Technical Solutions Specialist Jobs

About the Role The Data Platform team owns the end-to-end data lifecycle at Perplexity, from ingestion through processing, storage, and serving, powering product features, analytics, experimentation, AI workloads, and the company’s data lake. The team defines the architecture for batch and streaming systems, the orchestration and observability stack, and a self-serve data platform, while thoughtfully combining platforms such as Databricks and Snowflake with open-source technologies including Spark, Kafka, Flink, Airflow, Dagster, dbt, Iceberg, Delta Lake, and ClickHouse. In this senior/staff role, you will shape architecture, set standards, and drive the long-term technical direction of Perplexity’s data ecosystem. Key Responsibilities Design and operate large-scale batch and streaming data pipelines that directly power Perplexity product features, AI training and evaluation workflows, analytics, and experimentation. Build event-driven and streaming systems (Kafka, Kinesis, PubSub, or similar) for real-time ingestion, transformation, and delivery, alongside batch frameworks for backfills, aggregations, and offline computation. Lead the architecture of data orchestration using tools like Airflow or Dagster, owning scheduling, dependency management, retries, SLAs, and end-to-end observability for critical data flows. Set and enforce guarantees for data correctness, freshness, lineage, and recoverability, designing systems that handle rapid scale growth, partial failures, and evolving schemas without disrupting AI workloads or product experiences. Build self-serve data platforms that let engineers, data scientists, and analysts safely discover data, define contracts, and create and operate their own pipelines with minimal friction. Improve developer experience through better abstractions, opinionated paved paths, and standards for data modeling, testing, validation, and deployment, treating the data platform as a product used by many teams. Drive architectural decision

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Role Overview: As a Senior Member of Technical Staff specializing in web data for pre-training, you will play a pivotal role in developing the large scale web data pipeline that underpins Cohere’s advanced language models. In this role, you will work extensively with large-scale web corpora, transforming raw, noisy internet data into high-quality training data for pretraining. You will own key components of the data pipeline, including extraction, parsing, deduplication, and filtering. You will also analyze the composition and quality of web data, study its impact on downstream model performance, and collaborate closely with the broader data and evaluation teams to iterate on the training corpus. Your work will be essential to Cohere’s mission of delivering efficient and reliable language understanding and generation capabilities, driving innovation in natural language processing. If you are passionate about transforming data into the foundation of AI systems, this role offers a unique opportunity to make a meaningful impact. Please Note: We have offices in London, Paris, Toronto, San Francisco and New York but also embrace bein

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 Imagine team is redefining AI-driven media experiences for Grok users worldwide. As a Product Safety Engineer on the Imagine team, you will build the critical safety systems and infrastructure that ensure Grok’s multimodal generation capabilities (images, video, audio, and beyond) are powerful, delightful, and responsibly deployed. You’ll design and scale safeguards, detection systems, and evaluation frameworks that prevent harm while preserving creativity and user freedom. Your work will directly shape how millions of users experience generative media — balancing rapid innovation with rigorous safety, trustworthiness, and alignment with SpaceXSI's mission. If you’re a driven engineer passionate about AI safety, content integrity, and building robust systems that protect users without stifling innovation, this is your opportunity to make a lasting impact at the frontier of multimodal AI. RESPONSIBILITIES: Design and implement scalable safety systems for Grok’s media generation platform, including real-time content moderation, risk detection, and safeguard enforcement for images, video, and audio. Build infrastructure to measure, monitor, and mitigate safety r

Req ID: SLSQ227R500 About the Role: We are seeking a technically savvy, visionary leader that can partner with the SVP of Field Engineering (also a co-founder) and the broader leadership team of a 3,000-person global organization within Databricks. This is a rare opportunity to shape the future of a rapidly growing technology company by defining and executing strategies that drive scale, productivity, and technical excellence. This role is focused on several strategic outcomes critical for the future growth of Databricks: Shaping and driving the future of FE, Ensuring product execution at scale, Driving effective Delivery and Enablement execution, and being a company-first leader that can bridge across GTM and Product In this role, you will also help drive a high-performing, AI-driven builder culture, identifying ways to leverage AI, automation, and tooling to increase efficiency, improve decision-making, and enable teams to focus on the highest-impact work. This is a high-visibility, high-impact role for someone who thrives at the intersection of strategy, execution, and technical leadership. Successful Outcomes : Strategic Business partner to our SVP, FE to shape the future of this function OKRs/Metrics: Put in place OKRs, and metrics to measure performance Strategic Planning & Execution: Partner with the SVP and leadership team to set long-term organizational strategy, drive critical initiatives, and ensure cross-functional alignment. Future Operating Models: Define, design, and test innovative operating models for the organization, deciding where to centralize, where to push accountability to BUs, and which initiatives to pilot Ensure GTM Product Execution at scale Provide key inputs on product planning, product target setting, and product resources to the central GTM planning team Run the the inspection cadence and work across Product, Sales, Operations, FE teams to quickly resolve issues (e.g, pipeline, product gaps)&nbs

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 a Growth Engineer to own the technical foundation of Modal's marketing and developer-facing web surfaces: the marketing site, docs site, growth landing pages, high-profile microsites, forms, analytics instrumentation, and the integrations that help users discover, understand, and get started with Modal. This is a frontend-heavy role for someone with strong product taste, web engineering craft, and a business-owner mindset. You'll partner with Product Engineering, Design, Data, and Growth to ship polished, measurable web experiences from high-profile projects like the GPU Glossary and LLM Engine Advisor to internal tooling that helps teams publish content faster. When this role is going well, Modal launches new pages, docs experiences, campaigns, and experiments quickly without sacrificing performance, craft, or measurement. In this role you will: Own and evolve Modal's marketing

The Sr. Technical Program Manager for Robot Platform on PMO is a seasoned program management expert and cross-functional leader that will be responsible for strategic planning and execution of technical and integrated product milestones for our vehicle platforms on our path to launch. This person will work closely with hardware, firmware, software, safety, operations, manufacturing and systems integration teams to structure, plan, and execute milestones to achieve our company goals. The right candidate will have experience with complex HW/SW systems engineering and integration, and with leading large, cross-functional teams to deliver ambitious programs. In this role, you will: Partner with a wide range of department managers to translate the top-down corporate strategy and milestones into detailed technical roadmaps, timelines, and deliverables Influence key decisions working cross-functionally across engineering, manufacturing, product, operations, and strategy to reach the right outcomes Establish standard reports to provide concise and effective communications to key stakeholders on program status, issues/risks, and accomplishments Define and develop new KPIs and other methods to measure performance that best translate progress toward goals Ensure the program goals are aligned with business objectives; build and sustain momentum among cross-functional TPMs and workstreams towards delivering on time and on target Maintain a strong technical understanding of our vehicle platforms, software lifecycle, safety clearance process, and test operations Qualications: BS or MS degree in an engineering discipline or equivalent experience 7+ years of experience in engineering, program management, or management consulting with a focus on product launches Success in driving complex SW/HW integration processes and optimizations and leading complex cross-functional programs end to end

Who We Are Notion is the collaborative AI workspace where teams and agents think together . We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion. Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn’t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business’s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life’s work. About the Role As the Global Head of Technical Recruiting, you will play a critical role in advancing our mission by leading the growth of our Engineering, Product, and Design organizations. You will partner closely with our CTO and Co-Founder to thoughtfully build our global technical teams. You will lead a rigorous, high-performing technical recruiting organization focused on attracting talent that excels in craft and aligns with our company values. You will also collaborate with the Head of Recruiting, Head of Recruiting Operations, and our Staff team to scale our talent through rigorous, repeatable processes. You set a high bar for talent and have a strong understanding of the global technical talent market. You are “AI-first” in how you work—excited to experiment, learn quickly, and help the team adopt AI thoughtfully to improve recruiting quality, speed, and candidate experience. This role can be based in either San Francisco or New York City. We work from our offices on Mondays, Tuesdays and Thursdays (our Anchor Days) because we do our best thinking and building together in person. We’re looking for someone who’s excited to w

Everpure (NYSE: P) has evolved from storage pioneer to data platform, closing fiscal 2026 with $3.7 billion in revenue, its first billion-dollar quarter, and accelerating growth into FY27. Our strategic agenda spans the companies defining the next era of technology - hyperscalers, AI labs, the AI hardware supply chain, data platform providers, and the broader AI ecosystem. This type of work—work that changes the world—is what the tech industry was founded on. So, if you're ready to seize the endless opportunities and leave your mark, come join us. THE ROLE As the Team Lead for Initiator & Protocol Engineering, you will spearhead the critical bridge between our industry-leading FlashArray and the Linux/VMWare ecosystems. You will drive the performance and reliability of our storage protocol stacks—spanning NVMe over Fabrics and Fibre Channel—ensuring Pure Storage remains the gold standard for enterprise connectivity. Collaborating closely with cross-functional hardware and software teams, you’ll mentor a high-caliber engineering squad to solve complex kernel-level challenges and influence the global Linux upstream community. WHAT YOU'LL DO Own the Protocol Lifecycle: Lead the development, maintenance, and optimization of Linux and VMWare initiator stacks (NVMeoF, FC-SCSI, iSCSI) and target drivers to ensure seamless, high-performance integration with Pure FlashArray. Drive System Resilience: Architect enhancements for Fibre Channel and NIC driver stacks that improve RAS (Reliability, Availability, and Serviceability), specifically focusing on multipathing logic and link health monitoring. Technical Leadership & Mentorship: Guide a team of senior and junior engineers through complex project deliveries, conducting deep-dive code reviews and setting the technical bar for C/C++ and Python development within the kernel space. Solve the Impossible: Act as the final escalation point for the most challenging system-level bugs found in the field or internal testing, u

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: You will work on the most critical post-training and reinforcement learning challenges at any given time — including reward modeling, preference optimization (RLHF/DPO), and RL for improving reasoning, truthfulness, and real-world capabilities. You will get clarity on your first project before an offer. BASIC QUALIFICATIONS: You believe truth-seeking AI is the most important and challenging problem. You are obsessed about building incredibly useful models through post-training and RL techniques. You are a power user of AI models and eager to push the boundaries of what’s possible with reinforcement learning and alignment methods. If you previously worked on post-training, RLHF, or trained models used by millions of people it’s a big plus, but relevant experience is not required. You take pride in your work and thrive in meritocratic environments. COMPENSATION AND BENEFITS: $180,000 - $600,000 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 plan, short & long-term disability insurance, life insurance, and various other discou

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why this role? Are you energized by leading the design of high-performance, scalable and reliable machine learning systems? Do you want to set technical direction and help shape the next generation of AI platforms powering advanced NLP applications? We are looking for a Lead Member of Technical Staff to join the Model Serving team at Cohere. The team is responsible for developing, deploying, and operating the AI platform delivering Cohere's large language models through easy to use API endpoints. In this role, you will provide technical leadership across multiple teams, driving the architecture and strategy for deploying optimized NLP models to production in low latency, high throughput, and high availability environments. You will serve as a key point of contact for customers, leading the design of customized deployments to meet their specific needs, and mentoring engineers to raise the technical bar across the team. You may be a good fit if you have: 8+ years of engineering experience running production infrastructure at a large scale, with a track record of technical leadership Demonstrated experience leading the architecture

About the Team OpenAI’s Stargate and 3P Engineering teams are responsible for building and scaling the external infrastructure ecosystem that powers advanced AI systems. We work across hyperscalers, colocation providers, cloud partners, and strategic third-party operators to turn contracted capacity into production-ready compute. Our scope spans the full lifecycle of external deployments: commercial alignment, technical readiness, network integration, hardware enablement, operational readiness, and long-range scaling strategy. As OpenAI’s infrastructure footprint expands globally, we need leaders who can convert complex partner environments into reliable, high-velocity capacity for training and inference workloads. About the Role We are seeking a Technical Program Manager, Token-as-a-Service (TaaS) to lead delivery of external compute capacity that directly serves OpenAI model workloads. In this role, you will own complex cross-functional programs that transform third-party infrastructure into usable tokens at scale. You will partner across engineering, capacity planning, networking, hardware, finance, product, and external providers to ensure that deployed capacity translates into real production throughput. This role sits at the intersection of infrastructure execution, systems readiness, and business impact. Success requires strong technical fluency, elite program management, and the ability to drive accountability across internal teams and external partners. This is a high-visibility role with direct impact on OpenAI’s ability to scale model training and inference globally. This role is based in San Francisco, CA, with a hybrid work model of 3 days in office per week. Relocation assistance is available. Key Responsibilities Lead end-to-end delivery programs that convert external infrastructure capacity into production-ready token supply. Own readiness across compute, storage, networking, security, and operational dependencies for third-party environments. Build

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 are looking for strong engineers with experience in making ML systems performant at scale. If you are interested in contributing to open-source projects and Modal’s container runtime to push language and diffusion models towards higher throughput and lower latency, we’d love to hear from you! Requirements: 5+ years of experience writing high-quality, high-performance code. Experience working with torch, high-level ML frameworks, and inference engines (vLLM or TensorRT). Familiarity with Nvidia GPU architecture and CUDA. Experience with ML performance engineering (tell us a story about boosting GPU performance — debugging SM occupancy issues, rewriting an algorithm to be compute-bound, eliminating host overhead, etc). Nice-to-have: familiarity with low-level operating system foundations (Linux kernel, file systems, containers, etc).

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: You will join the multimodal team to push toward superhuman multimodal intelligence. Advance understanding and generation across modalities—image, video, audio, and text—spanning the full stack: data curation/acquisition, tokenizer training, large-scale pre-training, post-training/alignment, infrastructure/scaling, evaluation, tooling/demos, and end-to-end product experiences. Collaborate cross-functionally with pre-training, post-training, reasoning, data, applied, and product teams to deliver frontier capabilities in multimodal reasoning, world modeling, tool use, agentic behaviors, and interactive human-AI collaboration. Contribute to building models that can see, hear, reason about, and interact with the world in real time at unprecedented levels. RESPONSIBILITIES: Design, build, and optimize large-scale distributed systems for multimodal pre-training, post-training, inference, data processing, and tokenization at web/petabyte scale. Develop high-throughput pipelines for data acquisition, preprocessing, filtering, generation, decoding, loading, crawling, visualization, and management (images, videos, audio + text). Advance multimodal capabilities including sp

Perplexity serves tens of millions of users daily with reliable, high-quality answers grounded in an LLM-first search engine and specialized data sources. The Answer Quality team ensures that our prompts, tools, search systems, datasets, and models work together to create the best possible experience for our users. As our product and agent capabilities evolve, we need evaluation systems that are fast, reliable, production-faithful, and actionable. In this role, you will build and improve the technical foundations that support Answer Quality across Perplexity. This includes our shared evaluation infrastructure and the platform used to replay and analyze agent traces. You will work closely with data scientists, engineers, and product teams to identify quality problems, measure their impact, and turn evaluation findings into product improvements. Responsibilities Build shared evaluation infrastructure that helps teams run reliable evals, analyze results, and make product and model decisions Develop the platform for replaying and analyzing agent traces to reproduce production behavior and diagnose failures Build and operate scalable systems for processing, storing, and monitoring interaction, trace, and evaluation data Partner with data scientists, engineers, and product teams to turn answer-quality problems into evaluations, analyses, and product improvements Operate in a small, high-impact team where your work directly shapes how Perplexity measures and improves Answer Quality Qualifications 4+ years of software, data, or machine learning engineering experience shipping and operating production systems Strong proficiency in Python and SQL, with solid fundamentals in system design, data modeling, and distributed systems Experience building big-data systems, including distributed compute, large-scale storage, and high-volume pipelines Demonstrated ownership of ambiguous technical projects from initial design through production operation Ability to work effectively with

We build and run the inference engine behind every Perplexity query and deploy dozens of model architectures at scale with tight latency and cost budgets. Our stack is Rust, Python, CUDA, and CuTe DSL - and we need another engineer to join us. What you will work on Examples of real work the team does: New models support. Support transformer-based retrieval, text-generation, and multimodal models in our inference infrastructure, from weight loading, request scheduling and KV-cache management to support in API Gateway. GPU kernels migration to CuTe DSL. Port our in-house CUDA kernels to NVIDIA's CuTe DSL so they run on GB200 today and are portable to Vera Rubin racks tomorrow. Rust-native serving runtime. Develop our internal Rust-based inference server to solve all Python pains and keep up with rapidly growing traffic. Performance optimisation. Profile and fix bottlenecks from network ingress through continuous batching and GPU kernel interleaving. Reliability and observability. Build dashboards, alerts, and automated remediation so we catch regressions before users do. Respond to and learn from production incidents. Who we're looking for Deep experience with GPU programming and performance work (CUDA, Triton, CUTLASS, or similar). Any other deep systems programming experience is a plus. You understand modern LLM architectures and are able to bring them up reliably in a production environment. You've built and operated production distributed systems under real load - ideally performance-critical ones. Comfortable working across languages and layers: Rust for the serving runtime, Python for model code, CUDA/CuteDSL for kernels. You own problems end-to-end. You can read a research paper on Monday, write a kernel on Wednesday, and debug a production incident on Friday. Self-directed. You do well in fast-moving environments where the path forward isn't laid out for you. Good if you touched any of ML compilers and framework internals: PyTorch internals, torch.compile, cus