Technical Solutions Specialist Jobs

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title and Summary Director Product Management - Technical About Mastercard Mastercard is a global technology company in the payments industry. Our mission is to connect and power an inclusive, digital economy that benefits everyone, everywhere by making transactions safe, simple, smart, and accessible. Using secure data and networks, partnerships, and passion, our innovations help individuals, financial institutions, governments, and businesses realize their greatest potential. Role Summary We are looking for a **Principal Product Manager – Technical** to lead product strategy and execution for **global, real‑time switching and authorization platforms**.In this role, you will own the vision, roadmap, and delivery of **mission‑critical transaction processing capabilities** that operate at massive scale with strict requirements for availability, latency, resiliency, and correctness. You will work closely with engineering, architecture, operations, and business leaders to deliver platforms that support billions of transactions and enable reliable, secure payment experiences worldwide. This is a **senior individual contributor role** with broad influence across teams, regions, and portfolios. What You’ll Do Product Strategy & Vision* Define and own the long‑term product vision and strategy for switching and authori

About Hark Hark is an artificial intelligence company building advanced, personalized intelligence. One that is proactive, multimodal, and capable of interacting with the world through speech, text, vision, and persistent memory. We're pairing that intelligence with next-generation hardware to create a universal interface between humans and machines. While today's AI largely operates through chat boxes and decade-old devices, Hark is focused on what comes next: agentic systems that interact naturally with people and the real world. To get there, we're developing multimodal models and next-generation AI hardware together - designed from the ground up as a single, unified interface for a new era of intelligent systems. About the Role The Omni team at Hark is building the next generation of AI experiences beyond text, enabling models to understand and generate content across multiple modalities, including text, audio, and vision. Our goal is to create seamless, real-time multimodal intelligence that powers intuitive and immersive user experiences. We're looking for an engineer who sits at the intersection of model research and production systems. Together with our researchers, you'll decide what "better" means for a model and how to prove it — then build the infrastructure that makes those proofs reliable and repeatable: evaluation harnesses, data pipelines, and model training that hold up at scale and that the whole team can build on. This is a hands-on, individual-contributor position. The systems that judge whether a model improved, and the environments that drive that improvement, will be yours. Responsibilities Build and own end-to-end evaluation suites for LLM capabilities: task specs, grading logic, and the dashboards researchers check every day. Run the eval harness as a production service — sandboxed execution, tool calling, multi-turn and agentic tasks, deterministic replay, and caching — so a full evaluation pass is cheap and gives the same answer twic

Senior AI Technical Product Manager — 6 Locations. Apply via Workday.

Lead AI Technical Product Manager — 6 Locations. Apply via Workday.

Senior Datacenter Technical Program Manager, At-Scale AI Clusters — 3 Locations. Apply via Workday.

The internet is vast, containing trillions of URLs. Perplexity’s crawling and storage system is complex and has multiple stages (URL discovery, crawling, parsing, indexing). Each stage offers many opportunities for improvement and room for intricate bugs. You’ll work at the intersection of data analysis and engineering — designing metrics, building data pipelines, and improving the quality of our search and answer systems. Responsibilities Find and diagnose quality issues in our crawling pipeline Train small models that optimize particular aspects of the pipeline (e.g. parsing quality) Build datasets for model training, including LLM-as-a-judge labeling pipelines Improve page selection algorithms for indexing Design and analyze experiments to validate improvements Qualifications 4+ years of experience as a data analyst, ML engineer, or in a related role Strong coding skills: you should be able to write production-grade code at the level of a mid-level backend engineer Experience designing metrics from scratch Experience training ML models that shipped to production with measurable metric improvements Nice to have Direct experience working on web crawling or indexing pipelines

Lead Director - Retail Analytics Technical Product — NY - New York. Apply via Workday.

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. Our team includes creators of popular open-source projects (e.g., Seaborn , Luigi ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We’re looking for strong engineers with experience building software that developers love to work with. Our ideal candidate is someone with a demonstrated drive to build beautiful abstractions that enhance developer productivity. Requirements: 5+ years of experience developing high-quality Python, JS or Go applications or libraries where the code is used or interacted with by other developers A strong code-as-product sense that manifests as a focus on developer ergonomics and productivity. Knowledge of async programming and concurrency management/pitfalls A high level of customer empathy, good communication skills, and an openness to working directly with our users to help solve their problems. Ability to participate in on-call rotation and respond to production incidents. Ability to work in-person in our New York or Stockholm office. Any of the following would be a plus: Having built developer to

Perplexity is seeking an experienced Machine Learning Engineer to advance how AI systems search, reason, and work together to solve complex problems. Our work spans search and retrieval, LLM post-training, multi-agent training, and the harnesses that make these systems effective. We control the full stack: the models, the agent harnesses, and the search infrastructure underneath. That gives us the freedom to develop new approaches across all three training models to use search more effectively, designing tools and execution environments around learned behavior, and improving retrieval to support how agents actually work. Responsibilities Push search and agent quality forward through improvements to models, training data, tools, and system design. Develop LLM post-training methods, including reinforcement learning, to improve reasoning, search, tool use, and task completion. Train and evaluate multi-agent systems, exploring how agents divide work, share information, and coordinate effectively. Design and build agent harnesses around the tools, context management, execution environments, and orchestration that support reliable work over many steps. Improve retrieval and ranking models and the search interfaces agents use to find and assess information. Build datasets, reward signals, and evaluations that expose meaningful failures and guide improvements. Own experiments end to end, from a clear hypothesis to scalable training, deployment, and measurable gains in quality, latency, and cost. Collaborate with AI, Search, Infrastructure, Data, and Product teams to bring new capabilities into production. Qualifications A strong track record of building and shipping ML systems, with deep experience in one or more of LLM post-training, reinforcement learning, search and retrieval, or agent systems. Strong software engineering skills and the ability to work across model training, experimentation infrastructure, and production systems. Experience designing rigorous evaluations

Perplexity is seeking an experienced Machine Learning Engineer to advance how AI systems search, reason, and work together to solve complex problems. Our work spans search and retrieval, LLM post-training, multi-agent training, and the harnesses that make these systems effective. We control the full stack: the models, the agent harnesses, and the search infrastructure underneath. That gives us the freedom to develop new approaches across all three training models to use search more effectively, designing tools and execution environments around learned behavior, and improving retrieval to support how agents actually work. Responsibilities Push search and agent quality forward through improvements to models, training data, tools, and system design. Develop LLM post-training methods, including reinforcement learning, to improve reasoning, search, tool use, and task completion. Train and evaluate multi-agent systems, exploring how agents divide work, share information, and coordinate effectively. Design and build agent harnesses around the tools, context management, execution environments, and orchestration that support reliable work over many steps. Improve retrieval and ranking models and the search interfaces agents use to find and assess information. Build datasets, reward signals, and evaluations that expose meaningful failures and guide improvements. Own experiments end to end, from a clear hypothesis to scalable training, deployment, and measurable gains in quality, latency, and cost. Collaborate with AI, Search, Infrastructure, Data, and Product teams to bring new capabilities into production. Qualifications A strong track record of building and shipping ML systems, with deep experience in one or more of LLM post-training, reinforcement learning, search and retrieval, or agent systems. Strong software engineering skills and the ability to work across model training, experimentation infrastructure, and production systems. Experience designing rigorous evaluations

The Opportunity As a Technical Account Manager, you will serve as the primary technical advisor for a portfolio of strategic enterprise customers in Mexico. You will build trusted relationships, help customers improve how they gain value from their Adobe investments, and maintain an outstanding customer experience throughout the engagement. This role offers the opportunity to collaborate with world-class technical teams and senior leaders. It involves translating customers’ business priorities into clear technical strategies, operational plans, and measurable outcomes. You will proactively identify risks, uncover optimization opportunities, and orchestrate the appropriate Adobe resources to help customers achieve their long-term goals. Responsibilities Serve as the primary technical advisor and point of coordination for a portfolio of strategic enterprise customers Build and maintain trusted relationships with practitioners, technical leaders, managers, directors, and C-level executives Translate complex business objectives into actionable technical strategies, success plans, and operational priorities Proactively identify customer needs, technical risks, and opportunities for optimization, adoption, and long-term improvement Orchestrate the resolution of complex technical issues by coordinating across Adobe Engineering, TechOps, Managed Services, Support, Product, and other internal teams Establish clear expectations and maintain consistent communication through regular checkpoints, status reviews, governance meetings, and planning sessions. Conduct in-depth assessments of customers’ technical environments to identify architectural risks, performance concerns, integration challenges, and opportunities for improvement Provide strategic advice on implementation approaches, technical guidelines, scalability, performan

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. Our team includes creators of popular open-source projects (e.g., Seaborn , Luigi ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: Modal’s Inference Runtime team owns the container runtime stack used to run inference and training workloads across our fleet. We work at the boundary of Linux, containers, filesystems, storage, GPU drivers, and distributed systems.Our goal is to make demanding ML workloads start quickly, run efficiently, and remain securely isolated — whether they use a single GPU, hundreds of gigabytes of memory, or multiple GPUs connected with RDMA.We’re looking for a systems engineer who enjoys working deep in the stack. You’ll build production runtime infrastructure in Rust and Go, diagnose difficult Linux and performance problems, and help determine the architecture of Modal’s container platform. You’ll also work closely with maintainers of gVisor and contribute to the runtime itself when the right fix belongs upstream. The Work: Make container startup, checkpoint, and restore dramatically faster for large i

About the Team OpenAI's Vendor Security team helps internal teams work securely with external products, services, and partners. Our work spans software, infrastructure, hardware, professional and managed services, vendor-provided workforces, data, and research. We build the programs and products that help teams understand vendor risk and put effective safeguards in place, protecting our customers, employees, and the company. About the Role We are looking for a Vendor Security Technical Program Manager who can make sound security decisions and turn recurring vendor-security problems into tools and practices that work. You will independently lead vendor-security engagements: understand the business need, investigate the actual data and access, recommend a practical path, and work with the responsible owners until the safeguards are verified. You will also use what you learn to build and improve bounded tools and workflows, with priorities agreed with the Vendor Security lead. This is an individual-contributor role for someone who combines technical judgment with useful delivery. You should be comfortable taking a position, explaining the tradeoff, and changing your mind when the evidence changes. Success means internal teams can use vendors securely, reuse work that still applies, and understand what needs to happen next. In this role, you will: Own vendor security engagements from understanding the business need through scoping, assessment, decision, treatment, and reassessment when material facts change. Make assessment decisions independently and use judgment about when to involve peers, specialists, or leadership. Route formal exceptions and risk acceptance to the appropriate decision owners. Understand vendor use cases, workflows, user journeys, data flows, identities, access, integrations, and supply-chain dependencies. Identify plausible attack paths and their consequences for OpenAI. Assess relevant architectures, configurations, controls, logs, and operationa

We take play seriously. We’re looking for curious adventurers ready to find their party, fueled by imagination and drive to build what’s never been built before. At Hasbro and Wizards of the Coast, you’ll collaborate with passionate teams to reimagine our iconic brands and create experiences that spark joy, connection, and community through the magic of play. This is your chance to shape legendary play that lasts a lifetime. Step Into the Multiverse: Your Next Adventure Starts Here At Wizards of the Coast , we harness the power of imagination and connection to create unforgettable experiences. We create entertainment that inspires creativity, sparks passion, forges friendships, and fosters communities around the globe. In every pursuit our mission is to inspire a lifetime love of games. Whether it's through the strategic depth of Magic: The Gathering® , the rich storytelling of Dungeons & Dragons® , or our AAA digital game studios, we build worlds that bring people together, spark creativity, and fuel adventure. As we continue to grow and explore new realms, we're seeking passionate, curious, and innovative minds to join the adventure. We are looking for a Senior Technical Sound Designer to join our digital game team at Wizards of the Coast. This role is anticipated to be a hybrid work position, with some work on-site and some work from home. What You’ll Do Design and develop features, tools, and workflows that align with the game’s creative vision and enhance production efficiency, in collaboration with the Audio Director and key stakeholders. Partner with cross-discipline technical experts to streamline processes, improve integration, and elevate overall product quality. Collaborate with game engineers to implement scalable and reliable audio pipelines that support production at all stages. Optimize audio assets and development workflows to meet the evolving technical and creative needs of the project.

About Hark Hark is an artificial intelligence company building advanced, personalized intelligence. One that is proactive, multimodal, and capable of interacting with the world through speech, text, vision, and persistent memory. We're pairing that intelligence with next-generation hardware to create a universal interface between humans and machines. While today's AI largely operates through chat boxes and decade-old devices, Hark is focused on what comes next: agentic systems that interact naturally with people and the real world. To get there, we're developing multimodal models and next-generation AI hardware together - designed from the ground up as a single, unified interface for a new era of intelligent systems. About the Role At Hark, you'll build the desktop experience that brings our intelligence to where people do their work every day. We're looking for exceptional engineers with deep C++ experience and a background in Chromium or Electron-like application frameworks, who want to shape how a proactive AI lives on the computer. You'll architect and build the native foundations of Hark's desktop app on macOS and Windows, from OS-level integration and system APIs to the features that let Hark see, listen, remember, and act alongside users across their apps and the web. You'll own features end-to-end, work closely with researchers, model engineers, design, and hardware teams, and help define what it feels like to have an intelligent agent built into your desktop. This role is a fit for engineers who thrive in fast-paced environments, take initiative on high-impact problems, and care deeply about building software that is fast, stable, and feels native on every platform. Responsibilities Own features from concept and design through implementation and launch, serving as a desktop and native platform expert on the team. Build the core of Hark's desktop app, while contributing to features across the full stack. Build the native capabilities that make Hark mu