights Profile – EnCharge AI](https://www.cbinsights.com/company/encharge-ai)

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