Engineer 3 Jobs

MongoDB seeks an experienced Software Engineer to help level up IT and launch a new engineering team. This team will work alongside the Internal Engineering department, building enterprise-grade software to enable coworkers to be more effective and efficient. As a Software Engineer, you’ll be contributing to internal tools and platforms, helping design, build, and maintain software that supports critical workflows across the organization. Our ideal candidate Has 2-5 years of professional software engineering experience Experience with a modern programming language (Python, Go, Rust, etc.) Excellent communication skills and a strong desire to solve complex technical problems Comfortable working with modern infrastructure and delivery systems, including containerized applications, Kubernetes, and CI/CD tooling (e.g., Drone.io or similar) Collaborative, detail-oriented, and passionate about developing usable software Bonus Round Experience building full-stack applications, from front-end UIs to backend API handlers to DB migrations Knowledge of any of the following technologies: Next.js, FastAPI, React Position Expectations Build and maintain internal tools and platforms to improve workflows and efficiency Write clean, maintainable code to fix bugs and add new features Collaborate with other engineers and teams to prioritize work and deliver high-impact solutions Success Measures In three months, gain familiarity with internal platforms and workflows, contributing meaningfully to ongoing projects In three months, reduce manual friction for internal processes by delivering functional features or improvements In six months, implement tooling or enhancements that significantly improve internal engineering efficiency and productivity About MongoDB MongoDB is built for change, empowering our customers and our people to innovate at the speed of the market. We have redefined the data platform for the AI era, enabling builders to create, transform, and disrupt industries with

We’re looking for a Software Engineer 3 to help bring Voyage’s embedding models - used for semantic search, retrieval, and AI-native experiences; to the platforms and environments where customers already run their workloads, beyond first-party MongoDB Atlas. You’ll join the broader Search and AI Platform organization and collaborate closely with the engineers building Voyage’s first-party inference. Together, we’re extending that platform across cloud marketplaces, third-party inference providers, and self-managed deployments so customers get the same Voyage models, behaving consistently, wherever they choose to run them. As a Software Engineer 3, you'll focus on building the systems, tooling, and deployment workflows that power third-party model delivery. You'll own key components of how Voyage models are packaged, validated, and deployed, work across teams to ensure tight integration with the core inference platform, and contribute to delivery surfaces designed for reliability, observability, and ease of use. We are looking to speak to candidates who are based in Sydney for our hybrid working model. What you'll do Port and tune the model server that runs Voyage embedding and reranking models: improving inference performance, consistency, and runtime behavior across environments Productionize new Voyage models for delivery beyond first-party Atlas, owning the packaging, configuration, and deployment workflows that get them running on AWS, Azure, GCP and more Design correctness, correlation, and performance validation that proves third-party deployments match first-party behavior Build operability into every surface: structured logging, metrics, diagnostics, and health checks with tools like Prometheus and OpenTelemetry Debug problems that span model servers, containers, deployment configuration, and partner cloud environments Work alongside Voyage's model-serving teams, and partner with GTM, SAs, TSEs, and strategic customers on the hardest external deployments Who

We’re looking for a Software Engineer 3 to join our Marketing Technology Engineering team within Marketing Operations - Technology & Automation. This is a hands-on engineering role for someone who enjoys building reliable, scalable digital platforms and internal systems that improve how teams ship, measure, and optimize web experiences. You’ll work across application development, integrations, experimentation, data-informed decision making, and AI-enabled workflows that help the team move faster and deliver better outcomes. We are looking to speak to candidates who are based in Gurugram for our hybrid working model. What you’ll do Build and maintain production-quality software that powers martech experiences Design and implement backend services, internal tools, automations, and integrations across the martech ecosystem Improve system reliability, observability, maintainability, and developer experience across the team’s platforms Contribute to experimentation, personalization, and data workflows that support better customer and developer experiences Help evaluate and apply AI-enabled capabilities and tools where they can improve engineering velocity, quality, or user experience Participate in code reviews, technical design discussions, and team planning Take ownership of projects from implementation through rollout, monitoring, and iteration What we’re looking for 3+ years of professional software engineering experience building and supporting production systems Strong coding skills in one or more modern programming languages such as JavaScript or Python Experience building web applications, backend services, APIs, data pipelines, or internal platforms Solid understanding of software engineering fundamentals including testing, debugging, code quality, and maintainability Experience working with cloud services, CI/CD workflows, and modern development practices Ability to work across systems and collaborate effectively with cross-functional partners Strong writte

About the Role Adobe is seeking a Machine Learning Engineer to join the Adobe Genuine Engineering team. This group protects Adobe's ecosystem from fraud, abuse, and misuse using intelligent systems worldwide. In this position, you will build and develop machine learning models from scratch, including custom transformer-based frameworks, to identify fraudulent actions, stop account sharing, and protect the experience of hundreds of millions of users. You will manage the entire model lifecycle: raw behavioral data and feature engineering, architecture development, large-scale GPU training, deployment, and monitoring. The team is actively building in-house behavioral foundation models that learn identity-preserving representations from long sequences of user activity. This is a role for an engineer who wants to own deep learning systems end-to-end — not consume pre-built ones. Key Responsibilities Build and train deep learning models from scratch, including custom transformer and attention-based architectures for long behavioral event sequences. Own the full training stack: event tokenization, temporal and positional embeddings, self-supervised pretraining (e.g., masked modeling, contrastive learning), and downstream fine-tuning. Train large models efficiently on GPU infrastructure using mixed-precision training, gradient accumulation/checkpointing, efficient attention, and distributed strategies (DDP, FSDP, or equivalent). Build and optimize feature pipelines on Databricks and Spark, transforming raw behavioral events into high-quality model inputs. Translate prototypes into production ML systems — scalable, reliable, and observable — and drive inference performance through architectural and serving-side optimization. Contribute to MLOps practices: experiment tracking, model versioning, CI/CD, automated retraining, and

About the Role Adobe is seeking a Machine Learning Engineer to join the Adobe Genuine Engineering team. This group protects Adobe's ecosystem from fraud, abuse, and misuse using intelligent systems worldwide. In this position, you will build and develop machine learning models from scratch, including custom transformer-based frameworks, to identify fraudulent actions, stop account sharing, and protect the experience of hundreds of millions of users. You will manage the entire model lifecycle: raw behavioral data and feature engineering, architecture development, large-scale GPU training, deployment, and monitoring. The team is actively building in-house behavioral foundation models that learn identity-preserving representations from long sequences of user activity. This is a role for an engineer who wants to own deep learning systems end-to-end — not consume pre-built ones. Key Responsibilities Build and train deep learning models from scratch, including custom transformer and attention-based architectures for long behavioral event sequences. Own the full training stack: event tokenization, temporal and positional embeddings, self-supervised pretraining (e.g., masked modeling, contrastive learning), and downstream fine-tuning. Train large models efficiently on GPU infrastructure using mixed-precision training, gradient accumulation/checkpointing, efficient attention, and distributed strategies (DDP, FSDP, or equivalent). Build and optimize feature pipelines on Databricks and Spark, transforming raw behavioral events into high-quality model inputs. Translate prototypes into production ML systems — scalable, reliable, and observable — and drive inference performance through architectural and serving-side optimization. Contribute to MLOps practices: experiment tracking, model versioning, CI/CD, automated retraining, and

Principal Software Engineer - 3D Visualization (OpenGL) — 2 Locations. Apply via Workday.

We are Datadog's in-house product experts. The Technical Solutions team enables Datadog's worldwide growth by educating potential clients and ensuring that existing customers are happy and successful. Premier Support Engineers (PSEs) are primarily focused on assisting prospects and customers with any technical questions about Datadog. PSEs engage with Datadog’s Premier Customers via standard technical support channels, but are also involved with cadence calls, demos/presentations, conferences, and various side projects. You will work directly with Datadog’s Premier Customer base, and will be immersed in a fast-paced environment where you will be challenged, but will also immediately witness your contributions to Datadog and to our customers. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Respond to client requests (phone / chat / tickets) on our fast paced team while continuing to educate our clients on the use of the platform Develop relationships with our Premier Customers, working hand-in-hand to truly know their distinct environment Reproduce issues and dive into the 600+ integrations that Datadog works with Build out documentation and knowledge based articles for a variety of technology Drive product conversations based on needs and problems learned during client interactions Participate in routine health check meetings with Premier Customers Work from a Datadog office 3 - 5 days per week Who You Are: Experienced in multi-channel technical support at a SaaS company (5+ years of related experience) A tinkerer with some programming experience and a basic knowledge of Linux Self-motivated, detail-attentive, and have a desire for continuous learning A critical thinker who defaults to a client-centric approach A decision make

Java BPMN Development Engineer 3 — India - Chennai, Comcast India Engineering Cent. Apply via Workday.

Snowflake Data Governance Steward (Engineer 3) - FreeWheel — 12 Locations. Apply via Workday.

We are Datadog's in-house product experts. The Technical Solutions team enables Datadog's worldwide growth by educating potential clients and ensuring that existing customers are happy and successful. Premier Support Engineers (PSEs) are primarily focused on assisting prospects and customers with any technical questions about Datadog. PSEs engage with Datadog’s Premier Customers via standard technical support channels, but are also involved with cadence calls, demos/presentations, conferences, and various side projects. You will work directly with Datadog’s Premier Customer base, and will be immersed in a fast-paced environment where you will be challenged, but will also immediately witness your contributions to Datadog and to our customers. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Respond to client requests (phone / chat / tickets) on our fast paced team while continuing to educate our clients on the use of the platform Develop relationships with our Premier Customers, working hand-in-hand to truly know their distinct environment Reproduce issues and dive into the 600+ integrations that Datadog works with Build out documentation and knowledge based articles for a variety of technology Drive product conversations based on needs and problems learned during client interactions Participate in routine health check meetings with Premier Customers Work from a Datadog office 3 - 5 days per week Who You Are: Experienced in multi-channel technical support at a SaaS company (5+ years of related experience) A tinkerer with some programming experience and a basic knowledge of Linux Self-motivated, detail-attentive, and have a desire for continuous learning A critical thinker who defaults to a client-centric approach A decision maker but k

We are Datadog's in-house product experts. The Technical Solutions team enables Datadog's worldwide growth by educating potential clients and ensuring that existing customers are happy and successful. Premier Technical Support Engineers (PSEs) are primarily focused on assisting prospects and customers with any technical questions about Datadog. PSEs engage with Datadog’s Premier customers not only via standard technical support channels, but also get involved via cadence calls, business reviews, and side projects. You will be immersed in a fast-paced environment where you will be challenged, but will also immediately witness your contributions to Datadog and to our customers. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Respond to Premier customer requests (phone / chat / tickets) on our fast paced team while continuing to educate our clients on the use of the platform Develop relationships with our Premier customers, working hand-in-hand to understand their specific environment Reproduce customer issues and assist customers implementing 1,000+ Datadog integrations Handle urgent escalation requests that may result in customer-facing troubleshooting calls, and internal or external incident management Build subject matter expertise in many Datadog product areas Autonomously troubleshoot complex and/or high-priority customer issues without guidance Drive product and engineering conversations based on needs, use cases, and problems learned during client interactions Provide mentorship to junior members of the team and serve as their escalation partner Participate in routine health check meetings with Premier customers Build out and improve documentation and knowledge base articles for a variety of technologies Who You Are: Experienced in mul

We are Datadog's in-house product experts. The Datadog Federal Support Engineering team is dedicated to serving as highly trusted technical advisors for our Public Sector customers, who operate within some of the most highly regulated and security-constrained environments. These customers include various government agencies and organizations with critical, sensitive missions. As a Federal Support Engineer 3, this role places you at the forefront of supporting these customers' mission-critical workloads. These complex workloads are often deployed across sophisticated hybrid and multi-cloud architectures, requiring deep expertise in cloud technologies, monitoring, and security best practices. Your primary responsibility is to ensure the complete success of these customers across their entire lifecycle with Datadog. Whether you’re looking to learn from the best or be the best, the Federal Support team is dedicated to furthering personal development and team success. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Engage with public sector customers via multiple channels (ticketing system, live chat, calls, and screensharing tools) to identify and resolve technical support requests. Troubleshoot, investigate, and resolve complex technical issues in highly constrained environments across Datadog's 1000+ integrations, often with limited logs or sanitized data. Handle urgent escalation cases that may result in customer-facing troubleshooting calls, and internal or external incident management Become a subject matter expert in many Datadog product areas Partner with Product, Engineering, and Account teams to to validate bugs and advocate for customer-impacting improvements Provide mentorship to junior members of the team and serve

The Site Reliability Engineering team designs and builds the global infrastructure on which we deploy our services, focusing on the above mentioned flagship MongoDB Atlas platform. As our customers grow and globalize, our services must satisfy demands for low-latency requests around the globe, and comply with various data sovereignty requirements. The SRE Team’s mission is to build this increasingly complex infrastructure, while continually lowering the operational burden associated with it, and increasing our internal visibility into the health of the system. We are strong believers in infrastructure-as-code and self-healing systems. The SRE Team is fully integrated with all the other engineering teams, and the teams work closely together with a soft and traversable boundary between their areas of responsibility. We are looking to speak to candidates who are based in New York City for our hybrid working model. Responsibilities Design and build the infrastructure for a global cloud service that comprises hundreds of thousands of MongoDB clusters, processes a billion metrics per day, and replicates tens of billions of database writes to our backup service Design, implement, and troubleshoot the automation and monitoring of services that seamlessly spans the globe - including several cloud providers Become an expert in infrastructure performance, helping us optimize from the application level all the way through the firmware Build for resilience. Our goal is that nobody’s pager goes off, ever. Are we there yet? No. Are we really close? Very. While we work on that - participate in a weekly on-call rotation Improve our infrastructure capabilities, optimizing for cost, simplicity, and maintainability Requirements 3+ years of experience running a mission critical service at scale in a Linux environment Firm grasp of at least one modern programming language, beyond basic scripting Familiarity with web and network protocols and standards (HTTP, TLS, DNS, etc) Bachelor’s deg

About the Team OpenAI’s Hardware organization develops silicon and system-level solutions designed for the unique demands of advanced AI workloads. The team is responsible for building the next generation of AI-native silicon while working closely with software and research partners to co-design hardware tightly integrated with AI models. In addition to delivering production-grade silicon for OpenAI’s supercomputing infrastructure, the team also creates custom design tools and methodologies that accelerate innovation and enable hardware optimized specifically for AI. About the Role As an Engineer on our hardware optimization and co-design team, you will co-design future hardware from different vendors for programmability and performance. You will work with our kernel, compiler and machine learning engineers to understand their unique needs related to ML techniques, algorithms, numerical approximations, programming expressivity, and compiler optimizations. You will evangelize these constraints with various vendors to develop and influence future hardware architectures towards efficient training and inference on our models. If you are excited about efficiently distributing a large language model across devices, dealing with and optimizing system-wide/rack-wide networking bottlenecks and eventually tailoring the compute pipe and memory hierarchy of the hardware platform, simulating workloads at different abstractions and working closely with our partners, this is the perfect opportunity! This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. Key Responsibilities Co-design future hardware for programmability and performance with our hardware vendors Assist hardware vendors in developing optimal kernels and add support for it in our compiler Develop performance estimates for critical kernels for different hardware configurations and drive decisions on compute core and memory h

Software Security Compiler Engineer — 3 Locations. Apply via Workday.