Production Supervisor Jobs

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 . The Enterprise Applications & Architecture (EAA) Business Unit Delivery team builds and operates the internal platforms that help Coinbase scale. Within EAA, the Compliance CX Agent Experience team owns Agent Cockpit, the primary internal platform used by Coinbase's compliance agents and investigators to review cases, communicate with customers, access account and transaction data, and resolve compliance-related support queries. As a Staff Technical Program Manager, you'll own program delivery for this complex, high-impact platform, driving cross-functional execution to ensure agents and investigators have reliable, performant tools every day. What you'll do: Own the program management framework for Agent Cockpit, including roadmap tracking, intake and prioritization, sprint planning, dependency management, and cross-team delivery execution. Drive technical dependency coordination and platform migrations, translating upstream system changes (API deprecations, service integrations, data model changes) into internal delivery plans and engineering asks. Lead launch readiness and operational risk management, owning security review coordination, production approvals, testing governance, and escalation when critical-path items stall. Partner with Engineering on reliability, observability, and performance programs, including system health metrics, load testing, capacity

About Sayari: Sayari is the judgment infrastructure for trustworthy AI in economic security and commercial risk. The Sayari Commercial World Model resolves 11.7B+ primary-source records from 250+ jurisdictions forming the ground truth of global commerce. A Judgment Ontology, encoding over a decade of investigative tradecraft, and Superconductor, an agentic orchestration platform, deliver AI that reasons like an expert analyst, shows its work, and traces every finding to its source. Trusted by U.S. Customs and Border Protection, HM Revenue & Customs, and Fortune 500 enterprises, Sayari is used by thousands of professionals across 35+ countries to secure supply chains and dismantle illicit networks. Headquartered in Washington, D.C., with offices in London, Singapore, Tokyo, and Tel Aviv. POSITION DESCRIPTION This is not a traditional engineering role. As a Forward Deployed Engineer (FDE), you are at the critical intersection of our code, our clients, and their most critical missions. You will be deployed to our most strategic partners, embedding within their environments to solve high-stakes problems that have no textbook answers. You own the "last mile" of our product's impact , ensuring our technology fundamentally transforms how our users confront challenges such as financial crime, supply chain disruption, and threats to national security. You are equal parts engineer, strategist, and operator. One day you might be architecting a data pipeline within a client's cloud environment ; the next, you'll be writing production Python to integrate our API into a proprietary analytics platform; and by the end of the week, you could be briefing a C-level executive, intelligence analyst, or mission director on the outcomes your work has enabled. You thrive on ambiguity, operate with extreme ownership, and are relentless in your pursuit of delivering real-world value. You will act as a vital conduit between the front lines and our core engineering teams, turning you

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. ML Platform @ Roblox today supports hundreds of ML use cases and billions of inferences per day across Discovery, Safety, Engine, and much more. As an Infrastructure Engineer on the ML Platform team, you will design, scale, and maintain the foundational infrastructure powering our entire machine learning ecosystem. We are looking for accomplished engineers to spearhead the development of our next-generation ML tooling and platform capabilities. You will: Bootstrap and maintain Kubernetes and Cloud infrastructure for ML Platform components--Serving Layer, Metadata Store, Model Registry, and Pipeline Orchestrator. Set technical strategy and oversee development of high scale and reliable infrastructure systems. Propose and implement new platform tooling to improve time to production for MLEs and Data Scientists across the full ML lifecycle. Work on infrastructure projects such as GPU fleet management, hybrid-cloud orchestration, and writing custom Kubernetes controllers and resources. Stay abreast of industry trends in machine learning and infrastructure to ensure the adoption of leading-edge technologies and practices. Partner across organizations to build tooling, interfaces, and visualizati

About Us SharkNinja is a global product design and technology company, with a diversified portfolio of 5-star rated lifestyle solutions that positively impact people’s lives in homes around the world. Powered by two trusted, global brands, Shark and Ninja , the company has a proven track record of bringing disruptive innovation to market and developing one consumer product after another has allowed SharkNinja to enter multiple product categories, driving significant growth and market share gains. Headquartered in Needham, Massachusetts with more than 4,100 associates, the company’s products are sold at key retailers, online and offline, and through distributors around the world. AI at SharkNinja At SharkNinja, we’re building an AI-native culture. We’re not waiting for the future; we’re creating it. Our people are expected to experiment boldly, adopt new tools, and continuously raise what’s possible to create meaningful impact for our consumers. If you believe the best way to do your job hasn’t been invented yet, you’ll fit right in. Sr. Director, AI Engineering Transformation Location: Boston, MA preferred; New York, NY acceptable (On-site) Reports to: VP, Chief of Staff to the CEO Dotted Line: Chief Technology Officer / Chief Engineering Officer Direct Reports: AI Transformation Team (AI Fellows) The Role This is a high-impact leadership role at the intersection of AI, engineering, product quality, and organizational transformation. You will own the strategy and execution of AI integration across SharkNinja's Engineering organization, spanning the full development lifecycle from concept and architecture through design, validation, and production, and extending into reliability engineering, DFM/DFT, test data, and manufacturing engineering. Today, much of this work relies on PowerPoint-based program management, fragmented data, manual analysis, a

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. Machine Learning is at the heart of Lyft’s products and decision-making. Machine Learning Engineers at Lyft operate in dynamic environments, moving quickly to build the world’s best transportation solutions. We tackle a wide range of challenges, from pricing and marketplace frameworks that ensure reliability and competitiveness, to agentic AI platforms that automate analytical workflows, to behavioral detection systems that protect the integrity of our network. We operate at the intersection of applied ML and real business impact, shipping models that directly influence revenue, rider experience, and partner trust. Lyft Business builds products that help organizations move the people who matter most—employees, customers, patients, and guests—easily and efficiently. Our offerings include Business Travel, Lyft Pass, and Concierge (for healthcare and non-healthcare rides), enabling companies to manage transportation at scale through APIs, integrations (e.g., Concur, Expensify), and dedicated tools. These platforms power high-impact B2B use cases across corporate travel, healthcare access, customer experience, and community programs. We're looking for a Machine Learning Engineer to design, build, and deploy ML systems across Lyft Business. This is a high-scope role: you won't be siloed into one problem area. Instead, you'll move across pricing algorithms, fraud and behavior detection, agentic AI systems, and emerging ML applications as the business evolves. You'll write production-quality code, own models end-to-end from prototyping through deployment, and collaborate closely with Data Scientists, Product Managers, and Software Engineers to translate complex business problems into scalable ML solutions. This role is ideal for someone who is technically versatile, energized by variety, and wants to see th

We are looking for a deeply technical, customer-facing Forward Deployed Engineer to help product development organizations deploy Command - a new offering from Asana. As we incubate new motions and capabilities on Command, we need engineers who can work directly with customers, move quickly from insight to implementation, and bring real-world learning back into the product. This role is based in our San Francisco or New York City office with an office-centric hybrid schedule. The standard in-office days are Monday, Tuesday, and Thursday. Most Asanas have the option to work from home on Wednesdays. Working from home on Fridays depends on the type of work you do and the teams with which you partner. If you're interviewing for this role, your recruiter will share more about the in-office requirements. What you’ll achieve Collaborate with Engineering leaders, platform teams, administrators, and hands-on builders to connect Command to the systems where work already happens Establish the technical and operational foundations for adoption and help teams develop more effective ways of planning, building, shipping, and learning Move between cloud infrastructure, integrations, workflow design, automation, product enablement, and engineering coaching Work directly in customer environments — configuring secure access to source-control, CI/CD, ticketing, and identity systems, or pairing with engineering teams to design release workflows and help leaders clarify the context their agents and teams need to make good decisions Write production-quality code when needed and turn customer-specific solutions into reusable product capabilities Leave customers with more than a working deployment — leave them with a stronger system for building software About you 6+ years of experience in software engineering, forward deployed engineering, customer engineering, solutions engineering, implementation engineering, or a similar technical customer-facing role Strong coding and systems-thi

We are looking for a deeply technical, customer-facing Forward Deployed Engineer to help product development organizations deploy Command - a new offering from Asana. As we incubate new motions and capabilities on Command, we need engineers who can work directly with customers, move quickly from insight to implementation, and bring real-world learning back into the product. This role is based in our San Francisco or New York City office with an office-centric hybrid schedule. The standard in-office days are Monday, Tuesday, and Thursday. Most Asanas have the option to work from home on Wednesdays. Working from home on Fridays depends on the type of work you do and the teams with which you partner. If you're interviewing for this role, your recruiter will share more about the in-office requirements. What you’ll achieve Collaborate with Engineering leaders, platform teams, administrators, and hands-on builders to connect Command to the systems where work already happens Establish the technical and operational foundations for adoption and help teams develop more effective ways of planning, building, shipping, and learning Move between cloud infrastructure, integrations, workflow design, automation, product enablement, and engineering coaching Work directly in customer environments — configuring secure access to source-control, CI/CD, ticketing, and identity systems, or pairing with engineering teams to design release workflows and help leaders clarify the context their agents and teams need to make good decisions Write production-quality code when needed and turn customer-specific solutions into reusable product capabilities Leave customers with more than a working deployment — leave them with a stronger system for building software About you 6+ years of experience in software engineering, forward deployed engineering, customer engineering, solutions engineering, implementation engineering, or a similar technical customer-facing role Strong coding and systems-thi

SpaceX was founded under the belief that a future where humanity is out exploring the stars is fundamentally more exciting than one where we are not. Today, SpaceX is actively developing the technologies to make this possible, with the ultimate goal of making life multiplanetary and expanding consciousness to the stars. SpaceXSI is building Super Intelligence to help humanity understand the universe. Our teams are building the full Super Intelligence stack: from our Colossus supercomputers, to Grok models, to our suite of applications, including Grok Bot, Grok Build, Grok Imagine, Grok Voice, and X. We're creating a powerful flywheel where more compute trains better models, better models power more useful products, and what we learn from people using those products shapes what we build next. ABOUT THE ROLE: The RL infrastructure team is looking for an engineer to help with low precision RL training and inference. RESPONSIBILITIES: Design and optimize our inference stack for all shapes of RL workloads at SpaceXSI, from small scale ablations to production training runs. Analyze, profile and address performance bottlenecks in large scale RL systems Work closely with the modelling team to efficiently implement novel RL techniques and algorithms BASIC QUALIFICATIONS: Experience in building, debugging, and optimizing efficiency of large-scale distributed systems Experience in LLM inference Proficiency in programming languages such as Python, C++ and/or Rust; frameworks such as PyTorch, Jax, CUDA Willingness to dive deep and solve hardcore problems at all levels of the stack PREFERRED SKILLS AND EXPERIENCE: Strong knowledge in quantization and numerics in LLM inference and training Experience in developing inference engines, e.g. SGLang, vLLM COMPENSATION AND BENEFITS: $180,000 - $440,000 USD Base salary is just one part of our total rewards package at SpaceXSI, which also includes equity, comprehensive medical, vision, and dental coverage, access to a 401(k) retirement pl

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic's Research Productivity organization builds the infrastructure and systems that accelerate research across Anthropic, including the tools that help our research process get faster and more effective over time. We're looking for an experienced software engineer to join us as we scale this infrastructure at a moment when both demand and scope are growing extremely quickly. This team operates like a startup within a startup. You'll be a strong fit if you like thinking from first principles, iterating fast on infrastructure, and tackling reliability and scalability challenges head-on as the products built on top of your systems evolve underneath you. You'll independently scope complex, multi-month projects, drive cross-org alignment through ambiguous problem spaces, and make the architectural decisions that shape how the infrastructure behind our research tooling gets built. You'll partner directly with research teams to understand their workflows, anticipate how their requirements will change, and design and scale infrastructure that can keep pace. Responsibilities Design, build, and scale infrastructure and systems that support rapidly increasing usage, where requirements and workload continue to evolve as the products built on top of them evolve Independently scope and lead complex, multi-month engineering projects, from an ambiguous starting point through to a production system Drive cross-organizational alignment on technical direction, working through ambiguous problem spaces with multiple stakeholders and teams Make architectural decisions that shape the foundation of research infrastructure and tooling acr

The Behavior AI team builds the AI-based anomaly detection behind Datadog's security products. Our models learn what normal looks like across the billions of logs, events, and telemetry records flowing through the platform every second, and they flag the behavior that does not fit, on every record, in real time, at a cost that makes sense at our scale. What we build does not ship to a single feature. The same models power detection across many of Datadog's security products at once, so the work has impact well beyond any one team. Large general-purpose models are too slow and too expensive to run in that path, so we take the opposite approach: small, custom models, designed for high-throughput stream processing and optimized to run cheaply on every record. We are hiring a Senior Applied Scientist to build these models from start to finish. You will contribute to designing the architecture, training at scale, and the optimization work that takes a model from training to running efficiently on production traffic. This optimization requires a deep understanding of the constraints imposed by both the software and the hardware, together with the applied mathematics to work within them: often it comes down to finding a mathematical reformulation that fits those constraints better, and that judgment can decide whether a model reaches production at all. The work involves a number of open questions. How do you obtain most of the quality of a large model from one that is far smaller and cheap enough to run on the full stream? Where is it worth trading exactness for speed, and how do you reason about the error you accept? How do you make a small model's outputs clear enough that the detection engineers and analysts who rely on it can trust what it reports? If these are the problems you want to work on, we would like to hear from you. At Datadog, we place value in our office culture: the relationships and collaboration it builds, and the creativity it bring

About Appier Appier (TSE: 4180) is an AI-native Agentic AI as a Service (AaaS) company that empowers businesses to create value through cutting-edge AdTech and MarTech solutions. Founded in 2012 with the vision of "Making AI Easy by Making Software Intelligent," Appier helps businesses turn AI into ROI through its Ad Cloud, Personalization Cloud, and Data Cloud—each powered by Agentic AI that enables autonomous, adaptive, and real-time decision-making. Today, Appier operates 17 offices across APAC, the US, and EMEA, and is listed on the Tokyo Stock Exchange. Learn more at www.appier.com . About the role Engineers at Appier build a wide range of platforms and services that interconnect data and AI with our customers and users—operating at scale where every millisecond and every nine of availability matters. As a Senior Backend Engineer (SRE / Reliability & Performance) , you will sit at the intersection of backend development and site reliability engineering: designing and building scalable, performant backend services while owning the reliability, observability, and performance characteristics of large-scale, high-traffic systems (QPS > 10k). You will profile and tune systems end to end, lead the response to production incidents, and drive the engineering practices that keep our services fast and resilient as traffic grows. Seniority and title are determined by job-related skills, experience, and evaluation following the interview. We welcome international candidates to our teams. This position is ideally to be based in Taiwan. Responsibilities Design and build scalable, reliable, and maintainable backend services and the components that support them Own system reliability and performance for high-traffic services, including SLO/SLA definition, error budgets, and capacity planning Profile, benchmark, and tune critical components to resolve latency, throughput, and scalability bottlenecks in medium-to-large systems (QPS > 10k) Diagnose and sol

At FourKites we have the opportunity to tackle complex challenges with real-world impacts. Whether it's medical supplies from Cardinal Health or groceries for Walmart, the FourKites platform helps customers operate global supply chains that are efficient, agile and sustainable. Join a team of curious problem solvers that celebrates differences, leads with empathy and values inclusivity. As a Senior AI Engineer, you'll join a 10-person team focused on data integrations (shippers and carriers moving in and out of the FourKites ecosystem) and our active AI agent workstreams — including a support automation agent handling 60-70% of customer tickets, a voice agent that calls carriers to gather and update information, and an end-to-end carrier onboarding agent (email + voice). You'll work on features end to end (~75-80% backend, ~20-25% frontend) using Python, Java/GoLang, agentic frameworks like LangGraph, React, Redis and PostgreSQL. You'll develop products that change the logistics landscape for some of the biggest corporations in the world, and work closely with our US team and customers to shape the future of the industry. What you’ll be doing: Design, build, and productionize AI agents/workflows (e.g., support automation, voice, and onboarding agents) using agentic frameworks such as LangGraph Develop, test, and maintain backend applications in Python and Java or GoLang Write clean, efficient, and well-documented code across the full SDLC — development, QA, and release Design and implement data models and database schemas Collaborate with the frontend team to integrate the backend with the user interface Perform code reviews and ensure code quality standards are met Troubleshoot and debug applications, including AI agent workflows in production Work with the DevOps team to deploy and manage applications in production (Kubernetes) Continuously learn and stay up to date with new technologies and industry trends, particularly in the AI/agentic space About the team: Our

Platform administration isn't the part of the product anyone screenshots for a demo. Nobody's writing a blog post about your identity provisioning flow. But it's the thing every other team at Diligent quietly depends on more than any other dev team in the company and when it breaks, everyone notices immediately. If that kind of quiet, high-stakes ownership sounds appealing rather than thankless, keep reading. This role is for someone who wants real skin in the game: you build it, you ship it, you support it. We're a high-initiative team that improves things we see first and asks permission later, building secure, event-driven microservices in TypeScript on AWS, and treating infrastructure as code the same way we treat application code: with rigor, not as an afterthought. Here's a breakdown of what you'll do (not all of it, just the important stuff) Design and build secure, scalable full-stack services using AWS serverless tech (Lambda, SQS, API Gateway) — with real attention to event-driven patterns and observability, not just "does it work on my machine." Own your services in production. That means building good observability, keeping an eye on alerts, and responding to them before they become bigger problems. Build infrastructure as code with AWS CDK and push for CI/CD that ships safely and often — not "big bang" releases you have to pray over. Design RESTful APIs other teams will actually want to consume: clear contracts, sane versioning, no surprises. Write tests — unit, integration, end-to-end — as part of how you build, not a chore you do after. Show up to architecture discussions with opinions and documentation, not just vibes. Use AI tools to move faster on coding, debugging, testing, and research — but you're still the one who validates the output. These are the essentials you'll need to get an interview 2-3 years of professional software engineering experience in an agile, full-stack-focused environment. Solid full-stack fundamentals: request lifecycles, d

Binance is a leading global blockchain ecosystem behind the world’s largest cryptocurrency exchange by trading volume and registered users. We are trusted by 300+ million people in 100+ countries for our industry-leading security, user fund transparency, trading engine speed, deep liquidity, and an unmatched portfolio of digital-asset products. Binance offerings range from trading and finance to education, research, payments, institutional services, Web3 features, and more. We leverage the power of digital assets and blockchain to build an inclusive financial ecosystem to advance the freedom of money and improve financial access for people around the world. Role Overview Responsible for end-to-end quality assurance across Web and App (mobile) surfaces — combining automated and exploratory testing to ensure product stability, compatibility, and interaction experience from the user's perspective. The core requirement is cross-platform testing capability (Web + App), with the ability to design and maintain an automated testing system and to think deeply about troubleshooting and user-experience-oriented quality. In one sentence: This role is the quality gatekeeper for Web/App products — someone who can write automation scripts, test interaction experiences, investigate data issues, and use engineering methods to replace manual testing with systematic automated quality coverage. Not a manual tester — a QA engineer with real coding ability. Key Responsibilities Design and maintain comprehensive Web/App test cases and test plans covering functionality, compatibility, and interaction Develop and maintain UI/API automated tests using Java, Python, or JavaScript to ensure high coverage and reliability Combine automation and manual exploratory testing to validate user scenarios and discover potential experience issues Perform root cause analysis on test failures and production issues, and drive fixes to closure Identify blind spots i

Zscaler (NASDAQ: ZS) accelerates digital transformation so customers can be more agile, efficient, resilient, and secure. The Zscaler Zero Trust Exchange platform protects thousands of customers from cyberattacks and data loss by securely connecting users, devices, and applications in any location. Distributed across 200+ public data centers globally and thousands of private sites at the edge, the SASE-based Zero Trust Exchange is the world’s largest in-line cloud security platform. We believe the future of work is Human + AI and are building an AI-native enterprise where human potential is amplified by machine intelligence to solve the world’s hardest security challenges. Driven by deep customer obsession, we are committed to the mission, outcome, and to each other. We bring these commitments to life through three core behaviors: ownership and collaboration, trust through outcomes and impact, and a challenge culture with ongoing feedback. Ready to make an impact at the company pioneering security transformation in the AI era? Join us at Zscaler. Role We are looking for an AI Engineer to join our team. This is a Hybrid role, reporting to the Engineering Manager in the Product Operations department. We are seeking a hands-on AI Engineer to help scale the agentic layer of our AI Native - Product Operations Platform. In this role, you will design and build production-grade AI systems, reusable platform capabilities, and the engineering harnesses required to safely develop, evaluate, debug, and operate AI workflows at scale. As a pragmatic builder who understands modern AI systems in practice, you will translate ambiguous business needs into scalable technical solutions in a high-velocity environment. What you’ll do (Role Expectations) Build and scale the agentic layer of the AI Native - Product Operations Platform by designing production-grade AI systems, reusable platform capabilities, and reliable execution patterns Develop Agentic AI capabilities by applying p