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Staff Machine Learning Scientist Jobs

7,216 active opportunities · Updated for October 2026

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Explore current staff machine learning scientist jobs. Use filters to narrow by work mode, employment type, experience and date posted.

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Perplexity
📍 San Francisco• Full-time• $220K – $405K/yr
5mo ago

In 2026, we launched Computer, the defining product for the new era of agentic AI. Millions of people now use Perplexity to transform knowledge into action, and every action an agent takes is metered, budgeted, and settled through the billing platform this role owns. As a monetization engineer at Perplexity, you'll own the abstractions that let product teams ship new SKUs, run pricing experiments, and convert users into paying customers, without needing to understand billing internals. The usage-based billing system this team owns is foundational to Perplexity Computer and our agentic products: metering every agent action in real time, enforcing credit budgets, and settling costs across entirely new interaction models. You'll work across subscriptions, usage-based billing, and enterprise contracts to ensure every revenue path is reliable, observable, and easy to extend. Tech Stack: Python | Go | Stripe | PostgreSQL | AWS | Docker Why Perplexity is Different Craftsmanship. We build high quality, tasteful products targeting both the AI native and AI curious. Ownership. You identify the problem, design the solution and ship it. Entrepreneurship. We think like founders, act with urgency, and hustle to deliver for each other and our users. Scholarship. Work among highly talented peers, pursuing knowledge and truth, upleveling ourselves, our teams, and our products. Partnership. We amplify each others' strengths, break down silos, and give selflessly to help our colleagues deliver excellence. What you'll do Design, build, and own the billing platform and monetization systems that power Computer and every paid experience across Perplexity. Lead features end-to-end, from problem definition through technical design, implementation, and launch, including the billing API abstractions that let product teams ship new SKUs, pricing models, and monetization experiments with minimal friction. Build and operate the subscription, invoicing, and usage-based billing systems that serve

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Perplexity
📍 San Francisco• Full-time• $220K – $405K/yr
5mo ago

By applying to this role, you will be considered for engineering roles across all teams at Perplexity. We are hiring builders to join our highly leveraged engineering team for creating new products that innovate and accelerate human productivity In 2026, we launched Computer, the defining product for the new era of agentic AI. We’ve scaled beyond the millions of people using Perplexity every day for research, shopping, investing and curiosity into a new paradigm of using AI to transform knowledge into action. As an engineer at Perplexity, your role will be to build products and systems that define how AI empowers humans to think, decide and act. You’ll ship fast and work between product, infrastructure and frontier level advancements in technology. Why Perplexity is Different Craftsmanship. We build high quality, tasteful products targeting both the AI native and AI curious. Ownership. You identify the problem, design the solution and ship it. Entrepreneurship. We think like founders, act with urgency, and hustle to deliver for each other and our users. Scholarship. Work among highly talented peers, pursuing knowledge and truth, upleveling ourselves, our teams, and our products. Partnership. We amplify each others’ strengths, break down silos, and give selflessly to help our colleagues deliver excellence. What you'll do Design, build, and own product and platform systems for Computer Lead features, projects and products end-to-end, from problem definition to technical design, implementation, and launch. Hill climb on hard problems, continuously iterating to improve for ourselves and customers. Partner closely with engineers, product managers, designers, data scientists, and go-to-market teams. Build systems that take into account the nuances of AI, working with agents, context, evaluation, personalization and the ground truth. Qualifications 4+ years of professional software engineering experience. Strong experience in at least one general-purpose programming langua

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Modal
📍 New York• Full-time• $200K – $350K/yr
6mo ago

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. Our team includes creators of popular open-source projects (e.g., Seaborn , Luigi ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We are looking for strong engineers with experience in making ML systems performant at scale. If you are interested in contributing to open-source projects and Modal’s container runtime to push language and diffusion models towards higher throughput and lower latency, we’d love to hear from you! Requirements: 5+ years of experience writing high-quality, high-performance code. Experience working with torch, high-level ML frameworks, and inference engines (vLLM or TensorRT). Familiarity with Nvidia GPU architecture and CUDA. Experience with ML performance engineering (tell us a story about boosting GPU performance — debugging SM occupancy issues, rewriting an algorithm to be compute-bound, eliminating host overhead, etc). Nice-to-have: familiarity with low-level operating system foundations (Linux kernel, file systems, containers, etc).

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Micron
📍 Taichung - Fab 16, Taiwan• Full-time
6mo ago

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Responsibilities and Tasks: Drive best-in-class product maturity which includes bits per wafers (yield), product grades (Repair Density and DPM) at the fastest speed and cycle of learning. In depth knowledge of processes across different loops or functions (FEOL, MOL, CELL, BEOL) to identify best optimum process integration solution to achieve the goal, knowledge on product and circuit design will be plus. Collaborate with YE, Device, RDA, Metrology team to resolve top yield issues, develop inline visibility to enable fast yield ramp and minimize excursion. Identify best known method and business process from DRAM/NAND sites and drive for alignment and standardize across network. Travel to Micron sites as necessary for face to face collaboration. About Micron Technology, Inc. We are an industry leader in innovative memory and storage solutions transforming how the world uses information to enrich life for all . With a relentless focus on our customers, technology leadership, and manufacturing and operational excellence, Micron delivers a rich portfolio of high-performance DRAM, NAND, and NOR memory and storage products through our Micron® and Crucial® brands. Every day, the innovations tha

artificial intelligenceairecruitment
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We are looking for an AI Infra engineer to join our growing team. We work with Kubernetes, Slurm, Python, C++, PyTorch, and primarily on AWS. As an AI Infrastructure Engineer, you will be partnering closely with our Inference and Research teams to build, deploy, and optimize our large-scale AI training and inference clusters. Responsibilities Design, deploy, and maintain scalable Kubernetes clusters for AI model inference and training workloads Manage and optimize Slurm-based HPC environments for distributed training of large language models Develop robust APIs and orchestration systems for both training pipelines and inference services Implement resource scheduling and job management systems across heterogeneous compute environments Benchmark system performance, diagnose bottlenecks, and implement improvements across both training and inference infrastructure Build monitoring, alerting, and observability solutions tailored to ML workloads running on Kubernetes and Slurm Respond swiftly to system outages and collaborate across teams to maintain high uptime for critical training runs and inference services Optimize cluster utilization and implement autoscaling strategies for dynamic workload demands Qualifications Strong expertise in Kubernetes administration, including custom resource definitions, operators, and cluster management Hands-on experience with Slurm workload management, including job scheduling, resource allocation, and cluster optimization Experience with deploying and managing distributed training systems at scale Deep understanding of container orchestration and distributed systems architecture High level familiarity with LLM architecture and training processes (Multi-Head Attention, Multi/Grouped-Query, distributed training strategies) Experience managing GPU clusters and optimizing compute resource utilization Required Skills Expert-level Kubernetes administration and YAML configuration management Proficiency with Slurm job scheduling, resource mana

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Perplexity
📍 San Francisco• Full-time• $220K – $405K/yr
6mo ago

We are looking for an AI Infra engineer to join our growing team. We work with Kubernetes, Slurm, Python, C++, PyTorch, and primarily on AWS. As an AI Infrastructure Engineer, you will be partnering closely with our Inference and Research teams to build, deploy, and optimize our large-scale AI training and inference clusters Responsibilities Design, deploy, and maintain scalable Kubernetes clusters for AI model inference and training workloads Manage and optimize Slurm-based HPC environments for distributed training of large language models Develop robust APIs and orchestration systems for both training pipelines and inference services Implement resource scheduling and job management systems across heterogeneous compute environments Benchmark system performance, diagnose bottlenecks, and implement improvements across both training and inference infrastructure Build monitoring, alerting, and observability solutions tailored to ML workloads running on Kubernetes and Slurm Respond swiftly to system outages and collaborate across teams to maintain high uptime for critical training runs and inference services Optimize cluster utilization and implement autoscaling strategies for dynamic workload demands Qualifications Strong expertise in Kubernetes administration, including custom resource definitions, operators, and cluster management Hands-on experience with Slurm workload management, including job scheduling, resource allocation, and cluster optimization Experience with deploying and managing distributed training systems at scale Deep understanding of container orchestration and distributed systems architecture High level familiarity with LLM architecture and training processes (Multi-Head Attention, Multi/Grouped-Query, distributed training strategies) Experience managing GPU clusters and optimizing compute resource utilization Required Skills Expert-level Kubernetes administration and YAML configuration management Proficiency with Slurm job scheduling, resource manag

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Perplexity
📍 San Francisco• Full-time• $220K – $485K/yr
6mo ago

We build and run the inference engine behind every Perplexity query and deploy dozens of model architectures at scale with tight latency and cost budgets. Our stack is Rust, Python, CUDA, and CuTe DSL - and we need another engineer to join us. What you will work on Examples of real work the team does: New models support. Support transformer-based retrieval, text-generation, and multimodal models in our inference infrastructure, from weight loading, request scheduling and KV-cache management to support in API Gateway. GPU kernels migration to CuTe DSL. Port our in-house CUDA kernels to NVIDIA's CuTe DSL so they run on GB200 today and are portable to Vera Rubin racks tomorrow. Rust-native serving runtime. Develop our internal Rust-based inference server to solve all Python pains and keep up with rapidly growing traffic. Performance optimisation. Profile and fix bottlenecks from network ingress through continuous batching and GPU kernel interleaving. Reliability and observability. Build dashboards, alerts, and automated remediation so we catch regressions before users do. Respond to and learn from production incidents. Who we're looking for Deep experience with GPU programming and performance work (CUDA, Triton, CUTLASS, or similar). Any other deep systems programming experience is a plus. You understand modern LLM architectures and are able to bring them up reliably in a production environment. You've built and operated production distributed systems under real load - ideally performance-critical ones. Comfortable working across languages and layers: Rust for the serving runtime, Python for model code, CUDA/CuteDSL for kernels. You own problems end-to-end. You can read a research paper on Monday, write a kernel on Wednesday, and debug a production incident on Friday. Self-directed. You do well in fast-moving environments where the path forward isn't laid out for you. Good if you touched any of ML compilers and framework internals: PyTorch internals, torch.compile, cus

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We are looking for an AI Inference Engineer to join our growing team. We build and run the inference engine behind every Perplexity query and deploy dozens of model architectures at scale with tight latency and cost budgets. Our stack is Rust, Python, CUDA, and CuTe DSL. Responsibilities: New models support. Support transformer-based retrieval, text-generation, and multimodal models in our inference infrastructure, from weight loading, request scheduling and KV-cache management to support in API Gateway. GPU kernels migration to CuTe DSL. Port our in-house CUDA kernels to NVIDIA's CuTe DSL so they run on GB200 today and are portable to Vera Rubin racks tomorrow. Rust-native serving runtime. Develop our internal Rust-based inference server to solve all Python pains and keep up with rapidly growing traffic. Performance optimisation. Profile and fix bottlenecks from network ingress through continuous batching and GPU kernels interleaving. Reliability and observability. Build dashboards, alerts, and automated remediation so we catch regressions before users do. Respond to and learn from production incidents. Who we're looking for: Deep experience with GPU programming and performance work (CUDA, Triton, CUTLASS, or similar). Any other deep systems programming experience is a plus. You understand modern LLM architectures and are able to bring them up reliably in a production environment. You've built and operated production distributed systems under real load - ideally performance-critical ones. Comfortable working across languages and layers: Rust for the serving runtime, Python for model code, CUDA/CuteDSL for kernels. You own problems end-to-end. You can read a research paper on Monday, write a kernel on Wednesday, and debug a production incident on Friday. Self-directed. You do well in fast-moving environments where the path forward isn't laid out for you. Nice-to-have: ML compilers and framework internals: PyTorch internals, torch.compile, custom operators. Distribut

pythonkubernetesai
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Our vision is to transform how the world uses information to enrich life for all. Join an inclusive team passionate about one thing: using their expertise in the relentless pursuit of innovation for customers and partners. The solutions we build help make everything from virtual reality experiences to breakthroughs in neural networks possible. We do it all while committing to integrity, sustainability, and giving back to our communities. Because doing so can fuel the very innovation we are pursuing. Our vision is to transform how the world uses information to enrich life for all. Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Position Summary The Distinguished Member of Technical Staff (DMTS) in Process Development for Advanced Thin Film serves as a recognized expert both within and outside of Micron. This position is pivotal in shaping the technical vision for NAND structural and electrical film processes, with influence that spans top-level organizational boundaries. The DMTS leads programs that impact the entire engineering group, drives breakthrough innovations, and plays a key role in influencing industry-wide and cross-disciplinary teams. Additionally, the DMTS<sp

artificial intelligenceairecruitment
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Our vision is to transform how the world uses information to enrich life for all. Join an inclusive team passionate about one thing: using their expertise in the relentless pursuit of innovation for customers and partners. The solutions we build help make everything from virtual reality experiences to breakthroughs in neural networks possible. We do it all while committing to integrity, sustainability, and giving back to our communities. Because doing so can fuel the very innovation we are pursuing. Our vision is to transform how the world uses information to enrich life for all. Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Position Overview Acts as a technical authority in 3D NAND Advanced thin film development, setting strategic direction and leading multi-functional initiatives. Drives department-wide impact by architecting solutions, accelerating innovation adoption, and influencing technical standards. Engages in global projects and mentors engineers to elevate technical excellence. Key Responsibilities Define technical strategy and lead multi-functional projects in structural and electric film development. <span

artificial intelligenceairecruitment
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Our vision is to transform how the world uses information to enrich life for all. Join an inclusive team passionate about one thing: using their expertise in the relentless pursuit of innovation for customers and partners. The solutions we build help make everything from virtual reality experiences to breakthroughs in neural networks possible. We do it all while committing to integrity, sustainability, and giving back to our communities. Because doing so can fuel the very innovation we are pursuing. Our vision is to transform how the world uses information to enrich life for all. Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Position Overview The Member of Technical Staff (MTS) in Process Development for Advanced Thin Film plays a critical role in advancing thin film process development for NAND memory technology. This position is responsible for performing experiments, conducting material characterization, and providing support for process integration and fixing. As a key contributor, the MTS collaborates with senior engineers and Multi-functional teams to promote manufacturability, continuous improvement, and ongoing technology advancement within the organization. Key Responsibilities</span

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Perplexity
📍 San Francisco• Full-time• Remote• $220K – $405K/yr
6mo ago

Perplexity is seeking a highly skilled, experienced and hands-on Offensive Security Engineer to join our dynamic security team, taking an adversarial approach to hardening Perplexity's infrastructure, applications, and AI systems. You'll plan and execute red team operations, penetration tests, and attack simulations across our cloud infrastructure, web and mobile applications, AI/ML pipeline, and corporate environment—finding real vulnerabilities before adversaries do and working directly with engineering teams to drive remediation. Responsibilities Plan and execute red team and purple team engagements simulating advanced threat actors across cloud infrastructure (AWS, Kubernetes), endpoints, and application surfaces Conduct continuous penetration testing of web applications, APIs, mobile clients, browser extensions, cloud infrastructure, and internal services Assess AI/ML-specific attack surfaces including prompt injection, model exfiltration, agent abuse, tool-use exploitation, and MCP security boundaries Develop and maintain custom offensive tooling, exploits, and automation to improve the efficiency and coverage of security testing Perform open-scope adversary simulations that test detection and response capabilities end to end, collaborating closely with the defensive security team Drive threat modeling sessions with engineering teams to identify and prioritize attack vectors in new features and architectures Deliver clear, actionable findings to both technical and executive audiences; partner with engineering to validate remediations Contribute to the security of CI/CD pipelines, supply chain integrity, and secrets management through offensive assessment Stay current on emerging attack techniques, vulnerability research, and adversary tradecraft; bring external perspective into Perplexity's security strategy Qualifications 5+ years of hands-on experience in offensive security, red teaming, or penetration testing Deep technical expertise in at least two of: clo

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Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Join Micron's world-class team as a Global Facilities North Asia Regional Chemical Engineer! This outstanding opportunity allows you to lead business process alignment in design, construction project composition, management, schedule, cost control, testing & commissioning, and operational and maintenance programs for chemical & slurry systems across our manufacturing sites. Your role will be pivotal in ensuring our facilities run flawlessly, maintaining our competitive edge in the industry. Key Responsibilities Project Design and Construct and develop regional greenfield projects aligned with global standards. Collaborate with central sustainability, cost, construction, and line planning teams. Offer engineering assistance for site projects and sustainability efforts. Review and approve site capacity expansion and capital expenditures. Make decisions based on business needs for Facilities Reliability Improvement project capital expenditures. Reliability Support site system improvement projects, including system reliability improvements, quality enhancement, and equipment end-of-life replacements. Coordinate regional efforts and identify strategic program alignment opportunities (e.g., BCP, Critical Spec, Quality Defense Line). Offer engineering assistance for significant SIPP evaluations. Share lessons learned from regional events and influence the development of glob

artificial intelligenceaiproject management
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SpaceXSI
📍 Palo Alto• $180K – $440K/yr
7mo ago

SpaceX was founded under the belief that a future where humanity is out exploring the stars is fundamentally more exciting than one where we are not. Today, SpaceX is actively developing the technologies to make this possible, with the ultimate goal of making life multiplanetary and expanding consciousness to the stars. SpaceXSI is building Super Intelligence to help humanity understand the universe. Our teams are building the full Super Intelligence stack: from our Colossus supercomputers, to Grok models, to our suite of applications, including Grok Bot, Grok Build, Grok Imagine, Grok Voice, and X. We're creating a powerful flywheel where more compute trains better models, better models power more useful products, and what we learn from people using those products shapes what we build next. ABOUT THE ROLE: You will join the Grok Main Product team, responsible for the user-facing chat portal at grok.com and related experiences. We build highly scalable frontends, APIs, and features that handle tens of thousands of queries per second. Our focus is delivering the best possible chat interface—seamless, intuitive, and maximally useful—to turn Grok into an essential "everything app" that amplifies human productivity across any domain. Help build the portal that lets users accomplish anything: ask questions, create slide decks, solve puzzles, or tackle real work in engineering, law, medicine, and beyond. We're creating an easy-to-use experience that works flawlessly, driving a 10x increase in what knowledge workers can achieve. No prior AI experience required—just sharp thinking, relentless execution, and passion for AI that redefines what's possible. Own end-to-end features that delight millions, collaborating closely with model and research teams to ship breakthroughs at pace. RESPONSIBILITIES: Design and deliver polished, scalable user-facing features and APIs for Grok's chat experience. Innovate on frameworks for rapid experimentation to iterate quickly and keep Grok

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Perplexity
📍 San Francisco• Full-time• $175K – $330K/yr
8mo ago

Perplexity is AI for people who expect more. This role brings that standard to how we understand our users, shape our product, and decide what to build next. We're looking for a data scientist who can turn product questions into clear decisions. You'll work across product, engineering, growth, design, and user research to understand user behavior, define metrics, design experiments, and identify the highest-leverage opportunities for the company. The data team is AI-native by default. We use AI to accelerate analysis, write and review code, explore hypotheses, document data, generate first drafts, and automate recurring workflows. But the core of the role is still judgment: asking the right question, choosing the right metric, designing the right test, and knowing when the answer is strong enough to act on. What You'll Do Develop product insights - analyze user behavior to inform product roadmap, accelerate adoption, and identify opportunities to improve the user experience. Design and analyze experiments - form hypotheses, define success metrics, run A/B tests, interpret results, and turn findings into product recommendations. Define the metrics that matter - build the metrics, guardrails, dashboards, and reporting workflows that help teams understand product and company health. Partner across functions - work closely with engineering, product, growth, design, and user research to answer ambiguous questions and drive decisions. Build reusable data assets - create tables, models, and documentation that make analysis faster, more consistent, and easier for humans and AI systems to use. Use AI to scale data science - automate recurring analysis, build AI-assisted workflows, improve documentation, and turn one-off investigations into repeatable systems. Tell the story clearly - communicate findings, assumptions, uncertainty, and recommendations in a way that helps teams make decisions. What We're Looking For 6+ years of experience as a data scientist or closely related

pythonsqlai
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