quantization Jobs

Nebius is building a full-stack AI cloud platform to support developers and enterprises in the global AI economy, from data and model training through to production deployment. The Nebius Token Factory is seeking scientists to tackle frontier LLM and VLM inference bottlenecks by turning them into research questions, conducting rigorous experiments, and translating findings into production capabilities. You will own focused research and optimization projects, write strong code, and produce prototypes, publications, and technical artifacts for engineers to build upon. Your research will cover areas like quantization, distillation, speculative decoding, KV-cache optimization, and model/runtime co-optimization, alongside inference engines and distributed inference architectures. You will evaluate trade-offs across model quality, latency, throughput, memory footprint, and cost per token, and collaborate with engineering teams to bring promising results into production.

$195k - $262k

Nebius is building a full-stack AI cloud platform to support developers and enterprises from data and model training through to production deployment. As a Senior Machine Learning Engineer on the Applied AI team, you will own model and endpoint optimization from model artifacts through production deployment. Your work will span model internals, quantization, model compression, speculative decoding, KV-cache optimization, inference engines, and serving architecture to improve latency, throughput, memory efficiency, GPU utilization, and cost per token while preserving model quality and reliability. You will collaborate with kernel and platform engineers to investigate serving problems, compare configurations, and resolve performance and quality regressions, validating improvements through reproducible benchmarks and safe production rollouts.

$195k - $262k

CoreWeave is seeking a Senior Engineer for its Benchmarking & Performance team, focusing on GPU kernel authoring and optimization. In this role, you will be responsible for writing, profiling, and tuning GPU kernels that are critical for large-scale model serving, aiming to maximize throughput and minimize latency. You will also contribute to industry-leading performance benchmarking publications. This position requires an individual who can lead designs, improve engineering standards, and deliver significant enhancements to latency, throughput, and reliability across the inference stack. You will collaborate with product, orchestration, and hardware teams to translate kernel-level optimizations into system-wide improvements and meet stringent Service Level Agreements (SLAs) at scale.

$182k - $242k

Anduril Industries is a defense technology company focused on transforming military capabilities with advanced technology. The Air Dominance & Strike team develops aerial and multi-domain robotic systems, including unmanned fighter jets and cruise missiles, and the Lattice for Mission Autonomy software platform. We are seeking an AI Research Scientist to be a founding ML expert, designing, fine-tuning, and deploying generative AI, LLMs, and agentic systems for our air-dominance platforms. This is a highly applied research role focused on making state-of-the-art LLM models smaller, faster, and smarter, optimizing them for both offboard systems and power-constrained edge hardware. As an early member, you will have significant autonomy to set technical direction, design data collection strategies, and influence multi-agent autonomy deployment.

$220k - $292k

Tavus is building the human layer of AI, aiming to make human-AI interaction as natural as face-to-face communication. We pioneer research in multimodal AI for modeling human communication (language, audio, video) and generating audio-visual avatar behavior, powering applications from text-to-video avatars to real-time conversational video. We are a Series B company backed by top investors, seeking individuals who thrive in startup environments, can prioritize independently, and are willing to take calculated risks to help pave the path forward.

Chai Discovery is building the computer-aided design suite for molecules, with major pharmaceutical companies already using their platform to accelerate drug discovery. They are at the forefront of reinventing life sciences through AI, developing frontier models that understand biochemical structure and interaction. This role is an opportunity to push the boundaries of AI drug design alongside a skilled and dedicated team.

Join Tenstorrent’s AI Models team and work at the layer most ML engineers never see: bringing advanced models to life on custom AI hardware. You’ll own real workloads end‑to‑end including porting, tuning, and validating LLMs and vision models on our accelerator, and chasing down every last millisecond and percentage point of accuracy. This role is for people who love the craft of ML engineering and want their work to matter at silicon scale, not just behind another API. This role is hybrid, based in Cyprus. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting.

Deepgram is seeking an Applied ML Engineer to focus on deploying their advanced speech models to a variety of edge devices and non-NVIDIA accelerators. This role involves adapting existing models to run efficiently within diverse hardware constraints, including different inference runtimes and operator sets. You will be responsible for optimizing models through techniques like quantization and precision adjustments, validating performance on real hardware, and building robust deployment pipelines for edge targets. This is a hands-on engineering position, distinct from research or cloud-focused roles, aimed at ensuring Deepgram's cutting-edge voice AI can be deployed effectively across a wide range of customer hardware.

$155k - $245k

Parallel Wireless is seeking a hands-on technical leader to build and operate a secure local large-language-model (LLM) platform. This platform will enable engineering and business teams to leverage generative AI with proprietary company data, including source code, product documentation, and technical standards, all within a secure, company-controlled environment. This senior individual contributor role involves applied LLM engineering, platform architecture, data pipelines, security, and production operations. You will transform prototypes into a dependable internal capability by selecting and optimizing open-weight models, building permission-aware retrieval systems, creating reusable APIs and tools, integrating with existing workflows, and establishing metrics for quality, safety, latency, capacity, and business value. The role emphasizes building a trustworthy enterprise LLM solution that includes robust source grounding, access controls, repeatable evaluation, observable services, and a sustainable operating model.

SF Tensor is building the future of high-performance compute for AI by optimizing the entire stack, from hardware to cloud. They are developing a Kernel Optimizer for faster, cheaper, and more accessible compute, and a Model Foundry to manage experiments and move workloads across clouds and chips. This role focuses on the modeling side of their enterprise offering, which aims to turn customer datasets into specialist models in days. The infrastructure is designed to accelerate research and model training, enabling rapid experimentation and deployment.

$275k - $315k

Hyperbound is seeking a Machine Learning Engineer to build and ship the models powering their Revenue Activation Platform. This role involves owning the full lifecycle of models, from training and fine-tuning open-source models to deploying them in production and ensuring their performance. You will focus on pushing models on-device, building robust evaluation frameworks, and contributing to the company's agentic operating system for sales. This is a challenging, fast-paced role where you'll work closely with founders and engineering, with significant input into product development.

$260k - $300k

Thinking Machines is seeking a researcher to scale reinforcement learning for frontier models. This role focuses on the intersection of training recipes and infrastructure, particularly for high-training-compute, long-horizon RL. A key area of interest is asynchronous RL, requiring a deep understanding of its algorithms, design choices, and trade-offs on both ML and systems sides. The position also emphasizes the importance of inference systems, low-precision numerics, and quantization, as these significantly impact RL scaling and cost. This is a research role with full-stack ownership, from algorithms to training run health.

$350k - $475k

d-Matrix is seeking a Senior Staff ML Researcher to join our Algorithms team and develop new methods for running large language models efficiently on our DNN accelerators. This is a hands-on research role at the intersection of machine learning, applied mathematics, numerical computing, and AI hardware. You will invent, evaluate, and implement algorithmic techniques that improve LLM inference performance while preserving model quality, with a focus on challenges such as numerical precision, model compression, memory efficiency, and efficient execution on accelerator hardware. You will work closely with mathematicians, ML researchers, ML engineers, compiler engineers, and hardware architects to translate research ideas into practical solutions for cutting-edge generative AI workloads.

$175k - $265k

Deepgram is seeking an Embedded AI Engineer to work on optimizing their speech models for a wide range of hardware, including non-NVIDIA accelerators, embedded SoCs, mobile processors, and specialized devices with tight resource constraints. This role operates at the lowest layer of the edge stack, focusing on writing and optimizing custom kernels and operators, collapsing models onto device-specific execution units, and performing target-side quantization and assembly-level tuning. The engineer will collaborate with Applied ML Engineers to ensure Deepgram's models can run efficiently on new hardware platforms, making them viable for edge deployment. This position is ideal for senior embedded engineers with a passion for AI or staff-level engineers looking to shape the future of on-device AI model deployment.

$219k - $274k

At Mach9, ML Engineers build the perception models at the core of our AI-enabled CAD system, extracting 3D object and line features from dense LiDAR point clouds and imagery. This role is research-driven and product-focused, involving the design and training of models for image and 3D detection and localization. You will work end-to-end from research prototype to production feature, partnering closely with infrastructure and product teams to deploy capabilities. This position is ideal for early-to-mid-career ML engineers who excel at end-to-end ownership and can transition smoothly from dissecting research papers to shipping product features.

$180k - $300k

The AI Infrastructure team at Zensors builds the engine that powers our visual sensing platform, providing tools to automate the entire AI workflow from model development to monitoring. As a Machine Learning Engineer, you will focus on developing technologies to accelerate the training and inference of computer vision models, crucial for smart spaces and cities. This role involves optimizing core ML pipelines, collaborating across teams, and applying advanced model optimization techniques to enhance performance and reduce costs.

At Bland.com, we are building the models and infrastructure that make AI phone agent interactions feel natural, reliable, and genuinely human. We are a fast-growing company that has raised significant funding from leading investors. Voice is rapidly becoming the primary interface between businesses and their customers, and we are at the forefront of reimagining these interactions at scale. Our mission is to empower enterprises to build AI phone agents that are indistinguishable from human agents.

$160k - $280k