We're looking for an ML Data & Platform Engineer to own the infrastructure that powers our speech AI models: the pipelines that source and prepare training data, and the platform that trains, evaluates, and serves them in production. Speech AI has a data problem most ML teams don't, and you'll be at the centre of solving it, working as part of our ML team to remove friction across the entire lifecycle and get better models into production faster. This is a broad, cross-functional role suited to someone who enjoys working across the full stack: data infrastructure, distributed systems, and production ML, and who takes ownership of problems end to end rather than waiting to be told what to fix. What you'll do Designing, building, and maintaining scalable data pipelines for ingesting, transforming, validating, and storing large datasets used to train our models Developing and maintaining web scraping and data acquisition solutions to keep training datasets fresh, high-quality, and available at scale Building and operating the infrastructure that lets the ML team deploy and evaluate new models quickly, and that serves models efficiently and reliably in production Optimising infrastructure for both iteration speed and production reliability, including GPU utilisation, job scheduling, and training efficiency Implementing observability (monitoring, logging, alerting) across data pipelines and ML systems to catch issues early and keep things running smoothly Troubleshooting complex issues across distributed systems, spanning data infrastructure, training, and inference Continuously improving our data and MLOps practices, and helping shape the roadmap for how our platform evolves as we scale What you'll need Strong proficiency in Python and SQL, with a solid backend or data engineering foundation Hands-on experience with containerisation and orchestration (Docker, Kubernetes), and working with a major cloud provider Experience building data pipelines and ETL/ELT processe
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We're looking for an ML Data & Platform Engineer to own the infrastructure that powers our speech AI models: the pipelines that source and prepare training data, and the platform that trains, evaluates, and serves them in production. Speech AI has a data problem most ML teams don't, and you'll be at the centre of solving it, working as part of our ML team to remove friction across the entire lifecycle and get better models into production faster. This is a broad, cross-functional role suited to someone who enjoys working across the full stack: data infrastructure, distributed systems, and production ML, and who takes ownership of problems end to end rather than waiting to be told what to fix. What you'll do Designing, building, and maintaining scalable data pipelines for ingesting, transforming, validating, and storing large datasets used to train our models Developing and maintaining web scraping and data acquisition solutions to keep training datasets fresh, high-quality, and available at scale Building and operating the infrastructure that lets the ML team deploy and evaluate new models quickly, and that serves models efficiently and reliably in production Optimising infrastructure for both iteration speed and production reliability, including GPU utilisation, job scheduling, and training efficiency Implementing observability (monitoring, logging, alerting) across data pipelines and ML systems to catch issues early and keep things running smoothly Troubleshooting complex issues across distributed systems, spanning data infrastructure, training, and inference Continuously improving our data and MLOps practices, and helping shape the roadmap for how our platform evolves as we scale What you'll need Strong proficiency in Python and SQL, with a solid backend or data engineering foundation Hands-on experience with containerisation and orchestration (Docker, Kubernetes), and working with a major cloud provider Experience building data pipelines and ETL/ELT processe
Zoox is seeking a high-agency, hands-on Lead Data Platform Engineer to architect, optimize, scale and own the next generation of our enterprise & AI data foundation. In this role, you will architect a high throughput, data fabric that unifies data across Zoox and downstream AI agents. You will drive performance tuning, cost optimization, RBAC, data governance and CI/CD pipelines to deliver secure, low-latency, 'AI-ready' data foundations across the organization. You will serve as the primary technical driver for our data platform, designing autonomous frameworks, building scalable data infrastructure and establishing strict standards for security and developer velocity. This is an engineering-intensive leadership role for a builder who thrives on solving complex challenges. In This Role, You Will... Scaling self-healing data pipelines that automatically handle schema evolution, detect anomalies, execute circuit breakers and recover from failures without manual intervention. Define and enforce company-wide data governance, access, automated data quality testing, schema evolution policies and metadata management to maintain high-fidelity data assets. Implement intelligent storage lifecycle strategies, resource throttling and query optimization to minimize compute overhead while delivering high-throughput, low-latency data access for analytics and AI agents. With a focus on Databricks vs EMR (AWS) cloud optimization (cost and performance). Build automated CI/CD deployment templates, environment isolation, testing frameworks and version control standards, enabling rapid, reliable and zero-downtime deployments Qualifications 10+ years of hands-on experience in Data Platform Engineering or Software Engineering with a proven track record of architecting and scaling production-grade data foundations. Deep expertise in scaling and optimization, query tuning, compute resource allocation and impl
Who we are At Twilio, we’re shaping the future of communications, all from the comfort of our homes. We deliver innovative solutions to hundreds of thousands of businesses and empower millions of developers worldwide to craft personalized customer experiences. Our dedication to remote-first work , and strong culture of connection and global inclusion means that no matter your location, you’re part of a vibrant team with diverse experiences making a global impact each day. As we continue to revolutionize how the world interacts, we’re acquiring new skills and experiences that make work feel truly rewarding. Your career at Twilio is in your hands. . Hiring and how we work We use Artificial Intelligence (AI) to help make our hiring process efficient. That said, every hiring decision is made by real Twilions! Also, while we are a remote-first company, you may be asked to report in person on an ad-hoc basis for team gatherings, functional off-sites or customer meetings. . See yourself at Twilio Join the team as Twilio’s next Software Engineer, Platform Engineering (L3) About the job This position is a critical engineering role within Twilio Platform Engineering, requiring a hands-on engineer capable of developing, deploying, and managing highly available, massive-scale distributed systems. Our systems regularly process more than 12 billion emails during peak events like Black Friday, and our throughput requirements continue to scale rapidly. As an L3 engineer, you will build and operate resilient backend services at scale and contribute to the design and reliability of our dual-cloud infrastructure span across Amazon Web Services (AWS) and Microsoft Azure. You'll run Kubernetes beyond the boundaries of managed services, automate infrastructure with Terraform, and write production code to help keep distributed systems healthy under real production load while using modern AI-assisted tooling to move faster. Responsibilities In this role
Location: United States – Remote Clearance: Ability to obtain and maintain a Public Trust LTS is seeking a Senior AI Platform and Harness Engineer to develop and maintain the infrastructure, tooling, and evaluation frameworks that power enterprise AI solutions. This role is responsible for building the AI platform and reusable "AI harnesses" that enable Large Language Models (LLMs), AI agents, Retrieval-Augmented Generation (RAG), and Generative AI applications to be securely developed, tested, evaluated, monitored, and deployed at scale. The ideal candidate has experience with AI platforms, LLMOps, software engineering, cloud-native technologies, and backend systems, along with a passion for building reliable, observable, and production-ready AI solutions. You will work closely with AI architects, software engineers, data scientists, and product teams to ensure AI solutions are scalable, secure, cost-effective, and continuously improving. What You'll Do: Design, build, and maintain enterprise AI platform capabilities supporting Large Language Models (LLMs), AI agents, RAG, and Generative AI applications. Lead data preparation, training and fine-tuning of LLMs Develop reusable AI harnesses to automate testing, prompt evaluation, model benchmarking, regression testing, and quality assurance. Build AI evaluation frameworks to measure model accuracy, retrieval quality, hallucination detection, latency, throughput, cost, and overall application performance. Implement observability and monitoring solutions for AI applications, including telemetry, tracing, logging, dashboards, and operational metrics. Build and maintain LLMOps pipelines supporting model deployment, versioning, evaluation, experimentation, rollback, and continuous improvement. Design automated workflows for prompt testing, retrieval evaluation, AI system validation, and performance benchmarking. Develop internal tools for prompt management, model experimentation, AI performance optimization, and developer
Perforce is a community of collaborative experts, problem solvers, and possibility seekers who believe work should be both challenging and fun. We are proud to inspire creativity, foster belonging, support collaboration, and encourage wellness. At Perforce, you’ll work with and learn from some of the best and brightest in business. Before you know it, you’ll be in the middle of a rewarding career at a company headed in one direction: upward. With a global footprint spanning more than 80 countries and including over 75% of the Fortune 100, Perforce Software, Inc. is trusted by the world’s leading brands to deliver solutions for the toughest challenges. The best run DevOps teams in the world choose Perforce. Priten Nayak, the VP of Cloud Operations at Perforce, is searching for a Senior DevOps Engineer III, India to design and build the next-generation cloud platform for Perforce’s SaaS product portfolio to ensure the security, reliability, and high availability of all our production & CI/CD environments and applications. In this vital role, you will drive the design, development, & Implementation of automated tools and technologies to enable efficient delivery and service management of the production services & release deliveries. Drive the adoption of AI-assisted cloudops practices and agentic automation to improve operational efficiency, security, incident response, and platform reliability across the software delivery lifecycle.
Join Truecaller – The place where innovation meets impact! Truecaller's mission is to build trust in communication by making it safer, smarter, and more efficient. Born in Sweden, trusted by the world, and here’s why we stand out: We are trusted by over 500 million active users every month across 190+ countries We identify over 15 billion calls daily, helping users avoid spam and scams We are powered by a team of 400+ employees from 45+ nationalities We always look for people who take initiative, own their work, and keep raising the bar. An entrepreneurial mindset matters here, especially when it turns bold ideas into real actions. We stay collaborative and focused, always searching for smarter paths forward. If you want to make an impact and grow with a team that inspires millions, you’ll fit right in. The role: As a Senior Cloud Security Engineer, you will act as a technical leader in safeguarding our core cloud infrastructure. You will take ownership of maintaining the highest standards of security controls for our critical systems within Google Cloud Platform (GCP). We're looking for someone who thrives in complex environments, can solve infrastructure security problems where no established patterns exist, and isn't afraid to get their hands dirty . You won't just advise; you will actively build, configure, and fix security controls. You'll leverage your expert understanding of cloud services, infrastructure-as-code, and container security to architect robust security measures and drive systemic improvements across the organization. What you’ll do: Architect and Lead GCP Security: Take end-to-end ownership of designing and implementing security architectures for our GCP infrastructure. You will look beyond immediate fixes to architect long-term, scalable solutions for networking, compute, storage, and GKE. Hands-on Remediation & Engineering: You don't just identify risks; you fix them. You will actively write code, create Pull Requests, and apply configurati
About Ubiquiti At Ubiquiti Inc., we create technology platforms for Businesses, Smart Homes, and Internet Service Providers, driven by our goal to connect everyone, everywhere. To date, Ubiquiti has shipped over 100 million devices worldwide, from ISP networking products to next generation of IT solutions. Our growth is made possible by the dedicated team of hundreds behind the scenes. From software developers and product managers to designers and strategists, Team UI is driven to achieve our common goal: Rethinking IT. At Ubiquiti, you’ll heighten your potential and broaden your horizons - all while shaping the future of connectivity. Overview We’re looking for a technically strong and user-focused Cloud QA Engineer to join our UniFi Cloud Service team. This role plays a key part in ensuring our cloud platform delivers a reliable, scalable, and seamless experience across distributed systems. The focus is on building scalable test systems, validating cloud services, APIs, and networking behaviors under real-world conditions, while continuously improving QA efficiency through automation and AI-assisted workflows. You’ll take ownership of end-to-end validation across cloud, backend, and networking layers, with strong emphasis on automation, system reliability, and quality at scale. Key Responsibilities Automation & AI-driven QA Design and implement automated test strategies across API, integration, and end-to-end flows Build and maintain automation frameworks (Python preferred) and integrate with CI/CD Leverage AI tools to generate test cases, improve automation, and debug issues Evaluate AI-generated outputs and improve QA efficiency through AI-assisted workflows End-to-End Validation Own validation across cloud services, APIs, networking, and distributed system interactions Cover service-to-service flows, data consistency, and failure handling Validate real-world scenarios including deployment, upgrade, connectivity, and long-running usage Perform load/stre
About the role We are looking for a Software Engineer to help build our new financial platform that is highly reliable, scalable, and will serve as the backbone for Chime. This platform will power the most important financial activities that millions of Chime members undertake every day. You will ensure that we build the highest levels of trust with our members by making our platform lightning-fast, available, secure, resilient and auditable. This is an exciting opportunity to be an invaluable member of a strategically important initiative for Chime. In this role, you can expect to Design, develop, test, and deploy components of a new financial platform Deliver secure, reliable, and high-performance infrastructure and APIs Work with our infrastructure engineering team to minimize the operational overhead of production systems you deploy Develop thoroughly tested code and conduct quality assurance on all new code alongside our QA team Learn and execute on agile methodologies, follow test driven development approach Engineers are required to participate in on-call rotation. Being on call may include responding to incidents outside of regular working hours when necessary. To thrive in this role, you have Must have experience in Go Experience in additional backend languages such as Ruby, Java and Python is preferred Have 4+ years of engineering experience Have contributed to the development of backend systems Experience in payment processing systems Take a rigorous approach to testing backed development Experience with AWS or other cloud platforms, Cloud Native technology, No-SQL Databases as a bonus! Have an understanding of architectural patterns of large, mission-critical production services as a bonus! Have worked in continuous integration/deployment environments as a bonus! Please note: If you are located in Seattle, you will be required to onboard in person at our SF HQ + occasional business travel. #LI-Onsite #LI-WW1 Below is the base salary offered f
At Render, we’re building the modern cloud platform for developers creating AI-native, full-stack, multi-service applications. Our mission is to eliminate the tradeoff between the power of hyperscalers and the simplicity of developer-friendly platforms—so teams can ship fast, scale reliably, and focus on their product, not infrastructure. Unlike complex hyperscalers or ephemeral edge/serverless solutions, Render offers a developer-first experience with persistent compute, dynamic autoscaling, built-in orchestration, and observability, allowing teams to launch, scale, and manage real-world applications without writing infrastructure code or managing servers. Whether you're building LLM-powered applications, scalable SaaS products, or async processing pipelines, Render empowers teams to move fast and scale confidently from MVP to millions of users. Our platform is trusted by over 7 million developers worldwide and continues to grow rapidly. In February 2026, we raised an additional $100M in Series C financing, bringing our total funding to $260M, to accelerate our vision of making cloud infrastructure both powerful and intuitive—designed for the speed of modern AI development. We’re a diverse and talented team that values craft, velocity, and user experience. If you’re excited to help shape the future of the intelligent cloud and empower developers everywhere, we’d love to hear from you. Applying to Render We're seeking candidates who possess high integrity, humility, and an insatiable drive to learn. Through reasoned discussions and continuous feedback, we strive to improve both individually and collectively. We foster an environment of mutual trust and respect, empowering effective debate to achieve the best outcomes for our customers and team. We especially encourage members of underrepresented groups in the tech community to apply and understand that not all successful candidates will meet each requirement listed. Our interview process is unique to each role, and
Your wellbeing, our mission. Join a company shaping a healthier world. GET TO KNOW US At Wellhub we're revolutionizing workplace wellness. Our platform connects employees worldwide to the best partners for fitness, mindfulness, therapy, nutrition, and sleep—all in one simple subscription. Headquartered in NYC with team members in Europe, North America and South America, we’re on a mission to make every company a wellness company. We believe work should be fulfilling, inspiring, and balanced. Here, you’ll find a team that values wellbeing, collaboration, and different perspectives, where passion and creativity push boundaries to create real impact. Your contributions will help shape a healthier, more balanced world for you and millions of people globally. Join us in redefining the future of wellbeing! THE OPPORTUNITY We are hiring a Senior AI Platform Engineer to our Product Development team in Brazil ! This is a Remote – Brazil position, meaning you can work from anywhere within the country. Please note that this role is only open to candidates in Brazil. Join the ML Development Lifecycle team within our Product Development (PD) organisation, where we are redefining how a global tech company leverages intelligence. We build the foundations that allow hundreds of engineers and data scientists to develop and deploy AI at scale. You will own the evolution of our cloud-native ecosystem , creating a seamless and high-performance environment for the next generation of AI-driven products. If you are a software-minded engineer who thrives at the intersection of scalable Infrastructure and ML/AI orchestration, this is your chance to build a world-class platform that serves millions of users worldwide. YOUR IMPACT Scale the Ecosystem: Evolve and maintain our Kubeflow, Feast and Spark-on-Kubernetes infrastructure, ensuring it can handle the increasing complexity of both traditional ML and the new wave of AI. Build for Autonomy:
Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, Replit is democratizing software development by removing traditional barriers to application creation. About the Role Join our Enterprise Platform team and build the infrastructure foundations that enable the world's largest organizations to run Replit within their security and compliance boundaries. As a Software Engineer on this team, you'll design and implement the deployment flexibility, networking capabilities, authorization systems, and data controls that enterprises require, from single-tenant architectures and private connectivity to custom policy enforcement and customer-managed encryption. You'll work at the intersection of cloud infrastructure and enterprise requirements, partnering with Platform Engineering, Security, and Sales to ship capabilities that unlock adoption at demanding organizations. What You'll Do Build enterprise deployment infrastructure: Design and implement single-tenant and dedicated deployment options, enabling customers to run Replit with the isolation guarantees their security posture requires. Implement private networking capabilities: Build VPC peering, private connectivity, and static IP configurations that allow enterprises to integrate Replit into their existing network architectures. Design authorization services: Build the authorization infrastructure that enforces custom enterprise policies; enabling fine-grained access controls, custom permission models, and policy enforcement that integrates with customers' existing identity and governance systems. Ship data protection features: Implement bring-your-own-key (BYOK) encryption, customer-managed keys, and data residency controls that give enterprises ownership over their most sensitive data. Develop infrastructure automation: Write Terraform modules and automation that enable reliable, repeatable enterprise deployments across reg
Anyfin is building the next generation of consumer finance. We’re profitable, scaling quickly, and now operating with a banking license which opens up a lot of technical complexity. We’re looking for a senior backend engineer with cloud experience who enjoys moving fast, taking real ownership, and building things that actually have an impact. If that sounds like your kind of environment, keep reading. Because honestly, it’s not a role for everyone. Small team, high responsibility We hire carefully. We’re not a company that grows by adding headcount everywhere, we grow by keeping the bar high and building a team where every person matters. This isn’t a place where you disappear into a big org. If you join, you’ll have real influence on what we build and how we build it. What you’ll do Building, optimizing and scaling robust financial backend systems using Node.js and SQL (Postgres) Working primarily in the backend while contributing to our cloud infrastructure, helping design and operate systems across networking, servers and database architectures to support scalable and reliable services. Contributing to system architecture to ensure scalability, reliability, and long-term maintainability of financial systems. Collaborating closely with cross-functional teams to shape both product direction and business strategy. Sharing backend expertise with the team while promoting best practices, along with strong cloud and infrastructure competence. Our main stack is TypeScript, Node.js, React, React Native running on Google Cloud Platform. How we think about building We’re pragmatic. We like speed, but we also care about building things that last. AI isn’t a side tool here. It’s embedded in how we work helping engineers move faster, reduce friction and focus on solving meaningful problems. We’re looking for engineers who are curious about that shift and want to be part of it, rather than people who feel like good engineering means doing everything the hard way. No ego. Just g
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: At Modal, we sell cloud services atop which our customers run their critical production systems. As a rapidly growing new cloud infrastructure company, we seek to improve our reliability dramatically while scaling the size of our platform, customer base, and our team. This role is for people who are deep systems thinkers, love stacking nines, and thrive from making others move faster at scale. Responsibilities include: Identifying architectural changes to improve reliability and performance. Fostering a culture of reliability across Modal’s engineering organization. Defining and implementing operational processes such as deployments, upgrades, etc. Operating systems like Kubernetes, Postgres, Redis, etc. Participating in on-call rotations, and responding to production incidents. Requirements: 5+ years of experience writing high-quality production code. 2+ years of on-call experience for critical p
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
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