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Production Tech Jobs

3,233 active opportunities · Updated for October 2026

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Explore current production tech jobs. Use filters to narrow by work mode, employment type, experience and date posted.

S
1mo ago

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. About the team The Apps & Experiences Platform team powers the systems and services behind all of our user-facing applications, including Snowsight, Snowflake Intelligence, and new mobile experiences. Our mission is to build innovative backend services, developer tooling, platform infrastructure, and AI-powered capabilities that enable exceptional product experiences at scale. As part of our team, you’ll work across feature development, platform engineering, infrastructure, and internal tooling to support both end users and developers. We care deeply about building systems that are reliable, scalable, maintainable, and performant. Snowflake is a high-growth AI Data Cloud company, and we’re looking for exceptional engineers to help us scale the next generation of our platform. A key part of this is our work on our internal AI developer agent, which is designed to fundamentally democratize end-to-end web app development across all engineering teams by translating product specs and designs into a fully functional, production-ready features. AS A SENIOR SOFTWARE ENGINEER FOR THE APPS & EXPERIENCES PLATFORM TEAM, YOU WILL: Design, build, and operate scalable backend services and platform infrastructure that power Snowflake’s user-facing applications. Contribute across th

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AG
1mo ago

The Shift Engineer - Cluster - IPQA conducts in-process quality inspections during shifts, monitoring production processes and identifying quality deviations. This role records and analyzes quality data, assists in implementing corrective actions, provides training on in-process quality procedures, and supports continuous improvement initiatives to enhance process quality. Source: Adani Group | Job ID: 55742

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AG
1mo ago

The Shift Engineer - Cluster - IPQA conducts in-process quality inspections during shifts, monitoring production processes and identifying quality deviations. This role records and analyzes quality data, assists in implementing corrective actions, provides training on in-process quality procedures, and supports continuous improvement initiatives to enhance process quality. Source: Adani Group | Job ID: 55745

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This position will be responsible for leading end-to-end plant operations with accountability for safety, production, quality, cost, statutory compliance, process efficiency, and people development. The role requires strong leadership in non-ferrous/minor metals processing, including smelting, refining, electrowinning/electrolysis, casting, material handling, utilities, and plant performance improvement. The incumbent will drive operational excellence, ensure adherence to SOPs and regulatory requirements, and deliver plant KPIs in line with business objectives. Source: Adani Group | Job ID: 55103

AG
1mo ago

This role is responsible to execute the daily operations of water systems, ensuring the achievement of production goals and maintaining quality standards. This role needs to coordinate with the Maintenance team for optimal equipment performance, managing procurement via Material Service Requests. The role also entails the preparation and submission of daily MIS reports and the maintenance of accurate inventory records. Source: Adani Group | Job ID: 39882

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AG
1mo ago

The Shift Engineer - Cluster - IPQA conducts in-process quality inspections during shifts, monitoring production processes and identifying quality deviations. This role records and analyzes quality data, assists in implementing corrective actions, provides training on in-process quality procedures, and supports continuous improvement initiatives to enhance process quality. Source: Adani Group | Job ID: 47154

aitraining
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AG
1mo ago

The Blade Process Engineer is responsible for designing and optimizing blade manufacturing processes, ensuring they meet production efficiency and quality standards. This role involves developing detailed work instructions, monitoring process parameters, and implementing corrective actions to address production deviations. The Process Engineer supports troubleshooting efforts on the shop floor, participates in root cause analysis of process-related defects, and collaborates with material engineers to validate the integration of new materials into existing processes. This position plays a key role in maintaining compliance with industry standards, documenting process changes, and contributing to continuous improvement efforts to enhance blade quality and reduce production costs. Source: Adani Group | Job ID: 56242

AG
1mo ago

The Blade Process Engineer is responsible for designing and optimizing blade manufacturing processes, ensuring they meet production efficiency and quality standards. This role involves developing detailed work instructions, monitoring process parameters, and implementing corrective actions to address production deviations. The Process Engineer supports troubleshooting efforts on the shop floor, participates in root cause analysis of process-related defects, and collaborates with material engineers to validate the integration of new materials into existing processes. This position plays a key role in maintaining compliance with industry standards, documenting process changes, and contributing to continuous improvement efforts to enhance blade quality and reduce production costs. Source: Adani Group | Job ID: 56237

AG
1mo ago

The Shift Engineer - Cluster - IPQA conducts in-process quality inspections during shifts, monitoring production processes and identifying quality deviations. This role records and analyzes quality data, assists in implementing corrective actions, provides training on in-process quality procedures, and supports continuous improvement initiatives to enhance process quality. Source: Adani Group | Job ID: 56134

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B
1mo ago

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products. THE ROLE: Voice is becoming the internet’s next interface, but a production-grade Voice AI system is "hard to build" . You’ll join a small founding team of Baseten Voice AI, focused on bringing state-of-the-art open source models into production for Voice AI customers across productivity, customer service, clinical conversation, creator tools, education, and more. You’ll make a meaningful impact on people’s daily lives and help reshape these industries. This is a high-impact, high-ownership role. You will be the primary owner of Baseten Voice AI - our in-house inference stack to power Voice AI models - from product roadmap through engineering implementation. You’ll partner closely with Forward Deployed Engineers, Model Performance Engineers, and sister engineering teams to push the boundaries of Voice AI. EXAMPLE INITIATIVES: Develop world-class model serving stack for state-of-the-art open-source voice models - reduce end-to-end and tail latency (p95/p99), increase throughput, and improve GPU efficiency via profiling, runtime tuning, and server-level optimizations. Build large-scale, real-time infrastructure for multi-model voice agents - orchestrate STT, TTS, and agent components with streaming I/O to meet customer SLOs. Design tight training and inference iteration loops for voice model customization - enable fast evaluation, safe rollout, and rapid experimentation for custom voice model development. Past projects:

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P
Pendo
📍 Herzliya• Full-time
1mo ago

About the Team This team builds an AI-native predictive analytics platform that embeds ML and AI-driven insights directly into production Go-To-Market workflows — powering real-time decisions at scale. The team owns the full stack from distributed data pipelines and backend services to ML and AI-powered capabilities that ship directly to customers. We are building toward a model where AI components are first-class runtime dependencies, not bolt-on features. Agentic AI development is a core part of how we increase engineering velocity and deliver customer value. This is a team that ships daily, iterates constantly, and treats speed as a capability to be deliberately improved. The Role This is a high-ownership, builder-first Sr. Software Engineer role. You will design, build, and ship AI-integrated data systems from concept through production — owning outcomes end-to-end, including deployment, monitoring, cost, and business impact. We are seeking a candidate who views AI tooling as a fundamental force multiplier in their daily engineering process. This position is central to our transition into an AI-native function, requiring an individual capable of making decisive, pragmatic architectural choices on reversible matters to maintain momentum. We need an experienced builder of production-grade, data-centric systems who is obsessed with delivering customer value and possesses a deep, curious enthusiasm for the transformative potential of AI. What You Will Build AI-Native Systems Development. Design, build, and own scalable data and ML pipelines, backend services, and AI-powered capabilities that are part of the platform's production decision-making layer. AI and ML components are runtime dependencies in this role — not research projects or experiments. Candidates will have strong back end and data engineering skills to thrive in this space. Daily Shipping. Decompose complex work into safely mergeable increments and ship them daily. Treat large, multi-day pull requ

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T
Twilio
📍 Spain• Full-time• Remote
1mo ago

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 Machine Learning Engineer. About the job This position is to design and engineer AI powered features that makes every customer conversation smarter. As a Machine Learning Engineer on the Conversation Intelligence team, you'll develop and deploy solutions that extract meaning from voice and messaging data at Twilio scale. You'll work alongside experienced ML practitioners to ship real features - from model pipelines to production inference - that directly shape how businesses understand their customers. Responsibilities In this role, you’ll: Design and development of machine learning solutions, ensuring accuracy, performance, security, and scalability. Implement and maintain end-to-end AI/ML pipelines - from data ingestion and feature engineering through to model development, validation, and deployment with guidance from senior engineers on complex architectural decisions Instrument AI/ML services with appropriate metrics

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T
Twilio
📍 - Ireland• Full-time• Remote
1mo ago

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 Machine Learning Engineer. About the job This position is to design and engineer AI powered features that makes every customer conversation smarter. As a Machine Learning Engineer on the Conversation Intelligence team, you'll develop and deploy solutions that extract meaning from voice and messaging data at Twilio scale. You'll work alongside experienced ML practitioners to ship real features - from model pipelines to production inference - that directly shape how businesses understand their customers. Responsibilities In this role, you’ll: Design and development of machine learning solutions, ensuring accuracy, performance, security, and scalability. Implement and maintain end-to-end AI/ML pipelines - from data ingestion and feature engineering through to model development, validation, and deployment with guidance from senior engineers on complex architectural decisions Instrument AI/ML services with appropriate metrics

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D
Datadog
📍 Massachusetts• Full-time• From $192K/yr
1mo ago

Distributed Systems engineers at Datadog design, implement and run in production the foundational platforms powering our applications. Your data pipelines will ingest, store, analyze and query in real-time billions of events per second from companies all over the globe. The platforms are optimized for durability, high availability, low latency, internet-scale footprint and operability. At Datadog, we place value in our office culture - the relationships that it builds, the creativity it brings to the table, and the collaboration of being together. We operate as a hybrid workplace to ensure our employees can create a work-life harmony that best fits them. What You’ll Do: Build fault-tolerant, horizontally scalable solutions running in multi-tenant environments Write in Go, Java Rust or C++, amongst other languages Use Kafka, Redis, Cassandra, Elasticsearch and other open-source components Own meaningful parts of our service, have an impact, grow with the company Who You Are: 6+ years of experience You have a BS/MS/PhD in a scientific field or equivalent experience You have significant backend programming experience in one or more languages (Go, Java, Rust, C++) You have been exposed to working on problems (high durability / low latency /…) You can get down to the low-level when needed You care about simple designs and performance You want to work in a fast, high-growth startup environment that respects its engineers and customers You have demonstrated ability to use AI coding tools in day-to-day workflows and validate, critique, and refine AI-generated output. Bonus: you’re motivated to push the boundaries of how AI can improve software engineering best practices and contribute to building AI-enabled products. This job is available in various departments within our company; to conform to US export control regulations, some of these roles may require candidates to be eligible for any required authorizations from the US government. Datadog values peo

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O
OpenAI
📍 San Francisco• Full-time
1mo ago

About the Team The GPT Infrastructure team builds systems that turn advances in model inference and optimization into reliable production capabilities. We enable OpenAI workloads to be qualified and optimized across new accelerator platforms without requiring a one-off port and tuning effort for every hardware target. Our work spans distributed systems, model execution, compilers and runtimes, performance engineering, secure partner integrations, evaluation systems, and developer tooling. We build the infrastructure that makes optimization workflows automated, reproducible, and trustworthy. About the Role We are seeking a software engineer to help build the platform that qualifies and optimizes inference workloads across heterogeneous compute environments. You will develop both OpenAI-hosted services and secure partner-side software for running long-lived optimization workflows. These workflows generate candidate kernels, runtime configurations, and serving-stack changes; compile and execute them on target hardware; verify their correctness; measure their performance; and use the results to guide further optimization. You will work across model architecture, distributed execution, compilers, runtimes, networking, and accelerator systems. A central part of the role is turning research prototypes and one-off hardware bring-up efforts into reliable, reusable infrastructure with clear contracts, reproducible results, strong observability, and well-defined security boundaries. Key Responsibilities Design, build, and operate APIs and control-plane services for long-running workload qualification and optimization campaigns, including scheduling, retries, checkpointing, resource budgets, and observability. Build secure partner-side execution and evaluation software that can compile, run, verify, profile, and benchmark candidate artifacts on accelerator hardware. Integrate model workloads, hardware profiles, compiler toolchains, runtimes, serving engines, and distributed-exe

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