AI Compiler Engineer

🕒 June 10

🌐 United States, Canada, +2 more countries – Remote

🇺🇸 United States – Remote 🇨🇦 Canada – Remote 🇩🇪 Germany – Remote 🇳🇴 Norway – Remote

🏄 California – Remote

🏄 California – Remote

💵 $190k - $255k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 Artificial Intelligence

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

👻 Ghost score 3%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

Apply Now

Find Similar Remote Jobs

Set Up Email Alert For New Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

EnCharge AI

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2022

🤖 Artificial Intelligence

🔧 Hardware

🤝 B2B

💰 $100M Series B - EnCharge AI on 2025-02

Artificial Intelligence • Hardware • B2B

EnCharge AI is a company that develops analog in-memory computing hardware and complementary software to accelerate on-device and edge-to-cloud AI workloads. Their technology includes the EN100 analog AI accelerator and other form factors (chiplets, ASICs, PCIe cards) designed to deliver much higher energy efficiency, compute density, and lower total cost of ownership for inference compared with conventional GPUs and digital accelerators. EnCharge emphasizes sustainability, data privacy through local processing, and deployment for enterprise and developer customers seeking efficient, scalable AI computation outside traditional cloud infrastructure.

📋 Description

• 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.

🎯 Requirements

• 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.

🏖️ Benefits

• Health insurance • Retirement plans • Paid time off • Flexible work arrangements • Professional development • Bonuses • Stock options • Equipment allowances • Wellness programs