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Senior Ml Systems Engineer Jobs

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Explore current senior ml systems engineer jobs. Use filters to narrow by work mode, employment type, experience and date posted.

PG
PlayStation Global
📍 San Mateo, Canada• $215.6K – $274.6K/yr
18 days ago

Why Sony Interactive Entertainment? Sony Interactive Entertainment isn’t just the Best Place to Play — it’s also the Best Place to Work. Sony Interactive Entertainment (SIE) is the company behind the PlayStation brand. As a subsidiary of Sony Group Corporation, we’re part of a proud legacy of innovation and excellence. SIE is a dynamic technology company, delivering cutting-edge hardware and network services to more than 100 million people and an entertainment leader, home to some of the most beloved and recognizable intellectual properties (IP) in the world. Our role at SIE is to create and nurture the experiences under the PlayStation brand, a name synonymous with entertainment excellence and creativity. Senior Software Development Engineer in Test San Mateo, CA Role Overview Sony Interactive Entertainment LLC seeks a Senior Software Development Engineer in Test in San Mateo, CA to design, develop, and maintain automated testing frameworks and tools for PlayStation console and platform applications using both internal and external Python-based technologies. Requirements Master’s degree in Computer Science, Computer Engineering, or related field or equivalent, and two (2) years of experience in containerizing ML services and exploring Kubernetes-based deployments to support scalable service infrastructure; leveraging Amazon Web Services (AWS) technologies, including EC2, S3, and Lambda, to support model training, storage, and deployment workflows; implementing cloud-based ML infrastructure and monitoring solutions to improve system reliability and availability; utilizing Python and ML libraries including Scikitlearn and Pandas to build predictive models, perform data preprocessing and feature engineering, and generate analytical insights; applying supervised learning, anomaly detection, and optimization algorithms to support system tuning and predictive analytics; creating real-time ROI and analytics dashboards using Tableau to support data-driven decision-m

pythonawskubernetes
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Instacart
📍 Minnesota, United States• Full-time• Remote• $207K – $218.5K/yr
6mo ago

We're transforming the grocery industry At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers. Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table. Instacart is a Flex First team There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work. Overview: We are looking for a Senior Machine Learning Engineer with a strong Operations Research background to join the Service Availability & Routing team within Instacart's Logistics organization. In this role, you will work at the intersection of combinatorial optimization, mathematical programming, and AI to solve high-impact problems in the fulfillment space — including order batching, shopper routing, service availability prediction, and real-time assignment. You'll partner closely with engineering, product, and data science to ship models and algorithms that directly influence Instacart's profitability and shopper experience at scale. The Logistics & ML group is responsible for the intelligence and execution behind Instacart’s fulfillment system. The team optimizes a multi-sided marketplace to ensure customers get their orders on-time and in high qu

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About the Role Together AI is building the AI Native Cloud, an end-to-end platform for the full generative AI lifecycle, combining the fastest LLM inference engine with state-of-the-art GPU cloud infrastructure. The Together Cloud team builds the [Together GPU Clusters](https://www.together.ai/gpu-clusters) flagship IaaS product that provides high-performance, AI-ready GPU clusters through a self-serve cloud console, along with the virtualized infrastructure layer powering Together's inference, RL, and fine-tuning products. As a Senior Software Engineer focusing on AI Compute in the Together Cloud org, you will build and own major components of the next generation AI cloud platform – a highly available, global cloud infrastructure with cutting-edge virtualization of the latest ML hardware: GB300s/VRs, BlueField DPUs, InfiniBand and dual/quad-plane RoCEv2 fabrics. That virtualized computing platform powers our own SaaS products – inference, RL, and fine-tuning – and serves external cloud customers through self-serve offerings such as on-demand/reserved Kubernetes/Slurm clusters, across dozens of data centers and hundreds of thousands of GPUs. The hard problems in rapidly scaling heterogeneous GPU fleets are software problems: fully automated bootstrapping of GPU data centers, high-performance virtualization of GPU compute and DC networking without compromising isolation or portability, and fault-tolerant decentralized control planes. We solve them by building global and in-DC services, Kubernetes operators, and high-performance SDN libraries, forking hypervisors and Linux kernels, and building infra tailored to inference and fine-tuning. You'll own massive greenfield projects across their full lifecycle – scoping the problem and writing PRDs with our PMs, designing the system, and building it through to GA launch. Responsibilities Build the GPU and network virtualization stack: the hypervisor, kernel, and SDN work that makes GPU compute and DC networking high-perform

awsazuregcp
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R
Roblox
📍 San Mateo• Full-time• $259K – $311.4K/yr
11mo ago

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators. At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. With Roblox’s daily active users growing at a record pace, we are seeking experienced machine learning engineers who thrive on solving complex challenges and designing scalable, ground breaking solutions. In this role, you will develop deep learning-based models for performance advertising business. Your work will lay the foundation to deliver effective performance ads to our users, and more business values to our advertisers. You will build innovative machine-learning solutions to power ad ranking algorithms, and personalized advertising experiences. With our ads system still in its early stages, this is a unique opportunity to shape and develop a world-class, ML-driven advertising platform from the ground up. You Will: Drive the design and implementation of machine learning solutions for ad ranking algorithms. Design and implement large scale recommendation models Author specs for new features and improvement Collaborate with other teams within Roblox to make sure we are building products with a community first approach. Balance researching new technologies with a practical approach to accomplish the research efforts into the Roblox products Communicate with the industry and commun

machine learning
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TA
16mo ago

About the Role Together AI is building the AI Native Cloud, an end-to-end platform for the full generative AI lifecycle, combining the fastest LLM inference engine with state-of-the-art GPU cloud infrastructure. The Together Cloud team builds the [Together GPU Clusters](https://www.together.ai/gpu-clusters) flagship IaaS product that provides high-performance, AI-ready GPU clusters through a self-serve cloud console, along with the virtualized infrastructure layer powering Together's inference, RL, and fine-tuning products. As a Senior Software Engineer focusing on AI Compute in the Together Cloud org, you will build and own major components of the next generation AI cloud platform – a highly available, global cloud infrastructure with cutting-edge virtualization of the latest ML hardware: GB300s/VRs, BlueField DPUs, InfiniBand and dual/quad-plane RoCEv2 fabrics. That virtualized computing platform powers our own SaaS products – inference, RL, and fine-tuning – and serves external cloud customers through self-serve offerings such as on-demand/reserved Kubernetes/Slurm clusters, across dozens of data centers and hundreds of thousands of GPUs. The hard problems in rapidly scaling heterogeneous GPU fleets are software problems: fully automated bootstrapping of GPU data centers, high-performance virtualization of GPU compute and DC networking without compromising isolation or portability, and fault-tolerant decentralized control planes. We solve them by building global and in-DC services, Kubernetes operators, and high-performance SDN libraries, forking hypervisors and Linux kernels, and building infra tailored to inference and fine-tuning. You'll own massive greenfield projects across their full lifecycle – scoping the problem and writing PRDs with our PMs, designing the system, and building it through to GA launch. Responsibilities Build the GPU and network virtualization stack: the hypervisor, kernel, and SDN work that makes GPU compute and DC networking high-perform

awsazuregcp
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F
Fin
📍 Ireland• Full-time
25mo ago

Fin , now part of Salesforce, is on a mission to help businesses provide perfect customer experiences. Our AI Agent Fin is the highest-performing AI Customer Agent on the market today, enabling businesses to deliver impeccable, always-on customer support across the customer journey, from service, to sales, to ecommerce. Powered by our own AI models, Fin resolves complex customer issues end-to-end across every channel, with minimal set-up and integration. Fin can also be combined with our natively integrated Intercom help desk, giving modern support teams one single system. Together with Salesforce, the #1 AI CRM, where humans with agents drive customer success, we're building the future of customer experience. Here, ambition meets action. Tech meets trust. And innovation isn't a buzzword, it's a way of life. The world of work as we know it is changing, and we're looking for Trailblazers who are passionate about bettering business and the world through AI. Ready to level up your career at the company leading workforce transformation in the agentic era? You're in the right place. Agentforce is the future of AI, and you are the future of Salesforce. What's the opportunity? We’re looking for Senior Product Engineers to join the AI Group to build Fin's AI-powered products. Product Engineers working in ML work closely with both our ML Scientists and product teams. They must deeply understand our product, our customers, our ML tech stack and our broader product stack. Our group is responsible for defining new ML features, researching appropriate algorithms and technologies, and rapidly getting first prototypes in our customers’ hands. We are an extremely product focussed team. We work in partnership with Product and Design functions of teams we support. Our team's dedicated Engineers enable us to move to production fast, often shipping to beta in weeks after a successful offline test. We are very passionate about applying machine learning technology, and have p

javascriptpythonmachine learning
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Nuro
📍 Mountain View• From $193.9K/yr
11 days ago

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 Safety and redundancy is one of the key requirements to Nuro Driver™. In this role, you will contribute to our Parallel Autonomy System and Collision Detection System to protect our passengers and other road participants from the unknown unknowns. Here, you’ll be challenged to provide utmost accuracy while working with exacting latency requirements, where millisecond counts. About the Work This team tackles a wide range of problems: ML-based perception across all sensor modalities including audio, estimating object velocity and acceleration with high accuracy, onboard latency optimization, and developing tooling for large scale data curation. Partner with a tight-knit group of engineers who focus on collision avoidance. Participate in the design and implementation of a system that spans perception, planning, and control. Contribute to designing the validation methodology in order to validate a system that is required to pe

aic++logistics
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About Appier Appier (TSE: 4180) is an AI-native Agentic AI as a Service (AaaS) company that empowers businesses to create value through cutting-edge AdTech and MarTech solutions. Founded in 2012 with the vision of “Making AI Easy by Making Software Intelligent,” Appier helps businesses turn AI into ROI through its Ad Cloud, Personalization Cloud, and Data Cloud—each powered by Agentic AI that enables autonomous, adaptive, and real-time decision-making. Today, Appier operates 17 offices across APAC, the US, and EMEA, and is listed on the Tokyo Stock Exchange. Learn more at www.appier.com . About the Role We’re on the lookout for an ambitious and technically outstanding Senior Software Engineer, Backend Development to join our Enterprise Solution Engineering Team, Product Recommendation (ES REC) . Software engineers at Appier build a wide range of platforms and services that interconnect data and AI with our customers and users. In this role, you will be at the forefront of AI innovation, designing and building scalable backend architecture that delivers personalized experiences. What You’ll Do Key owner of sizable engineering projects and services within the ES REC team. Architect and implement AI Agents and agentic workflows to automate decision-making processes and enhance recommendation delivery. Build and optimize Machine Learning pipelines for large-scale personalization, ensuring efficient data processing, model serving, and low-latency response. Design and operate scalable, cloud-native architectures leveraging managed services (e.g., GKE, BigQuery, or Pub/Sub ) to support high-throughput recommendation workflows. Architect and operate resilient ML job execution frameworks covering training, inference, and post-processing workflows to ensure system elasticity. Define and implement CI/CD pipelines with tools like Jenkins or ArgoCD to enable seamless, automated, and reliable deployments. Lead system designs and provide technical guidance to team me

pythonsqlmysql
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DR
7mo ago

What we’re doing isn’t easy, but nothing worth doing ever is. We envision a future powered by robots that work seamlessly with human teams. We build artificial intelligence that enables service robots to collaborate with people and adapt to dynamic human environments. Join our mission-driven team as we build out current and future generations of robots. As an ML Engineer, Manipulation, you will develop and deploy learning-based manipulation systems that enable mobile robots to interact reliably with the physical world in dynamic human environments. You’ll build perception-to-action models, training datasets, evaluation tooling, and deployment pipelines that improve robustness, generalization, and safety for real-world manipulation tasks at scale. Your work will directly impact the robot’s ability to perform complex interactions consistently across real sites with minimal special-case engineering. Responsibilities Develop learning-based manipulation models for end to end sensor-driven interaction (e.g., reaching, motion generation, and execution in dynamic environments). Build and maintain manipulation training pipelines: dataset creation from robot logs/teleop, action representations, augmentation, and distributed training. Design evaluation metrics and regression tests that quantify manipulation reliability, recovery behavior, and safety in real environments. Develop sim-to-real workflows for manipulation learning, including simulation environments, domain randomization, and failure-mode testing. Optimize and distill models for edge deployment; benchmark latency, memory use, and stability on target hardware. Partner with the AI platform team to integrate policies with control and safety systems, and validate end-to-end performance on robots. Analyze field performance, identify dominant failure modes, and drive iterative improvements through data collection and targeted retraining. Basic Qualifications Bachelor’s or Master’s degree in Robotics, Computer Scienc

pythonartificial intelligenceai
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R
Roblox
📍 San Mateo• Full-time• $243.3K – $295.3K/yr
10mo ago

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators. At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. As a member of the Infrastructure Foundation Hardware Engineering team, you will play a key role in enabling our mission to deliver a reliable, high-performing, and cost-efficient infrastructure that powers the world’s play. In this specialized role, you will be the technical lead for our GPU and AI accelerator ecosystem. You will be responsible for the full lifecycle of GPU hardware, from initial architectural evaluation and firmware qualification to large-scale fleet integration and performance tuning. You will ensure that Roblox’s massive-scale rendering and ML workloads run on the most optimized and stable hardware possible. You Will: Architect & Prototype: Prototype next-generation GPU-accelerated hardware platforms, ensuring seamless integration between high-density compute nodes, high-speed interconnects (NVLink/PCIe Gen5/6), and system firmware. GPU Optimization: Drive the integration, performance testing, and debugging of GPUs in our fleet, focusing specifically on hardware-level optimizations, driver tuning, and thermal/power management. Validation & Certification: Develop and execute rigorous evaluation and stress-testing strategies for GPU-heavy server platforms to ensur

pythonlinuxai
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Z
Zoox
📍 Foster City• Full-time• Hybrid• $213K – $295K/yr
12mo ago

Zoox has embarked on a highly ambitious journey to develop a full-stack autonomous mobility solution for our cities. As a technical program manager, you will work cross-functionally with engineering leaders across software, hardware, vehicle engineering, and product to drive our corporate strategy into tactical and detailed road maps that facilitate effective execution at each stage of our growth curve. You will work with each engineering team to develop project schedules, identify milestones, flag risks, estimate budgets, and clearly communicate ongoing progress. In this role, you will: Partner with engineering managers in the respective Autonomy team (Perception, Prediction & Behavioral ML, TeleGuidance, Planning & Controls, Collision Avoidance System) to translate the top-down corporate strategy and milestones into detailed product roadmaps, timelines, and deliverables Drive cross-functional teams across Autonomy teams to build and execute on solutions for improving our driving behavior Collaborate with engineering to figure out how best to develop the underlying measurements and datasets for Driving Behavior KPIs Highlight potential risks and proactively build out risk-mitigating actions Build and deliver executive presentations on program status, issues/risks, and accomplishments Qualifications BS/MS degree in computer science, engineering or equivalent job experience At least 6 years of experience in engineering program management Experience with AI/ML, autonomous vehicles, computer vision, large language models, reinforcement learning, simulation, and/or automotive or aerospace processes Strong track record of managing complex cross-functional projects and problem solving An ability to keep the big picture in focus and to provide clear, well-structured, and concise communications tailored to each appropriate audience Deep familiarity with software dev

machine learningai
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Fin
📍 London• Full-time
12mo ago

Fin , now part of Salesforce, is on a mission to help businesses provide perfect customer experiences. Our AI Agent Fin is the highest-performing AI Customer Agent on the market today, enabling businesses to deliver impeccable, always-on customer support across the customer journey, from service, to sales, to ecommerce. Powered by our own AI models, Fin resolves complex customer issues end-to-end across every channel, with minimal set-up and integration. Fin can also be combined with our natively integrated Intercom help desk, giving modern support teams one single system. Together with Salesforce, the #1 AI CRM, where humans with agents drive customer success, we're building the future of customer experience. Here, ambition meets action. Tech meets trust. And innovation isn't a buzzword, it's a way of life. The world of work as we know it is changing, and we're looking for Trailblazers who are passionate about bettering business and the world through AI. Ready to level up your career at the company leading workforce transformation in the agentic era? You're in the right place. Agentforce is the future of AI, and you are the future of Salesforce. What's the opportunity? Fin's Machine Learning team is responsible for defining new ML features, researching appropriate algorithms and technologies, and rapidly getting first prototypes in our customers’ hands. We are an extremely product focussed team. We work in partnership with Product and Design functions of teams we support. Our team's dedicated ML product engineers enable us to move to production fast, often shipping to beta in weeks after a successful offline test. We are very passionate about applying machine learning technology, and have productized everything from classic supervised models, to cutting-edge unsupervised clustering algorithms, to novel applications of transformer neural networks. We test and measure the real customer impact of each model we deploy. What will I be doing? Identify areas w

sqlmachine learningai
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Fin
📍 Dublin• Full-time
21mo ago

Fin , now part of Salesforce, is on a mission to help businesses provide perfect customer experiences. Our AI Agent Fin is the highest-performing AI Customer Agent on the market today, enabling businesses to deliver impeccable, always-on customer support across the customer journey, from service, to sales, to ecommerce. Powered by our own AI models, Fin resolves complex customer issues end-to-end across every channel, with minimal set-up and integration. Fin can also be combined with our natively integrated Intercom help desk, giving modern support teams one single system. Together with Salesforce, the #1 AI CRM, where humans with agents drive customer success, we're building the future of customer experience. Here, ambition meets action. Tech meets trust. And innovation isn't a buzzword, it's a way of life. The world of work as we know it is changing, and we're looking for Trailblazers who are passionate about bettering business and the world through AI. Ready to level up your career at the company leading workforce transformation in the agentic era? You're in the right place. Agentforce is the future of AI, and you are the future of Salesforce. What's the opportunity? Fin's Machine Learning team is responsible for defining new ML features, researching appropriate algorithms and technologies, and rapidly getting first prototypes in our customers’ hands. We are an extremely product focussed team. We work in partnership with Product and Design functions of teams we support. Our team's dedicated ML product engineers enable us to move to production fast, often shipping to beta in weeks after a successful offline test. We are very passionate about applying machine learning technology, and have productized everything from classic supervised models, to cutting-edge unsupervised clustering algorithms, to novel applications of transformer neural networks. We test and measure the real customer impact of each model we deploy. What will I be doing? Identify areas w

sqlmachine learningai
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Z
Zoox
📍 Foster City• Full-time• Hybrid• $199K – $270K/yr
17 days ago

The Perception team is pioneering the development of a multi-modality foundation model to drive the next generation of autonomous system intelligence. As a Perception Deployment Engineer, you will focus on bringing highly efficient, production-ready large-scale models to our on-vehicle stack. We are looking for experts with hands-on experience in compressing, accelerating, and deploying complex computer vision or foundation models for power- and thermal-constrained vehicle SOCs. You will optimize the ML models, write custom CUDA kernels, and build highly concurrent inference code to ensure real-time, deterministic execution on edge devices. In this role, you will: Design and develop production-level, low latency, and memory-safe C++ and CUDA code for real-time perception algorithms on vehicle systems. Optimize large-scale models (Multi-Modal Sensor Fusion models, LLMs, VLMs) using advanced quantization (PTQ, QAT), pruning, mixed-precision inference frameworks. Architect and implement model conversion and compilation pipelines using TensorRT for edge deployment. Perform rigorous parity checking, accuracy recovery, and latency benchmarking between PyTorch frameworks and compiled edge binaries. Develop and optimize custom ML OPs and TensorRT Plugins with efficient CUDA kernels to minimize latency and maximize memory bandwidth on AI accelerators. Qualifications: Production-level C++ (14/17/20) and Python programming skills, with experience developing concurrent, memory-safe, real-time inference code for edge devices. Deep expertise in model compression technologies (e.g., model quantization such as PTQ and QAT) and mixed-precision inference frameworks (INT8, FP8, BF16/FP16). Proven experience optimizing large-scale models (Multi-Modal Sensor Fusion models, LLMs, VLMs/VLAs) utilizing Efficient Attention mechanisms (

pythonmachine learningai
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MI
Mach Industries
📍 Huntington Beach• $125K – $160K/yr
1mo ago

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 Mach Industries is building an AI-forward autonomy stack for contested environments where GNSS and other sensing may be unavailable, degraded, or denied. As an Autonomy Software Engineer, you will design, build, and deploy the software systems that power perception, localization, navigation, planning, and mission autonomy across our product lines. This is a broad role for engineers who are deeply technical in one domain and highly effective across adjacent ones. You may come from estimation, perception, machine learning, embedded systems, or planning, but you are excited to work across the autonomy stack and deliver real capability from prototype to fielded system. Key Responsibilities Design, implement, and ship production autonomy software in modern C++ on Linux, with Python for tooling, analysis, and ML workflows. Build and integrate capabilities across perception, localization, sensor fusion, navigation, planning, and embedded inference. Take systems from prototype through simulation, software-in-the-loop, hardware-in-the-loop, flight test, and deployment. Analyze logs, simulation results, and test data to debug failures, improve robustness, and drive rapid iteration. Develop evaluation pipelines, metrics, and tooling for accuracy, lat

pythonlinuxmachine learning
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