Technical Solutions Specialist Jobs

The Program Management Office (PMO) at Zoox is responsible for driving cross-functional program planning and execution at the highest level. We partner with leaders from across the company in vehicle development, system design, software engineering, manufacturing, fleet operations, and business functions to develop and deliver major corporate milestones on the path to launch, and beyond. Our program managers contribute to the end to end success of technical, integrated product milestones involving both of our vehicle platforms - the Toyota Highlander test fleet and Zoox’s purpose-built robotaxi. 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 live robotaxi service operations Build deep trust and credibility with technical department managers to steer high-stakes decisions and negotiate trade-offs across competing organizational priorities. Qualifications: 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

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 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 building a platform that covers the whole life of an LLM: training it, deploying it, and observing it in production. We already run multi-node training, elastic inference, sandboxes, and distributed volumes, and we control the infrastructure underneath. We’re looking for research depth in post-training to sit alongside our systems and product work. What You'll Do: We are looking for research scientists with a strong track record in reinforcement learning, machine learning, and foundation models, including large language and multimodal models, to join our research team. This role is well suited to candidates interested in improving existing methods and developing new techniques for large-scale model training, optimization, and inference, extending models to long-context and long-horizon tasks, and improving inference-time efficiency, reliability, and robustness in high-stakes real-world deplo

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: Most of the value of owning a model shows up at serving time. We're building a platform that covers the whole life of an LLM -- train it, deploy it, observe it -- and inference is where teams feel the difference every day. We already run elastic inference, sandboxes, distributed volumes, and multi-node training, and we control the infrastructure underneath, so the serving stack is ours to shape rather than something we resell. You will do hands-on inference research at Modal, working with the research lead to pick high-impact bets and owning them end to end. The bets that matter most are the ones that move cost per token and tail latency on the workloads our customers actually run. What You'll Do: Own end-to-end inference research bets: speculative decoding, disaggregated prefill/decode, quantization (FP8, INT4), KV-cache and memory management, autoscaling for spiky serverless traffic, and whateve

At Asana, security is foundational to our mission of helping teams work together effortlessly. Our Security organization protects Asana’s employees, users, and customers by proactively addressing threats, enabling secure product development, and embedding security into the fabric of how we operate. We partner closely with Engineering, Product, IT, Legal, and Compliance to build and maintain trust at scale. As a Security Technical Program Manager, you'll be the connective tissue across the entire Security organization, driving the strategy, programs, and operational rhythms that make the team highly effective and externally visible. This is a high-impact, high-autonomy role. You'll define how Security as a function operates: how it plans, how it measures itself, how it communicates progress, and how it executes on its biggest bets. You won't just run programs, you'll shape the operating model that makes all programs run better. This role is based in our San Francisco 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 Lead high-impact, cross-functional special projects that span organizational boundaries, from standing up new security capabilities and maturity programs to company-wide strategic initiatives Own the Security organization's annual and quarterly planning cycles, translating multi-year security strategy into a prioritized, executable roadmap Drive the prioritization and communication of security asks across stakeholders, building a unified framework that influences how partner teams plan and prioritize security work Define and own the Security team's KPI framework, covering risk posture, program health, and strategic

About the Role The Enterprise Knowledge Platform team builds the data layer that lets Perplexity's agents reach into the world's software. This team owns the systems that turn hundreds of heterogeneous integrations (native, MCP, CLI, first-party, and third-party APIs) into one unified, reliable, well-typed surface that agents can call with confidence. This platform is the core layer that forms the knowledge layer for Computer: it is how the agent discovers what tools exist, understands what each one means, decides which to call, and grounds its reasoning in real, permissioned, up-to-date enterprise data. We maintain a knowledge layer above connectors that pushes and pulls context into them, rather than letting each connector hoard org knowledge on its own, making Computer the source of truth for institutional knowledge. Models are commoditizing; grounded, actionable, permissioned access to a customer's real systems is not. When this layer is fast, accurate, and semantically rich, every agent built on top of it gets smarter; when it is weak, no amount of model quality compensates. Key Responsibilities Own the design and implementation of the connector runtime, the system that registers, hosts, and executes built-in connectors, hosted MCP servers, and CLI-backed tools behind a single agent-facing interface. Build and extend the semantic layer: tool and entity schemas, capability metadata, relationship modeling, and the mechanisms for capturing and applying organization- and account-specific corrections and knowledge. Design the tool-discovery and tool-selection surfaces that agents use to find the right connector and call it correctly, optimizing for both model accuracy and context efficiency. Make agent loops robust: structured results, partial-failure and retry semantics, idempotency, pagination, rate-limit handling, and observability into every tool call an agent makes. Define authentication, authorization, and credential-isolation patterns for connectors (OAuth fl

Director of Technical Product Marketing Job Description In this role, you will be responsible for leading, planning, developing, driving, and executing RapidFort’s global product marketing strategy. As a leader in the marketing team, you will work very closely with Sales, Product Management, Technical Marketing, Engineering, as well as global partners and customers to ensure timely planning and flawless delivery of product marketing initiatives. These initiatives will support sales enablement, campaigns, global awareness, demand generation, competitive differentiation, and partner growth objectives. If you are passionate about product marketing—and want to be part of a fast-growing, cutting-edge, high-energy team—we want to talk to you. This position reports directly to the CMO. Must have experience marketing cloud-native, Kubernetes, container security, DevSecOps, software supply chain security, or enterprise infrastructure security products. Strong understanding of Kubernetes, Docker/container ecosystems, CI/CD pipelines, software supply chain security, and modern cloud-native architectures is required. Candidates should be comfortable engaging with technical buyers including platform engineers, DevOps teams, security engineers, infrastructure architects, and developer-focused audiences. Ability to translate highly technical concepts into clear business and technical value propositions is essential. Responsibilities Define and drive global product marketing strategy, including value proposition, messaging, customer benefits, and competitive differentiation Lead global product launches, announcements, and integrated marketing campaigns Present at customer executive briefings and industry events Develop sales enablement materials, including playbooks, presentations, and tools Produce corporate press materials and analyst briefing content, including press releases and industry articles Plan, write, edit, and publish content such as eBooks, website copy, blog po

The Program Management Office (PMO) at Zoox is responsible for driving cross-functional program planning and execution at the highest level. We partner with leaders from across the company in vehicle development, system design, software engineering, manufacturing, fleet operations, and business functions to develop and deliver major corporate milestones on the path to launch, and beyond. Our program managers contribute to the end to end success of technical, integrated product milestones involving both of our vehicle platforms - the Toyota Highlander test fleet and Zoox’s purpose-built robotaxi. In this role, you will: Own the fleet validation operational strategy: Lead the end-to-end strategy and execution of mileage accumulation for both the physical test fleet and simulation assets, to enable Zoox’s geofence expansion across all cities. Partner closely with upstream teams (e.g. Autonomy, Systems Design & Mission Assurance, Places & Build) and downstream teams (e.g. Data Science, Fleet Operations) to ensure critical inputs are available, and results are delivered; you will ultimately "own the outcome" of test fleet data collection. This is a high leverage, high impact role. Usher in a simulation-first methodology : Act as the cross-functional catalyst for scaling simulated mileage accumulation. Drive alignment between Autonomy, System Design & Mission Assurance, and Simulation teams to ensure clear requirements are set, and simulation platforms are resourced to meet exponentially growing data needs. Identify and resolve critical bottlenecks : Develop rigorous tracking mechanisms that model the impact of upstream dependencies (e.g., map content deliverables and safety requirements). You’ll think critically and work cross-functionally to squash inefficiencies in upstream and downstream pipelines and systems. Partner collaboratively wi

About the Role The Backend Platform team is the backbone of Perplexity’s product reliability, scalability, and performance, enabling every product and AI team to build with confidence. This high‑impact group builds and maintains critical infrastructure, including backend systems for authentication, authorization, real-time data flows, service orchestration, and sandboxing, to ensure fast, reliable, and secure user experiences. By setting rigorous standards for code quality, uptime and performance, the Platform team ensures everyone at Perplexity can innovate at speed on top of a robust, well-architected foundation. Key Responsibilities Lead the design and implementation of our sandboxing platform to safely execute untrusted and user‑generated code while meeting strict performance and reliability requirements. Define and extend our RBAC and authorization primitives, ensuring they scale with new product capabilities and enterprise controls. Own key backend services involved in authentication and encryption flows (including BYOK‑related pieces), partnering with Security and Infra on defense‑in‑depth. Set the technical bar for backend platform design and operations, driving best practices in reliability, observability, and incident response for always‑on systems. Partner with product and AI teams to define clear platform interfaces, SLAs, and integration patterns so new features can reliably build on shared backend capabilities. Provide technical leadership across the backend platform area, mentoring other engineers and making long‑term architectural decisions that keep the foundation simple, secure, and evolvable. Qualifications Experience designing and building backend systems that run in production (typically 4+ years for mid-level, more for senior and staff). Strong system design skills, with a track record of creating efficient, reliable, and scalable architectures. Hands-on experience with modern infrastructure (for example AWS, Kubernetes, and related cloud techn

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