Senior Inference Engineer

DeepRec.ai; Palo Alto (CA); Hybrid; USD 180,000 - 240,000; Full time

Benefits offered by this job

Competitive salary

Equity

Health benefits

Monthly stipends

Company retreats

In-office culture

Job summary

DeepRec.ai in Palo Alto, CA seeks a Senior Inference Engineer to accelerate AI-driven video generation products. You will design and optimize inference pipelines, implement acceleration techniques, and push the boundaries of real-time AI deployment.

You will collaborate with researchers and engineers to deploy state-of-the-art video generation and language models, scale performance, and mentor fellow engineers in GPU programming.

Qualifications

• 5+ years of engineering experience in inference acceleration and model deployment at scale.
• Expertise in inference optimization, including quantization and attention acceleration.
• Strong CUDA/NCCL and GPU programming knowledge; experience with SP, TP, PP parallelism.
• Familiarity with video generation models and large language models (LLMs).
• Excellent cross-functional collaboration and ownership in fast-paced environments.

Responsibilities

• Accelerate inference pipelines and optimize for real-time video generation.
• Improve GPU utilization with tensor, sequence, and pipeline parallelism.
• Develop high-performance kernels using CUDA and NCCL.
• Collaborate with researchers and engineers to deploy state-of-the-art models.
• Mentor engineers, participate in code reviews, and promote best practices in GPU programming.

Skills

Inference acceleration

CUDA

NCCL

GPU programming

Quantization

Attention optimization

Model deployment

Distributed inference

Video generation

LLMs

Collaboration

Ownership mindset

Tools

CUDA

NCCL

Job description

Senior Inference Engineer AI Video Generation Company (Stealth) | Palo Alto, CA | Hybrid

About the Role We are seeking a Senior Inference Engineer to accelerate the performance of our AI-driven video generation products. In this highly technical role, you will operate at the intersection of cutting-edge inference acceleration, GPU parallelism, advanced model deployment, and video generation technologies. Your expertise will drive significant improvements to model speed and efficiency, ensuring our creative AI systems deliver industry-leading user experiences at scale.

You will design and optimize inference pipelines, implement state-of-the‑art acceleration techniques, and work closely with researchers and engineers across the team to push the boundaries of what's possible in real-time AI deployment. Your efforts will play a foundational role in powering the next generation of our video and language models.

What You’ll Do

• Accelerate Inference: Lead and implement advanced inference acceleration techniques, including attention optimization and quantization for efficient model serving.
• Maximize GPU Parallelism: Engineer and optimize GPU strategies across tensor, sequence, and pipeline parallelism (TP, SP, PP) for maximal efficiency and scalability.
• Programming for Performance: Develop and optimize high-performance computing kernels and distributed workloads using CUDA and NCCL.
• Advance AI Deployment: Collaborate with research and engineering teams to bring state-of-the‑art video generation and large language models into production.
• Improve Training Efficiency: Contribute to improvements in model training speed, stability, and resource utilization as part of our deployment lifecycle. (Bonus)
• Technical Excellence: Drive rigorous code reviews, participate in technical discussions, and mentor fellow engineers on best practices in inference and GPU programming.

What We’re Looking For

• Experience: 5+ years of engineering experience, with a strong track record in inference acceleration and model deployment at scale.
• Inference Mastery: Proven expertise in inference optimization, including quantization, attention acceleration, and deep learning compiler stacks.
• GPU and Parallelism: Deep knowledge of GPU programming (CUDA, NCCL) and experience with SP, TP, PP, and other forms of parallelism for distributed inference.
• AI Domain Knowledge: Familiarity with video generation models and large language models (LLMs).
• Collaboration: Strong cross-discipline communication skills; able to drive shared goals across research and engineering functions.
• Ownership Mindset: Self-driven, solutions-oriented, and capable of managing ambiguity in a fast-paced startup environment.

Nice to Have

• Experience with high-throughput video or real-time streaming model deployment.
• Familiarity with distributed training and optimization toolkits.
• Contributions to open source projects in AI infrastructure or deep learning compilers.
• Startup or rapid prototyping experience.

What We Offer

• Competitive salary commensurate with AI industry benchmarks.
• Equity in a fast-growing company shaping the future of generative AI.
• Comprehensive health benefits, monthly stipends, and company retreats.
• A collaborative, in-office culture focused on building and shipping together.

About the Company

A well-funded, early-stage AI video generation startup headquartered in Palo Alto, CA. The team is building technology to make video creation seamless, intuitive, and universally accessible through the transformative power of AI. Tight-knit and highly energetic, the company values efficiency, intellectual curiosity, and the ambition to make a meaningful impact on the world.