Machine Learning Infrastructure Engineer Jobs

About Taskrabbit: Taskrabbit is a marketplace platform that conveniently connects people with Taskers to handle everyday home to-do’s, such as furniture assembly, handyman work, moving help, and much more. At Taskrabbit, we want to transform lives one task at a time. As a company we celebrate innovation, inclusion and hard work. Our culture is collaborative, pragmatic, and fast-paced. We’re looking for talented, entrepreneurially minded and data-driven people who also have a passion for helping people do what they love. Together with IKEA, we’re creating more opportunities for people to earn a consistent, meaningful income on their own terms by building lasting relationships with clients in communities around the world. Taskrabbit is a hybrid company with employees distributed across the US and EU and a Built In — Best Places to Work (2022, 2023, 2024, 2025) continually ranked across multiple national and regional categories. Join us at Taskrabbit, where your work will be meaningful, your ideas valued, and your potential unleashed! This role operates on a hybrid schedule requiring two days of in-office collaboration per week. About the Role Reporting to the Infrastructure Director of Engineering, you are a pragmatic security leader who acts as a business enabler rather than a gatekeeper. You thrive in a high-velocity, non-regulated environment where you must define "what good looks like" from scratch and drive security progress with a blend of strong planning skills and strong cross-functional partnerships. You are a technical player-coach who manages the "how" behind engineering initiatives, providing direct guidance to a lean team which needs to navigate trade-offs between quality, depth, and delivery volume. You are just as comfortable planning core initiatives as you are writing a proposal for security program improvements. You have a proven track record of leading a team to achieve compliance with a security framework from scratch (e.g., CIS, SOC2, P

Location Details: At GoDaddy the future of work looks different for each team. Some teams work in the office full-time, others have a hybrid arrangement (they work remotely some days and in the office some days) and some work entirely remotely. Remote: This is a remote position, so you’ll be working remotely from your home. You may occasionally visit a GoDaddy office to meet with your team for events or meetings. Join our team Our Global Sustaining Engineering team sits at the intersection of software engineering and infrastructure, ensuring the services our customers depend on are fast, resilient, and always available. As a Senior Site Reliability Engineer, you'll take direct ownership of production services — from initial design through day-to-day operation — while partnering with product, engineering, and security teams to build and maintain business-critical systems. In this role, you will deepen your technical expertise and grow your leadership presence by mentoring the next generation of SREs. You will also gain hands-on experience with intelligent tooling in real-world workflows. What you'll get to do... Design, implement, and operate scalable, highly available production services while diagnosing and resolving complex infrastructure, network, and application issues Build and maintain alerting pipelines, dashboards, and SLO-driven monitoring strategies using Icinga, Prometheus, and Grafana Lead incident response end-to-end — performing root-cause analysis, authoring blameless post-mortems, and driving corrective actions to closure Develop and extend Infrastructure as Code coverage and build internal tooling that eliminates manual, repetitive operational work Mentor SRE I and SRE II engineers through code reviews, debugging sessions, and knowledge-sharing talks Apply LLM-driven log analysis, anomaly detection, and generative AI tools to accelerate incident response and runbook creation — validating all outputs before use Your experien

About Truveta Truveta is the world’s first health provider-led data platform, with a vision of Saving Lives with Data. Our mission is to enable researchers to find cures faster, empower every clinician to be an expert, and help families make the most informed decisions about their care. Achieving this vision requires a talented and diverse team with expertise across healthcare, software engineering, cloud infrastructure, data platforms, and artificial intelligence. We are looking for people who are motivated by purposeful work and committed to building technology that can improve healthcare outcomes. This position is based in Hyderabad, India . Who We Need Truveta is expanding its engineering presence in India to solve complex healthcare and technology challenges at global scale. We are seeking a collaborative and experienced engineering leader who can operate effectively across ambiguity, scale, and evolving requirements. The ideal candidate combines strong software and infrastructure fundamentals with the ability to build high-performing teams, influence technical direction, and deliver reliable platforms. You should be comfortable balancing hands-on technical leadership with people management and working with distributed teams across India and the United States. If you are motivated by purposeful work, enjoy building teams and platforms from the ground up, and want to shape how data, AI, and engineering systems are powered internally, Truveta may be the right fit for you. This Opportunity We are seeking a Director Of Engineering (POD Lead) to lead the Platform Services team in India. The Platform Services team will build, manage, and operate the infrastructure that supports engineering teams across India and globally. The team will also own critical backend and platform services, including authentication, authorization, customer and consumer identity and access management, CI/CD, Kubernetes and cloud

About the Role The Model Shaping team at Together AI works on products and research for tailoring open foundation models to downstream applications. We build services that allow machine learning developers to choose the best models for their tasks and further improve these models using domain-specific data. In addition to that, we develop new methods for more efficient model training and evaluation, drawing inspiration from a broad spectrum of ideas across machine learning, natural language processing, and ML systems. As a Platform Engineer in Model Shaping, you will work at the intersection of backend engineering and infrastructure, building the foundational layers of Together’s platform for model customization and evaluation. You will design, develop, and operate both the backend services and the underlying systems that enable us to sustainably and reliably scale production workflows launched by our users, as well as internal research experiments. You will operate in a cross-functional environment, collaborating with other engineers and researchers in the team to improve the infrastructure based on the needs of projects they work on. You will also interact with other engineering teams at Together (such as Commerce, Data Engineering, and Cloud Infrastructure) to integrate the services developed by Model Shaping with systems developed by those teams. Responsibilities Design and build Together’s systems and infrastructure for model customization, including user-facing features and internal improvements Contribute to reliability improvements for the platform, participating in an on-call rotation and improving processes for incident response Create and improve internal tooling for deployment, continuous integration, and observability Build a job orchestration platform spanning multiple datacenters, supporting a highly heterogeneous hardware landscape Partner with teams developing internal services, co-designing these services and incorporating them in systems built wit

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. The Technical Program Management Team The Engineering Technical Program Management Team’s mission is to enable Okta to deliver on key strategic goals by bringing groups together across Engineering, Security, Legal, Compliance, Product Management, and Customer Support. Engineering TPMs drive prioritization, planning, execution, and ensure transparency while managing success criteria. The Principal Technical Program Manager, Engineering Opportunity As a Principal Technical Program Manager in the Engineering TPM Team, you will partner with various groups across Okta to build and deliver key Engineering initiatives. You will be the point person for clarifying strategic level goals and outlining the execution plans to achieve them. You will work within and across teams to prioritize and execute on key objectives. Employing both a strategic and tactical approach is a requirement in this role. You will not only have strong TPM experience, but also experience implementing complex efforts within Engineering or Infrastructure in a SaaS and agile environment. *This position requires the ability to access Impact Level 4 & 5 (IL4 and IL5) data, as defined by the Department of Defense (DoD) Cloud Computing Security Requirements Guide. As a condition of employment for this position, the successful candidate must be able to submit documentation establishing U.S. Person status (e.g. a U.S. Citizen, National, Lawful Permane

About BlockTech BlockTech is a fast-paced algorithmic trading firm at the frontier of global cryptocurrency derivatives and spot markets. We trade 24/7 across some of the most data-rich, fast-moving venues in finance, and we use that data to build smarter models, sharper signals, and more adaptive systems. Crypto is one of the few markets where a researcher can still meaningfully move the edge. The data is abundant, the microstructure is novel, and the feedback loop between a research idea and live PnL couldn’t be shorter. We’re growing fast, and we’re looking for a Quantitative Researcher with a strong machine learning toolkit to help us push that edge further. The role As a Quantitative Researcher on our trading floor, you’ll own ideas end-to-end from hypothesis and dataset construction through feature engineering, model training and backtesting, all the way to live deployment, monitoring, and iterative improvement. You’ll sit shoulder-to-shoulder with Quantitative Traders and Quantitative Analysts, and your work will directly drive how we price and trade. What you’ll work on Collaborating closely with traders to translate research insights into systematic trading strategies Designing, developing and deploying models for price prediction, signal generation, execution, and anomaly detection across crypto derivatives and spot markets using state-of-the-art AI and ML techniques. Building robust trading, backtesting and research infrastructure alongside our engineers, so promising ideas can move into production quickly and safely Owning models in production: monitoring live performance, diagnosing decay, and iterating on what you ship What we’re looking for A strong academic background in a quantitative discipline (Mathematics, Physics, Statistics, Computer Science, Econometrics, ML/AI, or similar), typically a PhD or an MSc with strong research experience Fluency in Python and the modern ML stack (PyTorch and/or TensorFlow, scikit-learn, NumPy, pandas) A deep, intuit

About BlockTech BlockTech is a fast-paced algorithmic trading firm at the frontier of global cryptocurrency derivatives and spot markets. We trade 24/7 across some of the most data-rich, fast-moving venues in finance, and we use that data to build smarter models, sharper signals, and more adaptive systems. Crypto is one of the few markets where a researcher can still meaningfully move the edge. The data is abundant, the microstructure is novel, and the feedback loop between a research idea and live PnL couldn’t be shorter. We’re growing fast, and we’re looking for a Quantitative Researcher with a strong machine learning toolkit to help us push that edge further. The role As a Quantitative Researcher on our trading floor, you’ll own ideas end-to-end from hypothesis and dataset construction through feature engineering, model training and backtesting, all the way to live deployment, monitoring, and iterative improvement. You’ll sit shoulder-to-shoulder with Quantitative Traders and Quantitative Analysts, and your work will directly drive how we price and trade. You will: Collaborate closely with traders to translate research insights into systematic trading strategies Design, develop and deploy models for price prediction, signal generation, execution, and anomaly detection across crypto derivatives and spot markets using state-of-the-art AI and ML techniques. Build robust trading, backtesting and research infrastructure alongside our engineers, so promising ideas can move into production quickly and safely Own models in production: monitoring live performance, diagnosing decay, and iterating on what you ship What we're looking for A strong academic background in a quantitative discipline (Mathematics, Physics, Statistics, Computer Science, Econometrics, ML/AI, or similar), typically a PhD or an MSc with strong research experience Fluency in Python and the modern ML stack (PyTorch and/or TensorFlow, scikit-learn, NumPy, pandas) A deep, intuitive grasp of overfitting, g

About BlockTech BlockTech is a fast-paced algorithmic trading firm at the frontier of global cryptocurrency derivatives and spot markets. We trade 24/7 across some of the most data-rich, fast-moving venues in finance, and we use that data to build smarter models, sharper signals, and more adaptive systems. Crypto is one of the few markets where a researcher can still meaningfully move the edge. The data is abundant, the microstructure is novel, and the feedback loop between a research idea and live PnL couldn’t be shorter. We’re growing fast, and we’re looking for a Quantitative Researcher with a strong machine learning toolkit to help us push that edge further. The role As a Quantitative Researcher on our trading floor, you’ll own ideas end-to-end from hypothesis and dataset construction through feature engineering, model training and backtesting, all the way to live deployment, monitoring, and iterative improvement. You’ll sit shoulder-to-shoulder with Quantitative Traders and Quantitative Analysts, and your work will directly drive how we price and trade. You will: Collaborate closely with traders to translate research insights into systematic trading strategies Design, develop and deploy models for price prediction, signal generation, execution, and anomaly detection across crypto derivatives and spot markets using state-of-the-art AI and ML techniques. Build robust trading, backtesting and research infrastructure alongside our engineers, so promising ideas can move into production quickly and safely Own models in production: monitoring live performance, diagnosing decay, and iterating on what you ship What we're looking for A strong academic background in a quantitative discipline (Mathematics, Physics, Statistics, Computer Science, Econometrics, ML/AI, or similar), typically a PhD or an MSc with strong research experience Fluency in Python and the modern ML stack (PyTorch and/or TensorFlow, scikit-learn, NumPy, pandas) A deep, intuitive grasp of overfitting, g

About BlockTech BlockTech is a fast-paced algorithmic trading firm at the frontier of global cryptocurrency derivatives and spot markets. We trade 24/7 across some of the most data-rich, fast-moving venues in finance, and we use that data to build smarter models, sharper signals, and more adaptive systems. Crypto is one of the few markets where a researcher can still meaningfully move the edge. The data is abundant, the microstructure is novel, and the feedback loop between a research idea and live PnL couldn’t be shorter. We’re growing fast, and we’re looking for a Quantitative Researcher with a strong machine learning toolkit to help us push that edge further. The role As a Quantitative Researcher on our trading floor, you’ll own ideas end-to-end from hypothesis and dataset construction through feature engineering, model training and backtesting, all the way to live deployment, monitoring, and iterative improvement. You’ll sit shoulder-to-shoulder with Quantitative Traders and Quantitative Analysts, and your work will directly drive how we price and trade. What you’ll work on Collaborating closely with traders to translate research insights into systematic trading strategies Designing, developing and deploying models for price prediction, signal generation, execution, and anomaly detection across crypto derivatives and spot markets using state-of-the-art AI and ML techniques. Building robust trading, backtesting and research infrastructure alongside our engineers, so promising ideas can move into production quickly and safely Owning models in production: monitoring live performance, diagnosing decay, and iterating on what you ship What we’re looking for A strong academic background in a quantitative discipline (Mathematics, Physics, Statistics, Computer Science, Econometrics, ML/AI, or similar), typically a PhD or an MSc with strong research experience Fluency in Python and the modern ML stack (PyTorch and/or TensorFlow, scikit-learn, NumPy, pandas) A deep, intuit

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. The ASIC Validation team plays a critical role in bringing Micron's next-generation silicon products to life by validating and characterizing new devices as they return from fabrication. Working closely with design, verification, and firmware teams, the group develops innovative validation methodologies, automation solutions, and AI-enabled workflows to ensure product quality, performance, and reliability. As an ASIC Validation Intern, you will work alongside experienced engineers to validate newly developed silicon and enhance the validation infrastructure used across engineering teams. This role provides hands-on experience with hardware validation, lab equipment, automation, data analysis, and AI-assisted engineering workflows while contributing directly to the successful bring-up of next-generation ASIC products. Responsibilities Collaborate with validation, design verification, and firmware teams to support silicon bring-up, testing, and validation activities for new ASIC devices. Use laboratory equipment, automation tools, and validation environments to characterize device functionality and performance. Develop or enhance scripts, automation solutions, and AI-assisted workflows to improve validation efficiency, failure analysis, and reporting. Analyze validation results, debug complex issues, and evaluate AI-generated insights while applying sound engineering judgment. Document technical findings, communicate project results, and present recommendations to engineering teams. </

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: We’re seeking exceptional Applied engineers to join a high-priority project that approximately 600 million monthly users use. This is an exciting opportunity for individuals with a engineer or scientist background to apply their skills to recommendation systems, ranking algorithms, search technologies, and many other systems. You’ll work at the intersection of advanced AI development and real-world impact, enhancing the ability to connect users with relevant content, accounts, and experiences. RESPONSIBILITIES: Designing and architecting recommendation algorithms across various product surfaces Leverage all of SpaceXSI's infra and AI stacks to dramatically enhance the user experience Write data pipelines and training jobs that continuously learn from product data. Iterate and improve the algorithm by gathering user feedback in real time through experimentation Ensuring scalability and efficiency of machine learning systems BASIC QUALIFICATIONS: Knowledge of data infrastructure like Kafka, Clickhouse, and Spark Experienced in implementing recommender systems and/or deep learning applications at industrial scale Skilled in one or more DL software frameworks such as

About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies - from the world’s largest enterprises to the most ambitious startups - use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career. About the team Risk Detection is focused on providing a delightful experience for our merchants and minimizing friction, while ensuring the safety of our users in the financial ecosystem. Whenever the Risk team takes action on an account, we work to notify Merchants and provide clear status on what’s happening, enable guided workflows for resolving their issues, and redefine our overall Risk processes to make them as smooth as possible for good merchants. What you’ll do We’re looking for an engineering leader to lead and grow a strong team of engineers, build relationships with customers internally and externally, and champion our vision of making Stripe’s risk management a feature that attracts and retains merchants, and becomes a product differentiator. This is an exciting opportunity to partner with teams across Stripe to build the best merchant experience, and contribute directly to Stripe’s growth. Responsibilities Support the team in delivering a high level of technical quality and impact via APIs, user-facing experiences, services, and systems Recruit, hire, scale, and develop an amazing team of engineers Executing cross-functionally with leadership, product teams, infra teams & risk strategists Be actively involved in strategic direction and platform decisions that impact all of Stripe and Stripe customers Who you are We're looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you

Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career. About the team The Radar ML team builds the machine learning systems that power Stripe’s Radar fraud and abuse product suite. Our models make real-time decisions across a significant share of internet commerce - helping businesses stop fraud, increase authorization, and grow safely. By turning economy-scale datasets into compelling ML products, the team directly improves customer outcomes and drives meaningful revenue for Stripe. The team is growing, and expanding into multiple new areas. We are building abuse protections across the full customer life-cycle, adaptive and customizable fraud systems for enterprises, and risk intelligence for 50+ global payment methods. What you’ll do You will own ML problems from conception to production: analyzing new fraud and abuse patterns, exploring large-scale datasets, experimenting with model architectures, designing evaluations, deploying models, and monitoring performance. Your work may include developing transformer architectures for payment data, building graph-powered intelligence across consumers, leveraging LLMs to detect emerging attacks, or rapidly prototyping new protections with frontier AI labs. You will have opportunities to ship 0→1 products, and to improve mission-critical ML models operating at Stripe scale. Responsibilities Build, train, evaluate, and deploy models that detect fraud and abuse across Stripe’s global network. Investigate emerging fraud and abuse patterns, identify whe

Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career. About the team Growth Platform builds the machine learning systems that help businesses discover and use the Stripe products that meet their needs. Our recommendations reach users across the Dashboard, email, onboarding, documentation, and AI agent interfaces. We combine an understanding of each business with models that decide which recommendation is useful, when to show it, and how to learn from the outcome. Our work spans recommendation and ranking models, contextual bandits, agent-based recommendations, and the data and evaluation systems behind them. We build shared capabilities that product, marketing, and sales teams can use across Stripe. Success means helping businesses take useful actions and adopt products that help them grow, while keeping recommendations relevant and avoiding unnecessary messages. What you’ll do You will build and operate production ML systems that improve how Stripe recommends products, content, and next steps to businesses. You will own work from problem definition and feature development through training, evaluation, deployment, monitoring, and iteration. Working with data scientists, engineers, and product partners, you will turn model improvements into measurable user and business outcomes. Responsibilities Design, train, evaluate, deploy, and maintain models for recommendation, ranking, and personalized action selection across Growth Platform surfaces. Improve contextual bandit and policy-learning approaches, including e

About Ramp Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends. We automate how over $200B in annualized spend flows in and out of 70,000+ companies: authorizing payments, flagging risk, categorizing spend, and closing books. The problems are high-stakes, data-dense, and unforgiving. We hire people with high agency and high urgency. We look for slope over intercept. We care less about where you trained and more about what you’ve built. At Ramp, everyone is a builder who owns problems end to end and makes consequential decisions that shape the outcome. The median Ramp customer saves 5% and grows revenue 16% in their first year – far in excess of businesses operating without Ramp. We believe every ambitious company deserves the same. If you want to build systems that directly shape how companies move and manage billions, Ramp is the place to do it. About the Role We’re seeking someone to lead the future of fraud machine learning at Ramp. In this role, you will help build core machine learning models, design data architectures, and set strategic roadmaps to help Ramp mitigate fraud-related threats while minimizing the friction experience by legitimate users. You will partner closely with product and engineering counterparts across model design, implementation, execution, and analysis. What You’ll Do Employ statistical and machine learning techniques on large datasets to discover patterns of fraud, platform abuse, and identity theft Prototype and productionize machine learning models and rules-based systems to protect Ramp and its users from fraud Partner closely with Fraud Engineering and Data Platform teams to augment and leverage data across first and third party sources, ensuring we’ve added as much context as possible to every decision we make Contribute to the culture of Ramp’s machine learning team by influencing processes, tools, and systems that will allow us to make better decisions in