Senior Research Engineer Intern Fall 2026 Jobs

About the Team The Future of Computing Research team is an Applied Research team within the Consumer Devices group focused on developing new methods and models as we advance forward in our mission of building AGI that benefits all of humanity. As a Software Engineer on the Future of Computing Research team, you will work together with both the best ML researchers in the world and the greatest design talent of our generation to push the frontier of model capabilities. About the Role We are looking for a Software Engineer to join our team to build tools and services that enable AI research, evaluation, and data generation workflows. The best work in this role will start with an ambiguous design question and turn it into working research systems. You will work closely with researchers, designers, and engineers to build the evaluation systems, synthetic data generation pipelines, review tools, and supporting platform services. The goal is to make these workflows easier to create, run, and trust without requiring bespoke engineering support for each new design concept. You will help ensure that research artifacts have a clear lifecycle, runs are reproducible and observable, and results provide useful evidence for product and model-training decisions while the underlying systems remain reliable and reusable. This role is based in San Francisco, CA. We use a hybrid work model of three days in the office per week and offer relocation assistance to new employees. In this role, you will: Build web applications, APIs, data models, and backend services for AI research workflows. Build tools to author and manage evaluation tasks, rubrics, graders, suites, and rollout configurations, including workflows for publishing, versioning, auditing, and sharing research artifacts. Automate evaluation runs and generate useful reports for design, research, and engineering teams. Support synthetic data generation workflows for multimodal and conversational research, including tools that comb

Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with leading enterprises and government organizations to accelerate their AI initiatives through our data annotation platform, generative AI solutions, and enterprise AI capabilities. About the General Agents Team The General Agents team, part of Scale’s Enterprise organization, builds robust general agents for customer use cases and applications. The team sits at the intersection of frontier agent development and real-world deployment, translating state-of-the-art reasoning and agentic capabilities into reliable, production-grade systems that drive real economic value. Our agents are scalable systems built around recurring enterprise problem domains, with a strong emphasis on generalization, extensibility, and deployment across many customers. About the Role As a Senior/Staff Machine Learning Engineer (MLE) on the General Agents team, you’ll play a critical role in designing, building, and deploying production-ready AI agents that solve high-impact enterprise problems. You will work across the full agent lifecycle—from model and system design to evaluation, deployment, and iteration—bridging cutting-edge agentic techniques with the constraints and requirements of real customer environments. You will: Design and implement end-to-end agent systems that combine LLM reasoning, tool use, memory, and control logic to solve recurring enterprise use cases. Build scalable, reliable agent architectures that can be deployed across many customers with varying data, tools, and constraints. Develop evaluation frameworks, datasets, environments, and metrics to measure agent performance, reliability, and business impact in production settings. Collaborate closely with product managers, customers, data annotators, and other engineering teams to translate enterprise requirements into robust agent designs. Productionize frontier agent techniques (e.g.,

Synthesia is the world’s leading AI video platform for business, used by over 90% of the Fortune 100. Founded in 2017, the company is headquartered in London, with offices and teams across Europe and the US. As AI continues to shape the way we live and work, Synthesia develops products to enhance visual communication and enterprise skill development, helping people work better and stay at the center of successful organizations. Following our recent Series E funding round, where we raised $200 million, our valuation stands at $4 billion. Our total funding exceeds $530 million from premier investors including Accel, NVentures (Nvidia's VC arm), Kleiner Perkins, GV, and Evantic Capital, alongside the founders and operators of Stripe, Datadog, Miro, and Webflow. About the role Synthesia's long-term vision is to build the best human-interactive models: systems that don't just talk to people, but perceive and respond to them, reacting to a user's actions and emotions, not only their words. Today over 60,000 businesses rely on our platform, and the next leap in what we can offer them depends on models that combine text, audio, and video into a single real-time interactive experience. As a Staff Research Engineer, you'll join the Voice team within our 40+ person R&D department, but your scope will extend well beyond voice. You'll help define and drive that broader vision across teams, proposing ambitious research directions and taking direct ownership of the design and implementation of its most critical components. You'll work directly with our voice lead and collaborate tightly with our video teams and other senior members of the org. Concretely, you'll work on voice to voice models that produce text and voice simultaneously. Models that can reason, interrupt the user with back channeling and talk. Models that feel like you are having a natural conversation with, without the feeling of turn taking that is dominant in current speech to speech models. Your role would be

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

As a Senior Software Engineer on Coder’s Agentic Engineering team, you’ll build and evolve the systems behind our agentic development experience. You’ll work across the agent harness, integrations, and workflows that connect agents with real development environments. You’ll stay hands-on, solve complex technical problems, and work closely with Product, Design, and other engineers to ship reliable agentic experiences. What you’ll do here Design and build production systems in Go, with work across React and TypeScript where needed. Improve agent execution, tool use, context management, streaming, and long-running workflows. Extend our provider-agnostic architecture as models and capabilities change. Build reliable integrations between agents, workspaces, tools, and developer infrastructure. Own projects from implementation through rollout and iteration. Contribute to design reviews, code reviews, and technical discussions. Partner with Product and Design to turn agent capabilities into useful developer experiences. Improve the reliability, performance, and operability of agentic systems. What we’re looking for Strong experience building and operating production software systems. Hands-on experience with Go. Experience with React and TypeScript. Experience building systems around LLMs or agentic workflows. Familiarity with model APIs, tool calling, context management, or agent loops. Good understanding of distributed systems and production reliability. Working knowledge of AWS. Strong problem-solving skills and comfort working through technical ambiguity. Someone who contributes beyond their own code through reviews, collaboration, and knowledge sharing. Bonus tacos if you have Experience building coding agents, developer tools, or cloud development environments. Experience with MCP, agent tools, or multi-agent systems. Experience with remote execution, sandboxing, or isolated compute. Experience building integrations across multiple model providers. Experience with AW

As a Senior Software Engineer on Coder’s Agentic Engineering team, you’ll build and evolve the systems behind our agentic development experience. You’ll work across the agent harness, integrations, and workflows that connect agents with real development environments. You’ll stay hands-on, solve complex technical problems, and work closely with Product, Design, and other engineers to ship reliable agentic experiences. To provide substantive overlap with the team, this position must be in Eastern Time. What you’ll do here Design and build production systems in Go, with work across React and TypeScript where needed. Improve agent execution, tool use, context management, streaming, and long-running workflows. Extend our provider-agnostic architecture as models and capabilities change. Build reliable integrations between agents, workspaces, tools, and developer infrastructure. Own projects from implementation through rollout and iteration. Contribute to design reviews, code reviews, and technical discussions. Partner with Product and Design to turn agent capabilities into useful developer experiences. Improve the reliability, performance, and operability of agentic systems. What we’re looking for Strong experience building and operating production software systems. Hands-on experience with Go. Experience with React and TypeScript. Experience building systems around LLMs or agentic workflows. Familiarity with model APIs, tool calling, context management, or agent loops. Good understanding of distributed systems and production reliability. Working knowledge of AWS. Strong problem-solving skills and comfort working through technical ambiguity. Someone who contributes beyond their own code through reviews, collaboration, and knowledge sharing. Bonus tacos if you have Experience building coding agents, developer tools, or cloud development environments. Experience with MCP, agent tools, or multi-agent systems. Experience with remote execution, sandboxing, or isolated compute.

We’re looking for a Software Engineer to help shape AI governance for developer tooling at Coder. This role sits on our AI Governance team, which builds and maintains two enterprise-grade components of Coder's AI governance stack. AI Gateway is a centralized LLM gateway that sits between coding agents and providers such as OpenAI or Anthropic, providing organizations with audit trails, token tracking, cost control, and centralized authentication. Agent Firewall wraps those agents with default-deny network policies, controlling which domains and methods they can reach inside workspaces. This team works across the full stack - from Go backend and React frontend, to integrating with LLM provider APIs. Day to day, you'll be shipping features, hardening security boundaries, collaborating with enterprise customers on real-world policy needs, and contributing to Coder's open-source ecosystem. What you'll do here Design and build product features that push the standard for remote development in self-hosted environments Create and improve upon popular open source projects that integrate with VS Code, JetBrains, and other developer tools Champion best practices to both internal team members and external contributors Collaborate with Product and Design teams at Coder, as well as with partners like JetBrains, to execute key product integrations Document the design, implementation, and operations of systems for knowledge sharing within the team Work alongside Customer Success teams to support Coder’s enterprise user base Work with cutting-edge AI technologies to create seamless, painless developer experiences Rapidly iterate from prototype to implementation in a highly adaptive, reactive team environment What we're looking for 3+ years of full-stack experience writing code in a professional setting, with 1+ year(s) writing Go (ideally in current or most recent position) Proficiency in building distributed systems in Go Excellent verbal and written communication skills Exceptiona

As a Senior Backend Engineer on Coder's Enterprise Experience team, you'll build the systems that help large organizations run Coder in production with confidence. You'll improve how Coder scales, how it's upgraded, and how reliably it performs in regulated, air-gapped, and enterprise environments. You'll work on a genuinely cross-functional team of backend, platform, and QA engineers who own the end-to-end experience for Coder operators. From designing new features to evolving Coder's architecture, you'll partner across engineering and product to solve complex problems and ship software that operators trust. What you'll do here Design and build new features end to end, from technical design through production rollout. Design and implement backend architecture changes that support Coder's long-term scalability goals. Investigate and resolve scalability bottlenecks under production-like load, from database access patterns to concurrency handling in coderd. Improve database migration safety and upgrade reliability through schema compatibility, background migrations, and safe rollback strategies. Own the backend side of issues surfaced by Coder operators and administrators. Document the design, implementation, and operational tradeoffs of the systems you build. Participate in code reviews, RFC-style design discussions, and on-call rotations for the services you own. What we're looking for 5+ years of professional software engineering experience, including significant production experience with Go. Deep understanding of Go's concurrency model, including goroutines, channels, the sync package, and debugging race conditions under real-world load. Experience designing and operating relational databases in production, including schema design, migrations, and transactions. Strong verbal and written communication skills. Exceptional debugging and troubleshooting skills, with the persistence to drive complex problems to resolution. A self-motivated, analytical engineer who enj

Since 2003, Entrata has evolved from a visionary, student-led startup into a global leader in AI-driven property management technology. Today, we power the industry's most essential operating system, serving owners and residents worldwide through a comprehensive suite of intelligent leasing, payment, and communication tools powered by cutting-edge AI. With a proven track record of sustained growth and a global team of more than 2,200 employees, we offer the rare combination of established stability and high-velocity innovation. Recognized by the Silicon Slopes Hall of Fame and the Utah Business Fast 50, Entrata fosters a culture of radical transparency and entrepreneurial energy. At Entrata, we create an environment where different perspectives are valued and respected. Those perspectives challenge assumptions, strengthen our decisions, and raise the bar as we reshape the global living experience through AI-powered solutions. We are seeking a Senior Machine Learning Engineer to help build and scale Entrata’s applied AI capabilities. This role will focus on adapting and fine-tuning foundation models for property management use cases, building reliable model training and evaluation pipelines, and deploying AI systems into production.

Coder builds enterprise software that keeps developers in flow. As a Senior Customer Support Engineer, you will help customers solve complex technical issues, get unstuck faster, and build with confidence. You will work closely with Product, Customer Success, and Enterprise Account Managers to resolve urgent issues, improve support workflows, and turn customer feedback into better product experiences. This is a highly visible role on a growing team, with direct impact on how customers experience Coder. What you’ll do here Reproduce and debug customer issues using existing tools, test environments, or custom reproduction setups Solve incoming technical support requests in a timely manner, including urgent, high-severity cases Communicate clearly and tactfully with customers throughout the support lifecycle Gather context, provide diagnostic steps, share resolution guidance, and follow up after issues are resolved Identify and communicate product usage trends, bugs, and feature requests Collaborate with Enterprise Account Managers to schedule, coordinate, and lead customer debugging calls Document customer activity in accordance with internal and external security standards Guide and mentor new team members on support processes and procedures Contribute to product documentation, customer knowledge base articles, and best practice guides Improve support processes, tools, and workflows in collaboration with the broader team Participate in a periodic on-call rotation for production-down issues What we’re looking for 5+ years of customer support engineering experience, or a comparable customer-facing technical role, preferably with critical software products 5+ years of experience supporting enterprise customers 2+ years of experience diagnosing production network connectivity and performance issues Strong problem-solving, analytical, and troubleshooting skills Clear, thoughtful communication skills, both verbal and written Experience with Terraform Experience with major

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 a billion rides per year and counting, Lyft is solving hard problems in a rapidly growing domain with a lot of data and creative solutions in Rider, Marketplace, Growth, and beyond. While traditional approaches to optimization and problem decomposition are sufficient to disrupt transportation, building a next-generation platform for low-cost, ultra-immersive transportation to improve people's lives warrants modern ML utilizing peta-byte scale data. Our highly motivated Machine Learning Engineers work on these challenging problems and define solutions to directly impact various aspects of our core business. If you are a critical thinker with experience in machine learning workflows and LLMs, passionate about solving business problems using data and working in a dynamic, creative, and collaborative environment, we are searching for you. We are seeking a Senior Machine Learning Engineer to join the Rider Applied AI team and lead the design, development, and deployment of state-of-the-art machine learning and artificial intelligence systems. This role requires a strategic thinker who can balance high-level system architecture with hands-on technical implementation. You will collaborate across teams to shape the future of ride-sharing by leveraging AI, Machine learning and Data science. Responsibilities: Model Development & Research: Design, build, and deploy machine learning models for real-time applications, including translating state-of-the-art research into production-ready solutions. System Design: Architect scalable, reliable ML pipelines that integrate seamlessly with existing backend systems. Innovation & Applied Research: Stay ahead of the curve by exploring emerging algorithms, technologies (such as LLMs and LLM-based applications), and frameworks — critically eva

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 a billion rides per year and counting, Lyft is solving hard problems in a rapidly growing domain with a lot of data and creative solutions in Rider, Marketplace, Growth, and beyond. While traditional approaches to optimization and problem decomposition are sufficient to disrupt transportation, building a next-generation platform for low-cost, ultra-immersive transportation to improve people's lives warrants modern ML utilizing peta-byte scale data. Our highly motivated Machine Learning Engineers work on these challenging problems and define solutions to directly impact various aspects of our core business. If you are a critical thinker with experience in machine learning workflows and LLMs, passionate about solving business problems using data and working in a dynamic, creative, and collaborative environment, we are searching for you. We are seeking a Senior Machine Learning Engineer to join the Rider Applied AI team and lead the design, development, and deployment of state-of-the-art machine learning and artificial intelligence systems. This role requires a strategic thinker who can balance high-level system architecture with hands-on technical implementation. You will collaborate across teams to shape the future of ride-sharing by leveraging AI, Machine learning and Data science. Responsibilities: Model Development & Research: Design, build, and deploy machine learning models for real-time applications, including translating state-of-the-art research into production-ready solutions. System Design: Architect scalable, reliable ML pipelines that integrate seamlessly with existing backend systems. Innovation & Applied Research: Stay ahead of the curve by exploring emerging algorithms, technologies (such as LLMs and LLM-based applications), and frameworks — critically eva

Overview: Guidepoint seeks an experienced Data/AI Engineer as an integral member of the Toronto-based AI team. The Toronto Technology Hub serves as the base of our Data/AI/ML team, dedicated to building a modern data infrastructure for advanced analytics and the development of responsible AI. This strategic investment is integral to Guidepoint’s vision for the future, aiming to develop cutting-edge Generative AI and analytical capabilities that will underpin Guidepoint’s Next-Gen research enablement platform and data products. This role demands exceptional leadership and technical prowess to drive the development of next-generation research enablement platforms and AI-driven data products. You will develop and scale Generative AI-powered systems, including large language model (LLM) applications and research agents, while ensuring the integration of responsible AI and best-in-class MLOps. The Senior AI/ML Engineer will be a primary contributor to building scalable AI/ML capabilities using Databricks and other state-of-the-art tools across all of Guidepoint’s products. Guidepoint’s Technology team thrives on problem-solving and creating happier users. As Guidepoint works to achieve its mission of making individuals, businesses, and the world smarter through personalized knowledge-sharing solutions, the engineering team is taking on challenges to improve our internal application architecture and create new AI-enabled products to optimize the seamless delivery of our services. This is a hybrid position based in Toronto. What You'll Do: Architect and Build Production Systems: Design, build, and operate scalable, low-latency backend services and APIs that serve Generative AI features, from retrieval-augmented generation (RAG) pipelines to complex agentic systems. Own the AI Application Lifecycle: Own the end-to-end lifecycle of AI-powered applications, including system design, development, deployment (CI/CD), monitoring, and optimization

Work Flexibility: Hybrid What you will do: • Under minimal supervision, research, design, develop, modify, and verify components/modules for medical devices; translate design inputs to engineering specifications and produce sub-system level designs and develop and analyze solutions, prototyping one or more options to provide proof of concept. • Apply fundamental and some advanced concepts, practices and procedures for problem solving • Demonstrate advanced understanding of customer needs and design inputs; proficiency with product’s intended use and clinical procedures and learn how the financial models are constructed • Follow fundamental industry standards, design requirements and test strategies which apply to regulatory requirements • Independently create or refine engineering documentation, such as the Design History file and follow R&D procedure like design controls and risk management, per the Quality Management System • Under minimal supervision, work with R&D, Quality, Manufacturing, Regulatory, Clinical, Marketing and Project Management to ensure project success • Quickly process and assimilate procedures, policies, processes, systems, and technology required and work on complex problems, applying advanced experience and learnings • Demonstrate ownership and prioritize work with minimal supervision and works as key member of the team, collaborating with others and solidifying relationships Required Qualifications : Bachelor of Science in Engineering, Mechanical Engineering or BioMedical & 2+ years of work experience Experience- 4.5 years- 7 years CAD expertise Conceptual knowledge(basics should be clear); Manufacturing drawing; Mechanical Design; GD&T Preferred Qualifications : Working knowledge and under

About Us: Blockworks is an information platform that sits at the center of the crypto industry. We transform raw, complex data and facts into actionable research, trusted alpha-driven insights, and world-class events. The result is transparency and confidence. Blockworks connects investors and businesses in onchain capital markets. We give businesses a platform to earn trust and provide investors with the information they need to underwrite the asset class. Who You Are: Software engineering is your passion, and you have special talents focused on data architecture, design, and API development. You are a player-coach and a natural leader who understands the technical and human elements that go into great software design. You have a results-oriented attitude and a passion for delivering flawless releases and developing digital product pipelines (CI/CD pipelines). You have a proven track record facilitating engineering teams to increase productivity and quality. You're excited at the possibility of helping design and develop our data pipelines as well as leading our data-related projects and strategies for Blockwork's suite of projects. You love moving quickly in a fast-paced start-up, but you also bring intentionality, sustainability and scalability to your approach as an engineer. What You’ll Do: As our Senior Data Engineer , you will be directly responsible for leading the creation and execution of our data models and strategies that feed our products. You'll work collaboratively with other members of the engineering team to design, develop, implement, and evolve our data pipeline and approaches. Every day will look a little different, but in general, you will do things like: Own Data Sourcing Pipelines: You'll be responsible for helping to architect our data warehousing, ingestion and sourcing strategy, working with multiple SDKs to aggregate data from various sources into Blockwork's own data warehouse. Design and Implement ETL Solutions: You'll be responsible for