Algorithm Engineer Jobs

Role Overview As a Systems Research Engineer Intern specialized in GPU Programming, you will play a crucial role in developing and optimizing GPU-accelerated kernels and algorithms for ML/AI applications. Working closely with the modeling and algorithm team, you will co-design GPU kernels and model architecture to enhance the performance and efficiency of our AI systems. Collaborating with the hardware and software teams, you will contribute to the co-design of efficient GPU architectures and programming models, leveraging your expertise in GPU programming and parallel computing. Your research skills will be vital in staying up-to-date with the latest advancements in GPU programming techniques, ensuring that our AI infrastructure remains at the forefront of innovation. Responsibilities Optimize and fine-tune GPU code to achieve better performance and scalability Collaborate with cross-functional teams to integrate GPU-accelerated solutions into existing software systems Stay up-to-date with the latest advancements in GPU programming techniques and technologies Requirements Strong background in GPU programming and parallel computing, such as CUDA and/or Triton. Knowledge of ML/AI applications and models Knowledge of performance profiling and optimization tools for GPU programming Excellent problem-solving and analytical skills About Together AI Together AI, the AI Native Cloud, is purpose-built for AI engineers. AI application developers get high-performance inference that scales reliably, fine-tuning and reinforcement learning for creating frontier-level specialized models, and pre-training at massive scale for fully custom intelligence, all around a marketplace of leading open models that teams can run, adapt, and own. Trusted by Cursor, Decagon, ElevenLabs, Salesforce, and Zoom, Together serves 400+ trillion tokens a month. Internship Program Details: Our internship program runs 12 to 14 weeks, giving you the opportunity to work alongside industry-leading en

About Mach Industries Founded in 2023, Mach Industries is a rapidly growing defense technology company focused on developing next-generation autonomous defense platforms. At the core of our mission is the commitment to delivering scalable, decentralized defense systems that enhance the strategic capabilities of the United States and its allies. With a workforce of approximately 350 employees, we operate with startup agility and ambition. Our vision is to redefine the future of warfare through cutting-edge manufacturing, innovation at speed, and unwavering focus on national security. We are dedicated to solving the next generation of warfare with lethal systems that deter kinetic conflict and protect global security. The Role The Sr Embedded Software Engineer - Radar & DSP will play a key role in developing advanced RF sensing capabilities for Mach’s autonomous defense platforms. You will be responsible for designing, implementing, and optimizing radar software across the full development lifecycle; from algorithm prototyping to embedded deployment. This role involves close collaboration with cross-functional teams to ensure high-performance, low-latency radar systems that meet mission-critical requirements. Success in this role requires strong technical execution, adaptability, and a hands-on approach in a fast-paced, iterative environment. Key Responsibilities Develop, test, and implement radar software for RF sensing technologies ensuring high performance and reliability. Build next generation counter UAV systems through hands on application of radar defense systems to defend human lives, critical infrastructure, and high value assets for the United States and its allies Design and implement efficient, well-tested code in C++, Python or C. Work closely with other engineers to ensure seamless hardware-software integration. Develop and maintain signal processing algorithms tailored for RF sensing systems, ensuring real-time performance and low-latency

The Core Data Science team builds the products and data assets that let teams across Zoox measure and improve the autonomy and operational performance of our fleet. In this role, you'll focus on fleet simulation — the environment our data teams use to develop, test, and evaluate the algorithms that orchestrate our autonomous fleet (dispatch, routing, and vehicle assignment) and to understand how those algorithms perform before they reach the road. You’ll piece together the constituent components into a coherent, easy-to-use simulation environment, filling in the gaps, and building generalizable mechanisms so data scientists can measure their algorithm's impact on fleet efficiency. You'll join a diverse, experienced team with rapidly growing scope while working with one of the industry's most valuable autonomous vehicle datasets. In this role, you will: Turn existing fleet-simulation components into a coherent, self-service environment that data scientists and ML engineers can run without deep software expertise. Fill gaps and build the connective tissue between simulation, data, and fleet-orchestration algorithms. Build generalizable mechanisms that let teams measure how their orchestration algorithms affect fleet efficiency. Collaborate with data science, ML, and fleet-orchestration teams to shape and prioritize the simulation roadmap. Establish best practices and processes around simulation, evaluation, and data-driven decision-making. Qualifications Software development experience in a production environment, with fluency in Python; or demonstrated experience learning new programming languages. Experience building tools, services, or frameworks that make complex systems usable by non-specialist users. Familiarity with any version control system, with preference for Git. Experience designing metrics and building mechanisms that deliver robust, actionable insights. Good communi

About the Role As a Systems Research Engineer specialized in GPU Programming, you will play a crucial role in developing and optimizing GPU-accelerated kernels and algorithms for ML/AI applications. Working closely with the modeling and algorithm team, you will co-design GPU kernels and model architecture to enhance the performance and efficiency of our AI systems. Collaborating with the hardware and software teams, you will contribute to the co-design of efficient GPU architectures and programming models, leveraging your expertise in GPU programming and parallel computing. Your research skills will be vital in staying up-to-date with the latest advancements in GPU programming techniques, ensuring that our AI infrastructure remains at the forefront of innovation. Requirements Strong background in GPU programming and parallel computing, such as CUDA and/or Triton. Knowledge of ML/AI applications and models Knowledge of performance profiling and optimization tools for GPU programming Excellent problem-solving and analytical skills Bachelor's, Master's, or Ph.D. degree in Computer Science, Electrical Engineering, or equivalent practical experiences Responsibilities Optimize and fine-tune GPU code to achieve better performance and scalability Collaborate with cross-functional teams to integrate GPU-accelerated solutions into existing software systems Stay up-to-date with the latest advancements in GPU programming techniques and technologies About Together AI Together AI, the AI Native Cloud, is purpose-built for AI engineers. AI application developers get high-performance inference that scales reliably, fine-tuning and reinforcement learning for creating frontier-level specialized models, and pre-training at massive scale for fully custom intelligence, all around a marketplace of leading open models that teams can run, adapt, and own. Trusted by Cursor, Decagon, ElevenLabs, Salesforce, and Zoom, Together serves 400+ trillion tokens a month. Compensation We offer competi

Description: Graviton Research Capital LLP, Gurgaon is looking to hire Software Engineers for our Core Technology team which has some of the best programmers in India working on cutting edge technologies to build a super fast and robust trading infrastructure handling millions of dollars worth of trading transactions every day. As a Senior Software Engineer with Graviton your responsibilities will include: Designing and implementing a high-frequency automated trading system, that trades on multiple exchanges Building live reporting and administration tools for the trading system Performance optimization and improving the overall latency of systems, through algorithm research and using cutting edge tools and techniques End-to-end ownership of modules, including designing, development, deployment and support Growing the team through involvement in the regular hiring process and occasional campus recruitments Requirements : The ideal requirements for our candidates are: A degree in Computer Science 3-5 yrs Experience with C/C++ and object-oriented programming Experience in HFT industry Expertise in algorithms and data structures Excellent problem solving skills Strong communication skills A working knowledge of Linux systems Any of the following is a plus: A good understanding of TCP/IP and Ethernet Knowledge of any other programming language e.g. Java, Scala, Python, bash, Lisp, etc. Familiarity with parallel programming models and parallel algorithms Experience with big data environments e.g. Hadoop, Spark etc. Benefits: Our open and collaborative work culture gives you the freedom to innovate and experiment. Our cubicle free offices, non-hierarchical work culture and insistence to hire the very best creates a melting pot for great ideas and technological innovations. Everyone on the team is approachable, there is nothing better than working with friends! Our perks have you covered. Competitive compensation Annual international team outing Fully covered commuti

Job Title Senior Software Engineer - Image Reconstruction (C++/CUDA) Job Description Build the GPU-native engine that turns raw CT physics into life-saving images inside Philips scanners worldwide , wringing maximum performance from constrained hardware at the frontier of C&#43;&#43;, CUDA, and AI alongside world-class physicists. Your role: Help r e-architect an entire CT image-reconstruction pipeline, from raw detector physics to the final clinical image, as a fully GPU-native, massively scalable platform in C&#43;&#43; and CUDA. Work shoulder-to-shoulder with physicists, algorithm architects, and platform engineers, translating complex signal and image-processing models into high-performance GPU implementations that balance image quality against compute cost. Collaborate with CT platform teams around the globe to design, build, test, and deploy an industry-leading reconstruction software platform. Push the frontier of performance engineering and applied AI by profiling, parallelizing, optimizing memory use across caches and shared memory, and pioneering learned models that replace expensive physics with fast, accurate equivalents. This hybrid role is based in Cleveland, OH, with three flexible days in the office and two remote days each week . Regular travel is not typically </sp

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. As a Modeling Industrial Engineer, you will be responsible for 1. Capacity Model Optimization with AI enablement (Copilot / Claude and Etc): 1)Ensure accurate capacity model through periodic audits and validation of workstation performance, capital asset utilization (CAU), and cycle time using static and dynamic models. 2. Responsibilities and Tasks : 1)Ensure tool capacity is well positioned to meet output requirements at the manufacturing area levels. 2)Review capacity modeling accuracy and make sure without any surprise after IE bottom-up estimation. 3)Develop tool productivity algorithm by tool motion study and CEID data analysis. 4)Understand the impact to the driven by output changes through scenario analysis. 5)Work closely with APTD, PDE and APE to analyze &#34;Plan-to-Actual performance&#34; by using statistical methodology and propose the mitigation plan to close the gap. 6)Work with engineering team and partner with ATCP(Assembly Test Central Planning) to understand and close the gaps by workstation performance to meet external benchmark levels. 7)Understand individual area’s Entitled Cycle Time (ECT) for a given scenarios. 3. CIP Project with AI enablement (Copilot / Claude and Etc) : Lead the continuously improvement project to optimize the workflow as well as capacity management with AI proficiency or AI‑enabled ways of working where applicable ( Leveraging Ar

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Reinforcement learning is how Claude learns to reason, write code, and act autonomously over long horizons. The RL Scaling team works on how RL scales: what happens to throughput, stability, and learning efficiency as models get larger, episodes get longer, and compute grows by orders of magnitude, and what has to change in our algorithms and systems to keep getting returns from that scale. This role sits squarely across research and engineering. You'll develop next-generation architectures and RL algorithms, take them from a small-scale result to a frontier-scale run, and understand every place they behave differently along the way. You'll build the systems that set how fast the team can iterate: how many experiments, at what scale, and how quickly we can trust the results. And you'll work on Anthropic's largest and fastest RL runs, where the gap between a good idea and a working one is often a problem no one has solved yet. Key responsibilities Study how RL training and sampling scale with model size, context length, and compute, and find the algorithmic and systems changes that keep scaling efficient Develop next-generation model architectures and RL algorithms, and make them run efficiently at frontier scale Take promising small-scale results to frontier-scale runs, and diagnose why they behave differently when they get there, whether the cause is numerical, algorithmic, or systemic Build the experimental infrastructure that sets research velocity: fast, reproducible comparisons of architecture and algorithm variants at meaningful scale Own end-to-end performance of our largest RL runs, from research code down to th

The Collision Avoidance System (CAS) is responsible for detecting and reacting to imminent collision situations in support of our vehicle’s overall safety goals. CAS Perception is responsible for processing raw sensor data from our vehicle’s world-class sensor suite using a combination of geometric, interpretable algorithms and deep learning to detect near-collisions with obstacles along our intended driving path, in the most challenging dense urban environments and under tight compute resource constraints. Overall CAS is parallel and complementary to our Main Artificial Intelligence (AI) autonomy stack, and has a close relationship with our vehicle hardware and safety teams in order to architect redundancy into our overall driving system. The CAS Verification & Validation (CAS V&V) is a multidisciplinary team data, software and systems engineers defining and building metrics to measure the Collision Avoidance System performance and work with the Systems Design and Mission Assurance (SDMA) and QA teams to develop validation plans for the features. In this role, you will: Apply distributed computing algorithms to analyze petabytes of urban driving data. Develop metrics and tools to analyze errors and system improvements. Work closely with CAS engineers to evaluate system performance. Collaborate with Perception engineers to define metrics for autonomous driving. Partner with Planning engineers to measure performance in complex urban environments. Qualifications: BS, MS, or PhD degree in computer science or a related field Fluency in C++ and/or Python Extensive experience with programming and algorithm design Bonus Qualifications: Experience with analysis of latency for safety-critical software systems Experience with petabyte-scale distributed computing (Spark, Databricks, generic MapReduce pipelines) <li

About Mach Industries Founded in 2023, Mach Industries is a rapidly growing defense technology company focused on developing next-generation autonomous defense platforms. At the core of our mission is the commitment to delivering scalable, decentralized defense systems that enhance the strategic capabilities of the United States and its allies. With a workforce of approximately 350 employees, we operate with startup agility and ambition. Our vision is to redefine the future of warfare through cutting-edge manufacturing, innovation at speed, and unwavering focus on national security. We are dedicated to solving the next generation of warfare with lethal systems that deter kinetic conflict and protect global security. The Role The Sr Embedded DSP Engineer, High Performance Signal Processing will play a key role in developing advanced RF sensing capabilities for Mach’s autonomous defense platforms. Working on the DART team, you will focus directly on next-generation counter-UAV radar systems and RF seekers. You will design radar signal-processing algorithms and implement them as high-performance, low-latency embedded software on high performance processors. You will own capabilities across the full development lifecycle - from mathematical modeling and algorithm prototyping and implementation on high performance processing cores, performance optimization, hardware integration, and system-level validation. This role involves close collaboration with RF, FPGA, hardware, GNC engineers to ensure the successful development of high-performance, low-latency radar systems that meet mission-critical requirements. Success in this role requires strong technical execution, adaptability and expertise in signal processing theory, low level C and hands-on experience optimizing real-time processing pipelines in a fast-paced, iterative, start-up environment. Key Responsibilities Mission: Build next generation counter-UAV defense systems that will be used to defend human lives

About Mach Industries Founded in 2023, Mach Industries is a rapidly growing defense technology company focused on developing next-generation autonomous defense platforms. At the core of our mission is the commitment to delivering scalable, decentralized defense systems that enhance the strategic capabilities of the United States and its allies. With a workforce of approximately 350 employees, we operate with startup agility and ambition. Our vision is to redefine the future of warfare through cutting-edge manufacturing, innovation at speed, and unwavering focus on national security. We are dedicated to solving the next generation of warfare with lethal systems that deter kinetic conflict and protect global security. The Role Build the next generation of navigation systems for unmanned aerial vehicles. Mach is looking to build a tightly coupled navigation system to fuse GNSS, optical, and magnetic navigational aids to estimate vehicle pose. Key Responsibilities Develop sensor fusion algorithms to estimate pose of UAVs. Develop and integrate GNSS and LEO constellation navigational aids. Leverage optical techniques such as VIO to aid pose estimation. Characterize and integrate inertial sensors. Build algorithm validation tools and infrastructure. Required Qualifications Education: Bachelor's in Engineering, Physics, Mathematics. Experience: 1+ years of building and shipping Navigation solutions. Deep understanding of navigation sensors (i.e, IMU, GNSS receiver). Experience with modern software development tools (i.e, git, Jira). Experience with the implementation of embedded algorithms using C++. Experience with navigation error covariance propagation. Preferred Qualifications Experience with high altitude, monocular, SLAM. Experience with LEO constellation PNT. Experience with leveraging magnetometers for pose estimation. Experience with Aerospace systems. ITAR Requirements To conform to U.S. Government export regulations, applicant must be a (i) U.S. citizen or natio

Who We Are Nuro believes self-driving vehicles are the most immediate and profound opportunity for AI to drive positive change in the physical world. Safer streets, more time for what matters, and easier access to the world around us, that’s why we’re building a universal autonomy platform: self-driving for all roads and all rides. Founded in 2016, Nuro is a physical AI company developing Level 4 autonomous driving technology for a wide range of vehicles, use cases, and markets. Powered by the Nuro Driver™, our universal autonomy platform enables the global mobility ecosystem to deploy autonomy at scale, from robotaxis and logistics fleets to personal vehicles. With years of real-world deployment experience and a flexible, partner-led business model, Nuro is working toward a future where millions of autonomous vehicles powered by our technology help make everyday life safer, easier, and more connected. Nuro has raised over $2B in capital from Uber, NVIDIA, Google, Softbank, Fidelity, T. Rowe Price, and other leading investors. About the Role The ability to monitor and assist our vehicles remotely plays a key role in our business strategy. As a Software Engineer, Video Streaming you will work on our in-house Teleoperations platform. You will work with a diverse team of engineers to build the core communication system as well as the cloud platform to connect vehicles and operators. This position involves broad technical understanding in networking algorithms, bandwidth estimation, rate control, computer networking, and real-time communication systems. The team is expected to deliver reliable solutions and license to 3rd party teleoperation usages. About the Work Design and implement an efficient pipeline with state-of-the-art video streaming techniques to deliver high priority real-time data stream Build an offline streaming simulation/emulation framework that can help to iterate the video streaming algorithm and predict online performance Test systems in real-w

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. In the Technology Development — Advanced Modeling & AI Solutions (AMAIS) organization, you will be part of a multidisciplinary team developing next-generation Digital Twins, predictive modeling solutions, and AI-driven technologies that accelerate advanced memory development and manufacturing excellence. You will create predictive digital representations of semiconductor processes, materials, structures, equipment, and products across DRAM, NAND, and advanced packaging technologies including HBM. Leveraging physics-based modeling, computational methods, machine learning, GenAI, large language models (LLMs), and agentic AI frameworks, you will enable technology co-optimization, design-space exploration, process optimization, yield improvement, and accelerated technology learning. Working at the intersection of engineering fundamentals, manufacturing data, and digital engineering, you will develop scalable predictive and prescriptive solutions that connect process, structure, performance, yield, reliability, and cost. This role offers the opportunity to influence critical technology decisions, drive fab-technology co-optimization , and advance Micron's leadership in data-driven semiconductor memory innovation. Qualifications: Independence – be comfortable executing activities and needs Experience in algorithm development, numerical methods, and scientific computing Solid experience with Plasma, FPM, HAR etching, and MC modeling Experience with Wet Pr

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. RESPONSIBILITIES: Design, build, and implement a large-scale distributed system that powers one of the world's largest supercomputing clusters. Dive into the low-level stack to profile, debug, and optimize performance across diverse systems, including GPUs, Linux kernel, networking, and filesystems, to achieve peak efficiency. Collaborate on hardware, software, and algorithm co-design to push the boundaries of AI training. Maintain and innovate on our codebase to ensure scalability and reliability. Develop tools to enhance team productivity and streamline workflows. BASIC QUALIFICATIONS: Systems programming experience in C, C++, or Rust Computer systems fundamentals with a grasp of how computers execute code from transistors to high-level applications. Hands-on expertise with Kubernetes (K8s), including cluster architecture, pod lifecycle, networking (CNI), storage (CSI), service mesh, and production-grade operations PREFERRED SKILLS AND EXPERIENCE: Collaborate in a fast-paced, open environment to design and foundational systems. Strong debugging skills across the full stack — from kernel and OS up through container orchestration layers Deep knowledge of operating systems intern

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: As a Data Engineer in X product engineering team, you will play a key role in providing comprehensive data solutions that own or serve a wide range of stakeholders, including our end-users and internal teams such as Product engineering, Algorithm, Legal, Finance and Sales. Our work utilizes AI, distributed computing and hybrid storage technologies, but extends beyond purely data-centric solutions, encompassing non-data-related challenges, ultimately maximizing the potential of data for the benefit of our diverse user base. RESPONSIBILITIES: You'll help build and operate a distributed data platform that powers hundreds of realtime and batch pipelines processing billions of events per day. The team runs like an internal startup — we own problems end to end, from raw event streams to the datasets, tooling, and metrics that product, growth, safety, and business teams depend on daily. In this role you will: Design, build, and operate production-grade realtime and batch pipelines that ingest, process, validate, and deliver data powering user-behavior insights and product decisions. Create shared datasets, fact tables, and internal data products that let other teams ana