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Full Time Lte Optimization Engineer Jobs (NOW HIRING)

Formlabs

Senior 3D Print Optimization Engineer

Boston, MA · On-site

$115K - $148K/yr

As a 3D Print Optimization Engineer, you will be continuously using your problem-solving skills to ... Full time employees receive equity, in the form of RSUs. Your financial investment will grow with ...

Sonepar

Warehouse Optimization Engineer

$16.50 - $19.50/hr

We are seeking a Senior Warehouse Optimization Engineer to drive site-level and project-based ... full-time associates: * Healthcare plans * Dental & vision * Paid time off * Paid parental leave ...

Roblox

Principal Model Optimization Engineer

San Mateo, CA · On-site

$295K - $345K/yr

As a Model Optimization engineer on ML Platform, you will be responsible for digging deep into ... All full-time employees are also eligible for equity compensation and for benefits as described on ...

Sonepar

Warehouse Optimization Lead

$18.75 - $23.75/hr

The Lead Warehouse Optimization Engineer leverages advanced engineering principles, data science ... What We Offer You We offer great family-friendly benefits to full-time associates: * Healthcare ...

Nrel

ML and Optimization Engineer

Golden, CO · On-site

The National Laboratory of the Rockies (NLR) is seeking an accomplished full-time software engineer with experience in AI, optimization, applied mathematics, and high-performance computing within the ...

NIO

LLM Algorithmic Optimization Engineer

San Jose, CA

$143K - $186K/yr

Focus on model optimization from a systems perspective, ensuring efficient deployment in the ... The US base salary range for this full-time position is $143,200.00 - $186,000.00. * Within the ...

NIO

LLM Algorithmic Optimization Engineer

San Jose, CA · On-site

$143K - $186K/yr

Focus on model optimization from a systems perspective, ensuring efficient deployment in the ... The US base salary range for this full-time position is $143,200.00 - $186,000.00. * Within the ...

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How much do full time lte optimization engineer jobs pay per year?

As of Jun 26, 2026, the average yearly pay for full time lte optimization engineer in the United States is $96,107.00, according to ZipRecruiter salary data. Most workers in this role earn between $80,000.00 and $108,000.00 per year, depending on experience, location, and employer.
What are the most commonly searched types of Lte Optimization Engineer jobs? The most popular types of Lte Optimization Engineer jobs are:
Full Time Lte Optimization Engineer jobs near you

LLM Inference Frameworks and Optimization Engineer

Together AI

San Francisco, CA • On-site

$160K - $230K/yr

Full-time

Medical

Posted 5 days ago

Job description

About the Role
At Together.ai, we are building state-of-the-art infrastructure to enable efficient and scalable inference for large language models (LLMs). Our mission is to optimize inference frameworks, algorithms, and infrastructure, pushing the boundaries of performance, scalability, and cost-efficiency.
We are seeking anInference Frameworks and Optimization Engineer to design, develop, and optimize distributed inference engines that support multimodal and language models at scale. This role will focus on low-latency, high-throughput inference, GPU/accelerator optimizations, and software-hardware co-design, ensuring efficient large-scale deployment of LLMs and vision models.
This role offers a unique opportunity to shape the future of LLM inference infrastructure, ensuring scalable, high-performance AI deployment across a diverse range of applications. If you're passionate about pushing the boundaries of AI inference, we'd love to hear from you!
Responsibilities
Inference Framework Development and Optimization
  • Design and develop fault-tolerant, high-concurrency distributed inference engine for text, image, and multimodal generation models.
  • Implement and optimize distributed inference strategies, including Mixture of Experts (MoE) parallelism, tensor parallelism, pipeline parallelism for high-performance serving.
  • Apply CUDA graph optimizations, TensorRT/TRT-LLM graph optimizations, and PyTorch-based compilation (torch.compile), and speculative decoding to enhance efficiency and scalability.
Software-Hardware Co-Design and AI Infrastructure
  • Collaborate with hardware teams on performance bottleneck analysis, co-optimize inference performance for GPUs, TPUs, or custom accelerators.
  • Work closely with AI researchers and infrastructure engineers to develop efficient model execution plans and optimize E2E model serving pipelines.
Requirements
Must-Have:
  • Experience:
    • 3+ years of experience in deep learning inference frameworks, distributed systems, or high-performance computing.
  • Technical Skills:
    • Familiar with at least one LLM inference frameworks (e.g., TensorRT-LLM, vLLM, SGLang, TGI(Text Generation Inference)).
    • Background knowledge and experience in at least one of the following: GPU programming (CUDA/Triton/TensorRT), compiler, model quantization, and GPU cluster scheduling.
    • Deep understanding of KV cache systems like Mooncake, PagedAttention, or custom in-house variants.
  • Programming:
    • Proficient in Python and C++/CUDA for high-performance deep learning inference.
  • Optimization Techniques:
    • Deep understanding of Transformer architectures and LLM/VLM/Diffusion model optimization.
    • Knowledge of inference optimization, such as workload scheduling, CUDA graph, compiled, efficient kernels
  • Soft Skills:
    • Strong analytical problem-solving skills with a performance-driven mindset.
    • Excellent collaboration and communication skills across teams.

Nice-to-Have:
  • Experience in developing software systems for large-scale data center networks with RDMA/RoCE
  • Familiar with distributed filesystem(e.g., 3FS, HDFS, Ceph)
  • Familiar with open source distributed scheduling/orchestration frameworks, such as Kubernetes (K8S)
  • Contributions to open-source deep learning inference projects.

About Together AI
Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers in our journey in building the next generation AI infrastructure.
Compensation
We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $160,000 - $230,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.
Equal Opportunity
Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.
Please see our privacy policy at https://www.together.ai/privacy

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