Content Producer Jobs

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. Portal, part of Roblox’s Engine Productivity team, builds productivity tools for the hundreds of engineers developing Roblox’s game engine, desktop clients, apps, and Roblox Studio. As a Senior Software Engineer, you will build the systems that bring AI agents into engine development workflows. On a small team with broad reach, you will help decide where AI can meaningfully improve engineering productivity and take solutions from early experiments to reliable tools engineers use every day. You will: Own improvements to developer workflows, from identifying problems with engineers to designing and shipping productivity tools and measuring their impact. Build AI agent sandboxes and harnesses written in C and Rust, along with the integrations and context agents needed to work effectively in Roblox’s C++ game engine codebase. Partner with technical leaders across Roblox’s Engine and Infrastructure groups to deliver reliable tools and improve the daily experience of engineering at Roblox. You have: 5+ years of software engineering experience working on projects from 0 to 1. Experience owning substantial parts of a developer tool or system through design, launch, and ongoing operation. Systems pr

About the Team Come help us build and develop tools serving hundreds of engineers internally! We’re looking for a Fullstack Software Engineer to join our Developer Insights team. About the Role Our mission is to improve the developer experience of engineers at DoorDash by building various internal products, including our internal developer portal, Developer Insights. Our success as a platform team depends on the success of the product teams we serve. Because of this, we invest in building a strong community that encourages participation and promotes best practices. You’re excited about this opportunity because you will… Introduce cutting edge technologies to our engineering organization, including tools built on LLMs Build new features for Developer Insights (using Backstage.io) Improve the developer experience for all of our engineers Work and collaborate across team boundaries. Contribute features and bug fixes to upstream open-source projects. Mentor and educate your peers. Lead the team in a technical fashion and assist in roadmap planning and measurement of existing features. Represent the team at large in OKR and engineering all-hands presentations. Context switch from frontend to backend to data depending on the need that arises. We’re excited about you because… You have at least 2 years of experience in web technologies using Typescript with React on the frontend with Java, Kotlin, Python or Go backend experience. You have a product mindset and apply that to how you would build out platform services. You love systems and software, and you're proficient in both. You’re curious and dive deep into different system architectures. You are an organized and excellent written and verbal communicator. You have proficiency in using AI coding tools (e.g., Claude Code, Codex, Cursor) in the full software development lifecycle, including designing, generating code, testing, monitoring and releasing software Compensation The successful candidate’s starti

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 Cloud Security Engineer for the InfoSec team in Brazil ! We are looking for an experienced security engineer to lead our cloud security strategy across multi-cloud environments (AWS & GCP). You will drive our Zero Trust architecture, embed a Shift-Left security culture within engineering teams, secure containerized and serverless workloads, and pioneer security controls for emerging Artificial Intelligence deployments—including Agentic AI systems, Model Context Protocol (MCP), Retrieval-Augmented Generation (RAG) architectures, AI guardrails, and mitigations against OWASP Top 10 for LLMs and MITRE ATLAS framework threats. This position is for the Cloud Security team. The Cloud Security Engineer is responsible for designing, implementing, and managing security measures in cloud computing environments to protect data, applications, infrastructure, and services against potential threats and vulnerabilities. YOUR IMPACT Architect and govern cloud security controls across AWS and GCP environments following Zero Trust principles; Embed automated security testing and threat modeling directly into CI/CD pipelines to champi

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. 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 an AI Reimagination Engineer in Micron's Generative AI Center of Excellence (GenAI COE), you have an outstanding chance to transform how businesses function. You will partner with different business areas to break down large, manual, multi-step processes and redesign them into effective, autonomous systems. This position combines process reimagination with AI systems engineering, making you a key part of the transformation journey. You will collaborate closely with the GenAI COE, IT architecture, security, and project teams. You will lead projects from the initial redesign to the final build, delivering solutions that business teams can adopt and scale. Responsibilities: Decompose end-to-end processes: Map current-state flows, quantify effort and risk, and lead eliminate/simplify/agentify analysis before automation. Architect the agentic solution: Build future-state flows and AI architecture, including task and agent decomposition, orchestration patterns, tool and data access, memory and context strategy, and human-in-the-loop controls. Translate inventions into buildable soluti

MongoDB is the modern database platform and consistently voted the #1 most wanted database , preferred by developers. MongoDB continues to attract the most demanding and innovative companies and development teams in enterprise software. To support this growth, we are expanding our Industry Solutions Team (IST), a flexible, globally distributed organization that helps customers and partners modernize applications and data platforms with MongoDB. As a Forward Deployed Engineer in our Industry ISV Practice, you will work directly with independent software vendors (ISVs) and their engineering organizations to build MongoDB capabilities into their products. You will work in the partner’s codebase, languages, engineering practices, and release process to deliver production-ready integrations, migrations, and product capabilities. The solutions you help build should leave the partner with maintainable code and knowledge, while creating reusable patterns that can accelerate future partner engagements. This is a hands-on application engineering role. You will spend time understanding existing products built on relational databases, designing practical MongoDB approaches, writing production code, and working alongside partner engineers through implementation and rollout. The role requires regular travel and time on-site with ISV partners during key phases of the engagement. We are looking to speak to candidates who are based in Gurugram for our hybrid working model. What you’ll do at MongoDB In this role, you will Embed with ISV engineering teams, adapting to their codebase, practices, release cadence, and constraints while understanding their product architecture, industry context, data model, and deployment environment Design and build MongoDB-backed product capabilities, including integrations, data models, indexes, queries, persistence layers, migration tooling, and support for MongoDB alongside relational database editions Design and implement coexistence and migra

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. With over half a billion rides and counting, Lyft is solving hard problems in a flourishing domain with a lot of data and creative solutions in Marketplace, Mapping, Fraud, Growth and beyond. We're actively building the next-generation Machine Learning (ML) platform for low-cost, ultra-immersive transportation to improve people’s lives using modern ML with peta-byte scale data. Our Machine Learning Engineers are excited to work on these challenging problems and redefine solutions to directly impact various aspects of Lyft's primary business. If you are a student with experience in machine learning workflows, passionate about solving challenging problems using data and working in a dynamic, creative, and collaborative environment, this opportunity is for you! Responsibilities: Contribute to the design, build, train and test of Machine Learning models Write production-level code to convert ML models into working pipelines Partner with Product Managers, Data Scientists, and fellow ML Engineers to frame Machine Learning problems within the business context Analyze experimental and observational data, communicate findings to support decisions Participate in code and spec reviews to ensure code quality and distribute knowledge Experience: Currently pursuing a Bachelor's, Master's, or PhD degree in Computer Science or a related technical field from a university in Canada (required) , with a graduation date between December 2027 and Summer 2028 (required). For any candidates who are master's students who worked between their bachelor's and master's programs: candidates should also have less than 2 years of relevant full-time work experience Available during Summer 2027 for the internship in Toronto Good understanding and knowledge of ML libraries like scikit-learn, Tensorflow, PyTorch, Keras, MXNet, et

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. With over half a billion rides and counting, Lyft is solving hard problems in a flourishing domain with a lot of data and creative solutions in Marketplace, Mapping, Fraud, Growth and beyond. We're actively building the next-generation Machine Learning (ML) platform for low-cost, ultra-immersive transportation to improve people’s lives using modern ML with peta-byte scale data. Our Machine Learning Engineers are excited to work on these challenging problems and redefine solutions to directly impact various aspects of Lyft's primary business. If you are a student with experience in machine learning workflows, passionate about solving challenging problems using data and working in a dynamic, creative, and collaborative environment, this opportunity is for you! Responsibilities: Contribute to the design, build, train and test of Machine Learning models Write production-level code to convert ML models into working pipelines Partner with Product Managers, Data Scientists, and fellow ML Engineers to frame Machine Learning problems within the business context Analyze experimental and observational data, communicate findings to support decisions Participate in code and spec reviews to ensure code quality and distribute knowledge Experience: Currently pursuing a Bachelor's, Master's, or PhD degree in Computer Science or a related technical field from a university in Canada (required) , with a graduation date between December 2027 and Summer 2028 (required). For any candidates who are master's students who worked between their bachelor's and master's programs: candidates should also have less than 2 years of relevant full-time work experience Available during Summer 2027 for the internship in Toronto Good understanding and knowledge of ML libraries like scikit-learn, Tensorflow, PyTorch, Keras, MXNet, et

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Lyft’s Data Science Team builds mathematical models underpinning the platform’s core services. Compared to other technology companies of a similar size, the set of problems that we tackle is incredibly diverse. They cut across optimization, prediction, modeling, inference, transportation, and mapping. We're looking for Masters or PhD students who are passionate about solving mathematical problems with data and are excited about working in a fast-paced, innovative and collegial environment. We are hiring for a variety of Data Science interns, focusing on the following specialties: Optimization: Construct and fit statistical or optimization models that facilitate automated decision making in the app. Machine Learning: Design, build, tune, and deploy machine learning models with a special emphasis on feature engineering and deployment. Inference: Design and analyze tests in our dynamic marketplace, estimating statistical and ML models to enable better decisions, and developing and evaluating algorithmic policies in our pricing, dispatch, and incentives systems. You will report into a Science Manager. Responsibilities: Partner with Engineers, Product Managers, and other cross-functional partners to frame problems, both mathematically and within the business context Perform exploratory data analysis to gain a deeper understanding of the problem Write production modeling code; collaborate with software engineers to implement algorithms in production Design and run both simulated and live traffic experiments Analyze experimental and observational data; communicate findings including working with partner teams and presentations; facilitate launch decisions Experience: Currently pursuing a Masters or PhD degree at a university in Canada (required) in mathematical sciences ( Opera

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Lyft’s Data Science Team builds mathematical models underpinning the platform’s core services. Compared to other technology companies of a similar size, the set of problems that we tackle is incredibly diverse. They cut across optimization, prediction, modeling, inference, transportation, and mapping. We're looking for Masters or PhD students who are passionate about solving mathematical problems with data and are excited about working in a fast-paced, innovative and collegial environment. We are hiring for a variety of Data Science interns, focusing on the following specialties: Optimization: Construct and fit statistical or optimization models that facilitate automated decision making in the app. Machine Learning: Design, build, tune, and deploy machine learning models with a special emphasis on feature engineering and deployment. Inference: Design and analyze tests in our dynamic marketplace, estimating statistical and ML models to enable better decisions, and developing and evaluating algorithmic policies in our pricing, dispatch, and incentives systems. You will report into a Science Manager. Responsibilities: Partner with Engineers, Product Managers, and other cross-functional partners to frame problems, both mathematically and within the business context Perform exploratory data analysis to gain a deeper understanding of the problem Write production modeling code; collaborate with software engineers to implement algorithms in production Design and run both simulated and live traffic experiments Analyze experimental and observational data; communicate findings including working with partner teams and presentations; facilitate launch decisions Experience: Currently pursuing a Masters or PhD degree at a university in Canada (required) in mathematical sciences ( Opera

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Lyft’s Data Science Team builds mathematical models underpinning the platform’s core services. Compared to other technology companies of a similar size, the set of problems that we tackle is incredibly diverse. They cut across optimization, prediction, modeling, inference, transportation, and mapping. We're looking for Masters or PhD students who are passionate about solving mathematical problems with data and are excited about working in a fast-paced, innovative and collegial environment. We are hiring for a variety of Data Science interns, focusing on the following specialties: Optimization: Construct and fit statistical or optimization models that facilitate automated decision making in the app. Machine Learning: Design, build, tune, and deploy machine learning models with a special emphasis on feature engineering and deployment. Inference: Design and analyze tests in our dynamic marketplace, estimating statistical and ML models to enable better decisions, and developing and evaluating algorithmic policies in our pricing, dispatch, and incentives systems. You will report into a Science Manager. Responsibilities: Partner with Engineers, Product Managers, and other cross-functional partners to frame problems, both mathematically and within the business context Perform exploratory data analysis to gain a deeper understanding of the problem Write production modeling code; collaborate with software engineers to implement algorithms in production Design and run both simulated and live traffic experiments Analyze experimental and observational data; communicate findings including working with partner teams and presentations; facilitate launch decisions Experience: Currently pursuing a Masters or PhD degree in mathematical sciences ( Operations Research, Computer Science, Statistic

Our vision is to transform how the world uses information to enrich life for all. Join an inclusive team passionate about one thing: using their expertise in the relentless pursuit of innovation for customers and partners. The solutions we build help make everything from virtual reality experiences to breakthroughs in neural networks possible. We do it all while committing to integrity, sustainability, and giving back to our communities. Because doing so can fuel the very innovation we are pursuing. Responsibilities and Tasks Product Quality (PQ) Predictive Solutions: Build and productionize machine learning models (classification and regression) to support predictive and prescriptive analytics across semiconductor test and manufacturing processes. Agentic AI and LLM Development: Contribute to the design and implementation of multi-agent systems for PQ workflows, including code generation, automated troubleshooting, and process optimization. Work with retrieval-augmented generation (RAG) pipelines: identify data sources, develop retrieval strategies, and improve context quality for LLM-based applications. Assist in implementing tool-using capabilities, function calling, and agent memory systems. Software Engineering and Productionalization: Develop maintainable code and analytical pipelines suitable for high-volume manufacturing environments. Optimize for performance, latency, and token efficiency. Collaborate with senior team members on testing, deployment, and monitoring. Communicate analytical insights, model behavior, and results clearly to technical and non-technical stakeholders Integ

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 an AI Full Stack Engineer, you will be responsible for designing, developing, deploying, and supporting AI-enabled applications and enterprise solutions across the full technology stack. You will collaborate closely with business partners, product teams, and fellow engineers to translate business needs into scalable, reliable, and maintainable solutions while advancing the adoption of AI-enabled software engineering practices. Responsibilities include, but are not limited to: Design, build, test, deploy, and operate full-stack software solutions supporting business and manufacturing operations. Own solutions end-to-end, including system architecture, implementation, testing, observability, deployment, operational support, and lifecycle management. Collaborate with business stakeholders to gather requirements and translate them into scalable technical solutions. Contribute to platform enablement, architecture decisions, code reviews, and engineering best practices. Design and implement custom AI agents to automate tasks, orchestrate workflows, provide decision support, enable summarization capabilities, and perform multi-step reasoning. Build and integrate systems using Model Context Protocol (MCP) to enable structured interactions between AI models, tools, agents, and enterprise systems. Develop and integrate AI-powered solutions utilizing Large Language Models (LLMs), enterprise search, embeddings, APIs, and Retr

Ready to do the most impactful work of your career? At Coinbase , we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn't a place for complacency, it’s a place to be pushed past your perceived limits. If you're ready to build the future of finance alongside people who refuse to settle for "good enough," you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called “surges.” learn more about working at Coinbase . As a Senior Software Engineer on the Blockchain Networks team within the Platform group, you'll build the critical infrastructure that integrates blockchain protocols with Coinbase's internal services for new assets, stablecoins, and staking. This team translates complex blockchain operations and state machines into simple, reliable APIs that product teams across Coinbase depend on. You'll own multi-quarter technical initiatives and ship platform primitives that directly improve the latency, reliability, and cost of our crypto stack. What you'll do: Own the design and delivery of blockchain network infrastructure that abstracts blockchain complexity into reliable, platform APIs Lead multi-quarter initiatives including new chain integrations, re-architecture efforts, and data migrations that improve system latency, reliability, and cost Define and maintain APIs, SLOs, and observability for the systems you build, including on-call ownership Partner with product and platform teams to establish data contracts and ship SDKs and platform primitives that drive adoption across Coinbase Build deep technical context across multiple top blockchain protocols (e.g., Bitcoin, Ethereum) and apply that knowledge to simplify cross-chain operations Required Skills and Experience: 5+ years of software engineering experience, with demonstrated ownership of production services in a servi

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 As a Software Engineer, Forward Deployed, you’ll solve the hardest problems standing between Ramp and the world’s largest and most complex companies — shaping and shipping the product capabilities that unlock our growth upmarket. You'll be part of our Core FDE org, which is an agent-first, high-pace, customer-facing engineering team. On FDE, you will interact directly with customers and deliver solutions end to end — understanding pain points, shaping product decisions, and building agents that autonomously expand Ramp's capabilities. Check out our Engineering Blog and FDE post for more context on our work! What You’ll Do Deliver software end to end that meet the needs of our largest customers — understanding user pain points, scoping product specs, and building agents that autonomously implement solutions. Collaborate closely with Sales, Solutions, Customer Success, and Account Management to close deals, activate customers, and expand the value Ramp provides over time. Drive the core product engineering roadmap through our embedding

About PostHog Product development used to mean manually writing code, running analysis, diagnosing bugs, and rolling out changes using dozens of tools. PostHog makes products self-driving . It's the only platform that acts like a co-pilot for you (and your AI agents) to do it all – autonomously. We started with open-source product analytics, launched out of Y Combinator's W20 cohort . We've since shipped more than a dozen products , including: PostHog Desktop , the only AI devtool that understands your product, not just your codebase. A built-in data warehouse , so users can query product and customer data together using custom SQL insights. PostHog AI , an AI-powered analyst that answers product questions, helps users find useful session recordings, and writes custom SQL queries. We are: Product-led . More than 450,000 organizations have installed PostHog, mostly driven by word-of-mouth. We have intensely strong product-market fit. Default alive . Revenue is growing incredibly quickly, and we're very efficient. We raise money to push ambition and grow faster, not to keep the lights on. Well-funded. We've raised more than $180m from some of the world's top investors. We're set up for a long, ambitious journey. We're focused on building an awesome product for end users, hiring exceptional teammates, shipping fast, and being as weird as possible . Things we care about Transparency: Everyone can read about our roadmap, how we pay (or even let go of) people, our strategy, and how we work, in our public company handbook . Internally, we share revenue, notes and slides from board meetings, and fundraising plans, so everyone has the context they need to make good decisions. Autonomy: We don’t tell anyone what to do. Everyone chooses what to work on next based on what's going to have the biggest impact on our customers, and what they find interesting and motivating to work on. Engineers lead product teams and make product decisions . Teams are flexible and easy to change wh