Test Production Shift Supervisor Jobs

About the Role: Tubi is seeking a highly skilled and experienced QA Automation Engineer to lead quality assurance initiatives for our cutting-edge streaming and AI-driven product features. This pivotal role involves ensuring exceptional end-to-end user experiences, robust streaming playback, and the accuracy and integrity of our AI/ML features across web, mobile, and OTT platforms. We're looking for a candidate with a strong background in streaming QA and deep technical knowledge of media workflows. You'll be instrumental in collaborating with engineering, product, and data science teams to define comprehensive QA strategies that guarantee both functional excellence and data-level quality This is a hybrid role based out of our Toronto office. You must be willing to travel to our Toronto office two days/week. What You'll Do: Design and lead test strategies for streaming workflows, playback systems, and AI-powered features. Test across platforms (web, mobile, and connected TV) to ensure functional parity and playback stability. Validate streaming performance—including ABR logic, encoding pipelines, and DRM integrations—under diverse real-world conditions. Debug with precision using tools like Charles Proxy, Chrome DevTools, ADB, and Xcode. Collaborate with data and ML teams to validate AI model updates, recommendations, and personalization accuracy. Leverage AI-assisted QA tools to enhance regression coverage, UI validation, and anomaly detection. Contribute to automation and CI/CD frameworks, driving faster, more reliable releases. Oversee QA deliverables for multiple concurrent releases and ensure seamless sign-off for production launches. Monitor live environments for playback or recommendation anomalies post-release and escalate issues promptly. Continuously improve QA processes, metrics, and reporting for streaming and AI validation. Your Background: Bachelor’s degree in Computer Science, Software Engineering, or related field, or equivalent hands-on experi

About the Role: Tubi is one of the largest free streaming platforms in the US, serving a large-scale streaming audience across Web, iOS, Android, Roku, Fire TV, Apple TV, and game consoles. Quality at this scale isn't a checkbox — it's a competitive advantage. We're looking for an Automation Engineering Manager to lead the team responsible for building and operating Tubi's multi-platform test automation infrastructure. You will own the strategy, tooling, and execution quality across our client surfaces — from video playback and ad delivery to content discovery and onboarding. This role is for a hands-on technical leader who can set direction, influence cross-functional roadmaps, and stay close enough to the code to guide architecture, review critical implementation decisions, and unblock complex technical issues. You will build a team that ships reliable automation at speed — and you will help the team move toward AI-native automation practices: fluent in AI tooling, proactive about applying it, and disciplined about using it responsibly. This is a hybrid role based out of either our San Francisco or Toronto office. You must be willing to travel to either location at least 2 days a week. What You'll Do: Test Strategy & Quality Planning Define and own Tubi's multi-platform automation strategy — covering Web, iOS, Android, CTV (Roku, Fire TV, Apple TV, Smart TVs, game consoles), and API layers. Establish testing standards, coverage targets, and quality gate policies across the CI/CD pipeline to protect release confidence and production reliability. Design specialized test strategies for business-critical scenarios: video playback (HLS/DASH), ad insertion, content recommendation surfaces, and user authentication flows. Use AI-assisted analysis (e.g., failure pattern clustering, test gap detection) to continuously improve test strategy based on real production signal and defect trends — not gut instinct. Automation Framework & Infrastructure Lead the

About the Role We are seeking an experienced Azure DevOps Engineer to design, implement, and maintain CI/CD pipelines, cloud infrastructure, and automation solutions on Microsoft Azure. This role bridges development and operations, ensuring reliable, secure, and scalable delivery of applications and infrastructure. Location: Hyderabad-India-Onsite Duration: Fulltime Responsibilities Design, build, and maintain CI/CD pipelines using Azure DevOps (Pipelines, Repos, Artifacts, Boards) Architect and manage Azure cloud infrastructure using Infrastructure as Code (ARM templates, Bicep, or Terraform) Automate build, test, and deployment processes across multiple environments Implement and manage containerization and orchestration (Docker, Azure Kubernetes Service) Monitor system performance, availability, and security using Azure Monitor, Log Analytics, and Application Insights Collaborate with development, QA, and security teams to streamline release management Implement Azure security best practices, identity management (Azure AD/Entra ID), and network architecture Manage cost optimization and governance across Azure subscriptions Troubleshoot production issues and support incident response Document infrastructure, pipelines, and operational procedures Required Qualifications Microsoft Certified: Azure Solutions Architect Expert, Azure Administrator Associate (required) 3+ years of hands-on experience with Azure DevOps and Azure cloud services Strong experience with Infrastructure as Code (Bicep, ARM templates, or Terraform) Proficiency scripting in PowerShell, Bash, or Python Experience with Git version control and branching strategies Solid understanding of networking, security, and identity concepts in Azure Experience with containerization (Docker) and orchestration (Kubernetes/AKS) Familiarity with monitoring and logging tools (Azure Monitor, Application Insights) Preferred Qualifications Additional certifications: Azure DevOps Engineer Expert Experience with multi-

Amplitude is the leading AI analytics platform, helping over 4,700 customers—including Atlassian, Burger King, NBCUniversal, and Square—build better products and digital experiences. With powerful AI Agents embedded across our platform, teams can analyze, test, and optimize user experiences faster than ever. Ranked #1 across multiple categories in G2’s Winter 2026 Report, Amplitude is the best-in-class solution for product, data, and marketing teams. Learn more at amplitude.com . As an organization, we deliver for our customers by living our values. We operate from a place of humility, take ownership of problems and successes, approach challenges with a growth mindset, and put our customers at the center of everything we do. Amplitude’s Commitment to Diversity Equity & Inclusion (DEI): Amplitude believes that diversity enables the creation of better products, improves the ability to solve complex problems, and drives more powerful solutions. We strive to create an environment of inclusion—one focused on psychological safety, empathy, and human connection—that will allow employees of all backgrounds to thrive. About the Team DevX owns engineering velocity at Amplitude: build systems, CI/CD, developer environments, and internal tooling. We're building a software factory: automated workflows that remove manual bottlenecks from how engineers ship code. The Role We're looking for a Staff Software Engineer – DevX (Hybrid – San Francisco) who bridges infrastructure and application thinking and can accelerate how the whole team develops, tests, and ships in the cloud. You'll set architecture for our developer platform, lead our software factory work, and push our development model toward cloud-first workflows. This is a high-leverage, low-oversight role. You'll own initiatives end to end, from an ambiguous problem to production, and set technical direction for a foundational team. What You'll Do Cloud development platform: Unify and scale our existing loca

Quantitative Researcher Every trading strategy begins with a question worth answering. At Graviton, we believe the best trading strategies don't come from following established playbooks. They come from asking better questions. Why does a pattern exist? What is driving it? Is it real or just noise? Can it be explained, modelled and turned into an edge? As a Quantitative Researcher , you'll work on these questions every day. You'll investigate market behaviour, develop quantitative models, build and test hypotheses and turn insights into trading strategies. You'll work alongside quantitative researchers and technologists in an environment where research moves quickly from an idea on a whiteboard to something that can influence live trading. The problems are open-ended. The data is enormous. The answers aren't in a textbook. You'll be expected to find them. What You'll Work On You'll work across different areas of quantitative research and systematic trading. Depending on your team and research interests, your work may include: Discovering predictive patterns and sources of alpha from billions of market events . Formulating hypotheses about market behaviour and designing experiments to test them. Applying probability, statistics, optimization and machine learning to complex research problems. Building predictive models and quantitative signals for systematic trading. Developing and improving research infrastructure that enables faster experimentation and deeper analysis. Working with large and complex datasets to uncover patterns that aren't immediately visible. Designing robust backtests and statistical tests to distinguish genuine signals from noise. Investigating market microstructure and understanding how markets behave at different timescales. Evaluating strategy performance, identifying weaknesses and continuously refining models. Working closely with technologists to translate research ideas into efficient, production-ready systems. Building AI-powered r

ROLE We are passionate about data. We collaborate to build elegant, effective, scalable and highly reliable solutions to empower predictive modelling in finance. Cubist’s Data Services (CDS) group is looking for a Data Scientist to join our dedicated data team. Our group is responsible for the timely delivery of comprehensive and error-free data to some of the most demanding and successful systematic Portfolio Managers in the world. As a Data Scientist in the team, this individual will play a vital role in ensuring the smooth day-to-day implementation of a large research infrastructure, and the live production trading of billions of dollars of capital across global capital markets, including equities, futures, options and other financial instruments. RESPONSIBILITIES Onboarding novel datasets from a huge variety of sources into our platform Develop, test and deploy data pipelines, applications and services Re-shaping, aggregating, enhancing and creating features from datasets Engaging with vendors and internal stakeholders to understand characteristics of datasets Defining and automating qualitative data alerts and reports Partnering closely with investment teams to ensure their data requirements are met Perform preliminary analysis and research to be shared with investment teams REQUIREMENTS Masters in Financial Engineering, Statistics, Computer Science or other disciplines involving rigorous quantitative analysis Strong programming skills in Python and SQL Experience working with AWS, Linux and Airflow preferred but not required Financial industry experience preferred but not required Strong organization, communication and interpersonal skills Attention to detail and a love of processes Strong oral and written communication skills Ability to exercise sound judgment in assessing and determining how to handle queries, calls and issues Ability to multitask and prioritize assignments Commitment to the highest ethica

Agents have changed the game for software delivery and efficacy. Diligent is the leading GRC platform in the world, and we are racing ahead to take the agents show on the road and work with the customers where they work . The FDE function will lead the change on how we embed AI agents into some of the world’s most complex governance, risk and compliance environments. This is not a support or consultancy role. It is a builder role, for someone who is equally comfortable reading a failing agent trace, running a discovery workshop with a bank’s internal audit team, and translating what they find into a production-grade agentic solution. You will be building AI agents for GRC professionals , not assistants that surface suggestions, but agents that own complex, multi-step workflows end to end . Agents that customers can hand a task to and trust it will come back done. Closing the gap between a promising prototype and something a company Board and ELT depends on is a completely . Here’s a breakdown of what you’ll do Embed directly with major enterprise customers (global banks, regulated corporates) across EU and US ; sitting wi th internal audit teams, risk functions, compliance and governance professionals to understand their real workflows and devise agentic solutions to intelligently automate them creating tremendous efficacy and efficiencies for our customers. Run agent-focused discovery workshops, rapidly prototype agentic solutions, and test them with practitioners; distinguishing between workflows that need an agent and those that need a button. Source, integrate, and move data between enterprise systems as part of live customer implementations — understanding the real data landscape customers operate in and building reliable pipelines to support it . Take agents from prototype t

Here’s a summary of the role: Build cloud software that matters, grow your technical depth, and use modern AI tooling to do your best work. This is a hands-on engineering role for someone who enjoys solving product problems, writing clean code, and helping services run reliably at scale. You’ll work on secure, scalable microservices and APIs using TypeScript, AWS , and modern engineering practices. You’ll be part of a collaborative product engineering team where you can own features, contribute to design discussions, support production systems, and keep growing across backend, cloud, and AI-assisted development workflows. Here’s a breakdown of what you’ll do, not all of it, just the important stuff: Design, build, test, and improve backend services and APIs using Node.js, TypeScript, and AWS . Take ownership of well-defined features from planning through release, including code quality, deployment, and production support . Work closely with product managers, designers, and other engineers to turn requirements into practical, reliable solutions. Contribute to technical design conversations, code reviews, and engineering standards that keep the team moving well. Use AI tools to speed up research, coding, debugging, testing, and documentation, while checking outputs carefully and applying sound judgment. Help keep systems secure, observable, and maintainable by improving monitoring, reliability, and day-to-day development practices. These are the essentials you’ll need to get an interview: 3 to 5 years of professional software engineering experience building production applications in an agile environment. Strong backend development skills with Node.js and TypeScript, including experience building APIs or microservices. Experience with React or Angular in a product engineering environment. Hands-on experience with

Software is eating the world, but AI is eating software. We live in unprecedented times – AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products. To make them safe, aligned and actually useful, these models need human eval and reinforcement learning through human feedback (RLHF) during pre-training, fine-tuning, and production evaluations. This is the main innovation that’s enabled ChatGPT to get such a large headstart among competition. At Scale, our products include the Generative AI Data Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI. At the foundation of these products is the Platform Engineering team. In this role, you will support the design and development of shared platforms used across Scale. This includes designing our foundational data platforms and lifecycle, architecting Scale’s core cloud infrastructure and orchestration stack, and redefining how engineers develop, build, test, and deploy software at Scale. You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies. You will: Drive the design, and implementation of our foundational platforms and systems, working closely with stakeholders and internal customers to understand and refine requirements. Collaborating with cross-functional teams to define, design, and deliver new features. Proactively identifying opportunities for, and driving improvements to, current p

Software is eating the world, but AI is eating software. We live in unprecedented times – AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products. To make them safe, aligned and actually useful, these models need human eval and reinforcement learning through human feedback (RLHF) during pre-training, fine-tuning, and production evaluations. This is the main innovation that’s enabled ChatGPT to get such a large headstart among competition. At Scale, our products include the Generative AI Data Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI. At the foundation of these products is the Platform Engineering team. In this role, you will support the design and development of shared platforms used across Scale. This includes designing our foundational data platforms and lifecycle, architecting Scale’s core cloud infrastructure and orchestration stack, and redefining how engineers develop, build, test, and deploy software at Scale. You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies. You will: Drive the design, and implementation of our foundational platforms and systems, working closely with stakeholders and internal customers to understand and refine requirements. Collaborating with cross-functional teams to define, design, and deliver new features. Proactively identifying opportunities for, and driving improvements to, current p

Opportunity Overview: We are seeking a Senior Data Engineer to contribute to the design and delivery of our cloud-native healthcare data platform. You will implement scalable data solutions built on AWS, Apache Iceberg, Lake Formation, Glue Catalog, Athena, dbt, and modern orchestration frameworks. This role combines strong hands-on engineering with collaboration across platform, analytics, and business teams. What You'll Do Data Engineering Delivery Deliver complex data engineering projects in collaboration with cross-functional teams Drive technical execution from design through production deployment Implement scalable data patterns and reusable frameworks Design and implement batch and near-real-time pipelines Build reusable ingestion, transformation, validation, and publishing frameworks Support modernization of legacy workloads Contribute to Apache Iceberg implementation and optimization Apply standards for schema evolution, partitioning, compaction, and metadata management Ensure efficient storage and query performance Implement data quality frameworks and validation layers Support observability and monitoring practices Contribute to operational excellence and reliability improvements Participate in architecture and design discussions Conduct and participate in code reviews Mentor junior engineers and share best practices ISMS roles and responsibilities Good knowledge of Information security Oversee specific business processes within the ISMS. Responsible to manage the ISMS documentation, conduct risk assessments, and implement risk treatment plans. Risk Owners are responsible for identifying, assessing, and managing risks within their areas of responsibility. They are also responsible for implementing risk treatment plans. Conduct the BCP and other test related to information security continuity along with CISO Responsible for monitoring and reporting on the performance of the ISMS. Responsible for implementation of security policies and procedures and report

Opportunity Overview: We’re looking for a Manager, Platform Engineering that can lead and grow a high-performing engineering team focused on Developer Experience, DevOps, SRE, and Quality. You will own the systems and processes that enable teams to build, test, release, and operate software with high velocity and reliability, driving engineering efficiency and operational excellence across the organization. What you’ll do: Lead a fast-paced, autonomous team of engineers focused on platform engineering, developer experience, DevOps, SRE, and quality engineering Own and drive the internal developer platform strategy and roadmap, improving how engineering teams build, test, deploy, and operate services Create transparency into engineering efficiency and system health through meaningful metrics across delivery, reliability, and quality Enable teams to move faster by improving CI CD pipelines, environments, tooling, and overall developer workflows Provide technical leadership across platform, infrastructure, and reliability, helping teams build scalable and resilient systems Ensure strong engineering practices across release processes, testing, quality, reliability, and security Define and enforce release guardrails, validation standards, and rollback mechanisms to improve production safety Improve environment stability and consistency across development, QA, and pre production environments Drive test strategy and automation maturity to improve overall product quality and confidence in releases Define and implement observability, monitoring, and alerting standards across systems Improve incident detection, response, and RCA practices, ensuring learnings translate into platform and system improvements Drive cloud infrastructure best practices across AWS, containers, and infrastructure as code Foster a culture of ownership, reliability, and continuous improvement within the team Provide innovative solutions for attracting, developing, and retaining top engineering talent I

Job title: Data Validation Role Purpose (overall high level summary of the role) Finance has mobilised the first phase of a five year programme to transform the Finance operating model by leveraging cloud technology. Finance Cloud Transformation will rationalise operational processes, automate data and report production, to deliver comprehensive data to our internal and external stakeholders for analysis and reporting. The programme will entail migration of core Finance data and processes to the cloud, with an initial phase to implement a standard global operating process for Finance actuals report production, followed closely by forecast data and report production. The vision for the Finance on the Cloud Programme is “to deliver standardised global processes that leverage a single dataset for reporting, analysis and forecasting.” Key programme outcomes are to deliver a singular automated data production processing capability for actuals and forecasting, correction of data once for all downstream calculations, reports and outputs, introducing automated preventative and detective controls, significantly reduce manual activity in the run-time actuals process to allow the production of all actuals outputs by working day 5 for a monthly process The Data Analyst will be expected to support the delivery of data related activities within the FotC programme. Various aspects may include data validation, solution functionality validation, data gap analysis, reconciliation, user tooling or automation testing activities. • The role holder will be responsible to functionally understand and test our liquidity core release requirements • He/ She is required to perform a detailed data validation to ensure the data reflects accurately across all liquidity returns for all applicable regulations - PRA/EBA/HKMA/US FED etc. • He/She needs to furnish UAT dashboards and walkthrough the Reporting Ops of the changes introduced by liquidity core release requirements • He/She is

Job title: Liquidity reporting Compliance Finance has mobilised a multi-year Integrity of Regulatory Reporting (IRR) programme to ensure that Regulatory Reporting across the Group is fit for purpose; accurate, timely and complete. The IRR programme is responsible for overseeing the design and implementation of a set of standards and control outcomes that will be consistently applied across the end-to-end Regulatory Reporting Process. IRR will drive the interconnectivity across various strategic transformation programs to ensure linkages and dependencies are well understood and aligned to the IRR standards and control outcomes. The Liquidity Product Based Review (LIQ_PBR) workstream is part of the overall data controls framework for Liquidity Regulatory Reporting. Product Based Reviews enable Finance to develop key assurance that the end to end data flow for Business Data Elements (“BDE’s”), from upstream Primary Booking Systems to downstream Reporting data warehouses (including the Liquidity Reporting Finance Data Application / Platform) complies with the applicable group data standards and controls (‘DMOV’ and ‘DUSE’), is complete and valid for the production of key Liquidity reports and metrics and that data quality or completeness issues discovered through the PBR process are appropriately logged, reported, escalated and managed to resolution. The LIQ_PBR Data Analyst contributes to Global Finance, supporting data flow discovery and documentation, from upstream primary trading and booking systems (PTS) to downstream Liquidity reporting platforms. The role holder will support the Liquidity PBR workstream to undertake quantitative and qualitative data documentation, test case formulation, data test execution and results tabulation, in order to provide the necessary assurance for management with regards to the traceability, lineage, transformation and controls on Liquidity business data elements from source systems to reporting. In this regards, the LIQ PBR d

About the Team Our Robotics team is focused on unlocking general-purpose robotics and pushing towards AGI-level intelligence in dynamic, real-world settings. Working across the entire model stack, we integrate cutting-edge hardware and software to explore a broad range of robotic form factors. We strive to seamlessly blend high-level AI capabilities with the constraints of physical systems to improve peoples’ lives. About the Role We are seeking a Mechanical Design Engineer to lead the development of motor mechanical designs and prototype hardware for advanced robotic systems. You will own stator and rotor mechanical development from early concepts and detailed design through hands-on builds and prototype validation, partnering closely with electromagnetic, electrical, test, and manufacturing teams. This role focuses on the design, integration, and validation of motor components and prototype processes, including laminations, stack assemblies, bobbins, winding interfaces, and fixtures. You will help drive motor development from initial design through repeatable low-volume builds while establishing the tooling, work instructions, and validation practices needed for future robotic platforms. This role is based in San Francisco, CA, and requires in-person presence 4 days a week. In this role, you will Own stator and rotor mechanical designs and released CAD and drawings, including geometry, interfaces, fits, tolerances, retention, assembly access, and mechanical validation. Develop laminations, stack assembly methods, bobbins, and winding interfaces that control alignment, insulation, conductor placement, and end-turn packaging. Design, fabricate, and debug fixtures for winding, stacking, assembly, alignment, and inspection. Build and troubleshoot prototypes. Use measurements, defects, rework, and assembly effort to improve designs and processes. Establish low-volume prototype production with equipment, build sequences, work instructions, revision control, traceability