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Face Models Jobs in Kentucky (NOW HIRING)

... models, in-house RTL simulation, and measured runs on competing GPUs and accelerators. You will ... Bring up inference workloads from Hugging Face, PyTorch, published papers, and vendor stacks such ...

New

$18.13 - $22.17/hr

At The North Face we dare to lead the world forward through Exploration. We were born to Explore ... Model inclusive behavior that respects diverse backgrounds and experiences. What do you need to ...

About Face Reality Our Core Values Integrity, Inclusion, Collaboration, Adaptability, Accessibility Our supportive business model ensures that everyone has a clear path to success and growth. We ...

Face Reality Skincare was created with one goal: to give people clear skin for good. With over 50 ... model ensures that everyone has a clear path to success and growth. We foster an inclusive space in ...

... models, prefill versus decode, KV cache, expert routing, and quantization, plus retrieval, speech, vision, and recommendation workloads where they map onto the accelerator. * Bind Hugging Face and ...

New

Model Oncology partners with community health systems to build and operate sustainable oncology ... Serve as the external face of the oncology program, building trust with referring physicians ...

New

... models, plus retrieval, speech, vision, and recommendation workloads where they map onto the accelerator. * Bind Hugging Face and PyTorch workloads to the programming model and runtime, then run them ...

New

$77K - $105K/yr

Senior Machine Learning Engineer We're looking for a Senior ML Engineer to advance our age bracket classifiers and face recognition models. We run 5 binary classifiers (+12/+15/+18/+21/+25) deployed ...

We are looking for a hands‑on Applied Engineer with deep expertise in training foundation models ... • NeMo, JAX, or Hugging Face Transformers. * Experience building or working with ...

$76K - $103K/yr

Hugging Face, LangChain) * Familiarity with REST APIs and REST-based AI services * Understanding of containerization (Docker) and model deployment workflows * Experience with speech, vision, or NLP ...

Develop state-of-the-art NLP models using GPT, BERT, T5, and Hugging face transformers for tasks like text generation, summarization, and information retrieval * Perform data cleaning, normalization ...

... Face, Physical Intelligence, or equivalent. * Has personally trained, fine-tuned, post-trained, and materially improved large models. * Has built agent systems, model infra, evals, data pipelines ...

About the Role As an AI Image Evaluator, you will help image generation models learn two things at ... You notice small details: an extra finger, a mismatched shadow, a brand mark, a face that is a ...

Our innovative models transform lives, enhance communities, and save healthcare systems millions of ... Conducting annual face-to-face visits, reassessments, and care plan updates. * Following up with ...

Experience with Hugging Face Transformers & Datasets. * Familiarity with XML/XSD and Office document parsing tools. * Experience deploying models with vLLM, TGI, or Ollama. * Understanding of ...

$44.25 - $57.25/hr

Implement camera capture pipelines for liveness detection and face analysis using AVFoundation * Port our ONNX age classification models to Core ML for on-device inference * Build document capture ...

$177K - $216K/yr

Leverage the Hugging Face Transformers library and model hub to develop state-of-the‑art language models and text analytics solutions. * Create and maintain machine learning models that perform ...

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Face Models information

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How much do face models jobs pay per hour?

As of Sep 11, 2026, the average hourly pay for face models in Kentucky is $39.70, according to ZipRecruiter salary data. Most workers in this role earn between $12.93 and $62.64 per hour, depending on experience, location, and employer.

What is the difference between Face Models vs Makeup Models?

AspectFace ModelsMakeup Models
Required CredentialsMinimal; often based on appearance and skin conditionMinimal; focus on makeup application and skin suitability
Work EnvironmentPhoto shoots, fashion shows, advertisingPhoto shoots, beauty campaigns, runway shows
Industry UsageFashion, advertising, beautyBeauty, cosmetics, fashion
Search & Comparison IntentPeople seeking face modeling opportunities or infoPeople comparing face models and makeup models roles

Face models primarily focus on showcasing facial features for various media, requiring minimal credentials. Makeup models, on the other hand, are used to display makeup products and techniques. Both roles are common in fashion and beauty industries, often overlapping in photo shoots and campaigns. Understanding these differences helps individuals identify the right modeling path based on their appearance and career goals.

What are popular job titles related to Face Models jobs in Kentucky?

For Face Models jobs in Kentucky, the most frequently searched job titles are:

What job categories do people searching Face Models jobs in Kentucky look for?

The top searched job categories for Face Models jobs in Kentucky are:

Infographic showing various Face Models job openings in Kentucky as of September 2026, with employment types broken down into 57% Full Time, 29% Part Time, and 14% Contract. Highlights an 86% In-person, and 14% Remote job distribution, with an average salary of $82,585 per year, or $39.7 per hour.

Senior Modeling Architect, Performance Benchmarking

On-site

Neurophos, Inc.
1 - 10 employees

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 3 days ago

New


Job description

About Neurophos

The demand for new data centers and AI compute is rapidly outpacing the planet's energy capacity. Digital solutions are hitting a power wall as we approach the physical limits of traditional silicon. Conquering this bottleneck means rethinking the fundamental architecture of inference compute. The industry's current path can't meet the need, so we're taking a different approach.

Instead of traditional electronic circuits, we use silicon photonics and an active, programmable metasurface to perform matrix multiplications at the speed of light. Our optical cells are 10,000x smaller than traditional photonic components, enabling unprecedented density. By using photonics instead of electricity, our chips become more efficient as they scale. This architecture will deliver up to 100 times the energy efficiency of existing solutions while significantly improving performance for large-scale AI inference.

We’ve assembled a world-class team of industry veterans and recently raised a $110M Series A led by Gates Frontier. Participants include M12 (Microsoft’s Venture Fund), Carbon Direct Capital, Aramco Ventures, Bosch Ventures, Tectonic Ventures, Space Capital, and others.

Join us and shape the future of computing!

Location: Austin, TX or Sunnyvale, CA. Full-time onsite position.

Reports To: Sr. Director of Modeling

FLSA Status: Exempt

Position Overview

We are seeking a performance engineer to own the benchmarking numbers behind the T100 optical inference accelerator. Architecture and product decisions here are made on measured performance and energy, and this role produces those figures for the same workloads at every level of fidelity we use: roofline and limiter analysis, architecture performance models, in-house RTL simulation, and measured runs on competing GPUs and accelerators.

You will join the Architecture and Modeling team, set the measurement methodology, and keep it current as models, software stacks, drivers, and hardware generations turn over. Every result ships with the harness, config, plots, logs, and assumptions behind it, so anyone can rerun it and see how the number was reached.

Key Responsibilities
  • Own the performance and energy metrics that architecture, product, and leadership rely on, and keep them consistent across modeling fidelities and measured hardware.

  • Produce numbers for the same workloads across all fidelities we use internally: roofline and limiter models, architecture performance models, in-house RTL simulation, and measured competitor hardware. Work with the modeling team to keep the simulated and measured workload sets aligned.

  • Hold workload definitions constant across fidelities, including model or application, sequence length, batch, precision, prefill versus decode, and tensor, pipeline, and sequence parallelism.

  • Bring up inference workloads from Hugging Face, PyTorch, published papers, and vendor stacks such as vLLM, SGLang, TensorRT-LLM, and Triton Inference Server. These include dense and Mixture-of-Experts (MoE) transformers, attention and KV-cache reduction strategies, and hybrid/SSM models, as well as retrieval, speech, vision, and recommendation workloads that map onto the accelerator.

  • Measure competing GPUs and accelerators end-to-end, owning the cloud or lab account, image, drivers, and run recipe.

  • Report time to first token (TTFT), inter-token latency (ITL), tokens per second, tokens per second per watt, and energy, using nvidia-smi, DCGM, power capping, or equivalent instrumentation.

  • Document where RTL simulation, the performance model, and measured competitor results disagree, and attach the configs and logs behind each.

  • Maintain a reviewed internal benchmark suite. Keep internal-only results clearly separate from anything cleared for customer or public use, and route external claims through the designated approver before they ship.

Qualifications
  • BS or MS in Computer Engineering, Electrical Engineering, Computer Science, or equivalent practical experience.

  • 5+ years of experience in GPU performance engineering, accelerator benchmarking, HPC performance measurement, or ML systems measurement.

  • Track record of building or operating benchmark harnesses that produced measured results on real GPUs or accelerators, including turning a Hugging Face model card, paper, or application description into a runnable benchmark.

  • Hands-on experience with roofline analysis, limiter analysis, or analytical performance modeling.

  • GPU performance analysis with NVIDIA Nsight Systems and Nsight Compute, or an equivalent profiler, covering HBM-bound versus compute-bound analysis, precision (FP16, BF16, FP8, INT8), and batching.

  • Working knowledge of LLM inference stacks such as Hugging Face, vLLM, SGLang, or TensorRT-LLM, including prefill versus decode, continuous batching, and MoE.

  • Proficiency in Python for harnesses, parsing, and plots, and comfort working in Linux.

  • Cloud GPU operations on AWS, GCP, or Azure, including containers, instance types, drivers, quotas, and cost.

Preferred Skills
  • Experience correlating a performance model or RTL/Verilator simulation against measured silicon or GPUs.

  • GPU kernel work in CUDA, CUTLASS, or Triton, or familiarity with PyTorch internals.

  • Familiarity with current inference-serving internals such as PagedAttention, FlashAttention, speculative decoding, and disaggregated prefill.

  • Distributed inference experience covering collectives, all-reduce, NCCL, NVLink, and InfiniBand, or work with MLPerf or production inference benchmarking pipelines.

  • Background at a hyperscaler, GPU vendor, accelerator company, or inference lab.

What We Offer

This is an opportunity to play a pivotal role in an innovative startup redefining the future of AI hardware. Work on game-changing technology at the intersection of photonics and AI as part of a collaborative, brilliant team. You’ll contribute to a platform that redefines computational performance and accelerates the future of artificial intelligence. Come help us bring this transformative technology to the world.

Benefits

Join a team that invests in your future and your well-being. At Neurophos, we offer:

  • 100% coverage of base health plan premiums for you and your dependents, plus HSA contributions.

  • Unlimited PTO. No rigid vacation banks, just a focus on delivery.

  • 401(k) matching and stock option opportunities to ensure our success is your success.

  • Full suite of voluntary benefits, including Dental, Vision, Life, Hospital, Critical Illness, and Accident insurance.

  • Personalized Benefits. Choose the plans that fit your life and take the cash back for those that don’t.

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