Jobiba hiring network

Technical Writer Sr Jobs

10,000 active opportunities · Updated for October 2026

Fresh results

15 shown

Explore current technical writer sr jobs. Use filters to narrow by work mode, employment type, experience and date posted.

P
Perplexity
📍 San Francisco• Full-time• $220K – $485K/yr
6mo ago

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

pythonkubernetes
View job →

We are looking for an AI Inference Engineer to join our growing team. 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. Responsibilities: 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 kernels 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. Nice-to-have: ML compilers and framework internals: PyTorch internals, torch.compile, custom operators. Distribut

pythonkubernetesai
View job →
H
Hark
📍 San Jose• $170K – $400K/yr
7mo ago

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 You'll build the platform that powers Hark's AI agent — the runtime, the infrastructure, the primitives. Everything that makes the intelligence actually works in production. That means owning the hard systems problems, such as low-latency streaming, reliable tool execution, memory and context at scale, and orchestration logic that holds up under real usage. You will be building the foundation that everything else runs on. This is a high-ownership role on a small team. You'll work directly with the people building the models and the people shipping the product, and the systems you build will define what's possible for both. Responsibilities Build the core runtime that powers Hark's agent platform. Orchestration, tool execution, memory retrieval, streaming, and the systems that make all of it work reliably together. Own features end-to-end, from early prototyping alongside model researchers to production deployment and iteration based on real usage. Architect the platform primitives that the rest of the product team builds on. Agent runtimes, execution sandboxes, memory APIs, streaming pipelines. Instrument and evaluate the product. Write evals, track quality regressions, and feed signals back into the model and product loop. Work across th

artificial intelligenceai
View job →
PE
Private Employer
📍 Uttar Pradesh, India• Full-time
9mo ago

About Us: Paytm is India's leading mobile payments and financial services distribution company. Pioneer of the mobile QR payments revolution in India, Paytm builds technologies that help small businesses with payments and commerce. Paytm’s mission is to serve half a billion Indians and bring them to the mainstream economy with the help of technology. Job Summary: Build systems for collection & transformation of complex data sets for use in production systems Collaborate with engineers on building & maintaining back-end services Implement data schema and data management improvements for scale and performance Provide insights into key performance indicators for the product and customer usage Serve as team's authority on data infrastructure, privacy controls and data security Collaborate with appropriate stakeholders to understand user requirements Support efforts for continuous improvement, metrics and test automation Maintain operations of live service as issues arise on a rotational, on-call basis Verify whether data architecture meets security and compliance requirements and expectations .Should be able to fast learn and quickly adapt at rapid pace. java/scala, SQL, Minimum Qualifications: Bachelor's degree in computer science, computer engineering or a related field, or equivalent Experience 6+ years of progressive experience demonstrating strong architecture, programming and engineering skills. Firm grasp of data structures, algorithms with fluency in programming languages like Java, Python, Scala. Strong SQL language and should be able to write complex queries. Strong Airflow like orchestration tools. Demonstrated ability to lead, partner, and collaborate cross functionally across many engineering organizations Experience with streaming technologies such as Apache Spark, Kafka, Flink. Backend experience including Apache Cassandra, MongoDB and relational databases such as Oracle, PostgreSQL AWS/GCP Solid hands on with 4+ years of experience. St

pythonjavasql
View job →
C
Cohere
📍 Paris• Full-time• Remote• €250K – €535K/yr
14mo ago

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: The integration team is responsible for developing and scaling machine learning algorithms and infrastructure for LLM post-training, with a focus on large-scale, distributed RL methods. We strive for excellence in both engineering and science by meticulously designing experiments and design docs. While tasks are assigned according to everyone’s expertise, there is a global team effort to write production code and support the team research efforts, depending on individual interests and organizational needs. In particular, this role aims to enhance the global quality of the post-training codebase by implementing new tools to ease and support research, optimizing post-training algorithms, and scaling distributed RL to unprecedented levels. Please Note: We have offices in London, Paris, Toronto, San Francisco, New York but we are also remote-friendly! Applicants for this role may work anywhere between UTC−06:00 and UTC+01:00. Key Responsibilities: Design and write high-performing and scalable software for training models. Develop new tools to support and accelerate research and LLM training. Coordinate with other engi

REMOTEpythonkubernetesmachine learning
View job →
C
Cohere
📍 London• Full-time• Remote• £250K – £535K/yr
16mo ago

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: Advance the state of the art for model post training, ship state of the art models to production, and bridge the gap between research and production. We have one of the highest ratio of compute to engineers in the world. We do not delineate strongly between engineering and research. Everyone will contribute to writing production code and supporting our research effort depending on individual interest and organisational needs. We have all the compute, data, and talent available for you to do your best work. Please Note: We have offices in London, Paris, Toronto, San Francisco and New York but also embrace being remote-friendly! Key Responsibilities: Design and write high-performant and scalable software for training models. Consistently post-train the models to reach SOTA level performance. Coordinate with other specialist teams (Agentic, Code…) to produce models that have strong all encompassing performance. Craft and implement techniques to improve the performance and results of our training cycles both on the SFT and the RL regime. Research, implement, and experiment with ideas on our supercompute and data infra

REMOTEpythonkubernetesai
View job →
C
Cohere
📍 Paris• Full-time• Remote• €250K – €535K/yr
20mo ago

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: Contribute in and provide strong support for model training pipelines, ship state of the art models to production, and bridge the gap between research and production. We have one of the highest ratio of compute to engineers in the world. We do not delineate strongly between engineering and research. Everyone will contribute to writing production code and supporting our research effort depending on individual interest and organizational needs. We have all the compute, data, and talent available for you to do your best work. Please Note: We have offices in London, Paris, Toronto, San Francisco and New York but also embrace being remote-friendly! There are no restrictions on where you can be located for this role. Key Responsibilities: Design and write high-performant and scalable software for training. Improve our training setup from an infrastructure and codebase performance standpoint. Craft and implement tools to speed up our training cycles and improve the overall efficacy of our training infrastructure Research, implement, and experiment with ideas on our supercompute and data infrastructure. Learn from and wor

REMOTEpythonkubernetesai
View job →
C
Cohere
📍 London• Full-time• Remote• £250K – £535K/yr
20mo ago

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 Performance Engineer in the Pre-Training team you will be responsible for optimizing the performance of our advanced language models and systems. Their primary focus is on improving key model training metrics, such as training throughput, ensuring high accelerator utilization. The team combines expertise in software engineering, machine learning, and low-level kernel design and development to design robust systems and enhance model performance. You will work on identifying and removing performance bottlenecks, develop cutting-edge training and profiling tools to help Cohere's mission of providing efficient and reliable language understanding and generation capabilities and drive innovation in the field of natural language processing. Note: We have offices in London, Toronto, New York and San Francisco, but we’re also remote-friendly! This team operates primarily between ET to CET time zones, so we’re seeking candidates in locations that align with these hours for effective collaboration. Key Responsibilities: Design and write high-performant and scalable software for training. Understand architectural modific

REMOTEpythonmachine learningai
View job →
M
MongoDB
📍 Austin• $106K – $209K/yr
7mo ago

Reporting to the Director of Technical Revenue, the Senior Manager, Technical Revenue will serve as a strategic thought partner and trusted advisor to Product, GTM, Deal Strategy, Legal, and FP&A, influencing how MongoDB recognizes revenue on its newest products, pricing models, and most complex commercial deals. This is a highly visible role at the intersection of product, deal strategy, technical accounting, and requires strong business acumen and a deep understanding of MongoDB's products and deal terms. This role will help shape our revenue recognition policy under ASC 606, not just apply it, as the business scales. This role will be based out of our Austin, Palo Alto or NYC office. Position Expectations Evaluate revenue accounting implications of new products, pricing and packaging changes, partner/channel arrangements, strategic transactions, and go-to-market initiatives; prepare technical accounting memos, position papers, and related documentation as needed Act as a strategic thought partner and trusted advisor to cross-functional stakeholders (Sales, Deal Desk, Legal, FP&A, Pricing and Packaging, Product, and GTM leadership) on revenue recognition implications of commercial strategy, deal structures, and new offerings Proactively engage early in business initiatives to shape outcomes upstream, ensuring revenue accounting considerations are embedded in decision making rather than addressed reactively Serve as the company’s subject matter expert on ASC 606 for Software/SaaS arrangements, including variable consideration, contract modifications, and material right assessments Review contract write-ups to ensure that revenue is recognized in accordance with ASC606 Support accounting systems and process improvement initiatives, particularly those related to scalability and continued company growth automation, and AI-enabled workflows Candidate Profile Bachelor's degree in Accounting (CA/CPA preferred) with a Big 4 background and at least 7+ y

mongodbawsazure
View job →
A
Anthropic
📍 Ca New York City• $265K – $295K/yr
5 days ago

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic believes AI capabilities are improving rapidly, and that AI safety policy needs to keep pace. Our Policy Development team translates technical insights into workable new policy ideas for governing frontier AI. As a member of the Policy Development team, you will drive our work on technical and cross-lab safety practices, deepen our work on frontier AI legislation, and develop new technical governance ideas that you pressure-test with researchers and carry into policy proposals. You will work closely with policy colleagues and with research, alignment, safety, and legal teams, and you’ll move easily between technical detail and how policy actually gets made. Key responsibilities Help develop technical safety best practices and standards for frontier development, working closely with policy, research, and safeguards teams Support cross-lab discussions and initiatives and serve as the Anthropic representative in key standards initiatives and groups Review and give substantive input on federal, state, and global frontier AI safety bills, including on risk reporting, independent evaluation, and incident reporting, helping shape AI safety legislation development Work with our external affairs policy teams to strengthen our frontier AI legislative framework Contribute research and analysis across the policy team’s pacing workstreams, including developing novel policy proposals that address challenges related to the acceleration of AI R&D Engage with the external AI safety and governance community to track new thinking and feed it into our own Write clear memos and briefings that help leadership align on decisions

ailogistics
View job →
A
Anthropic
📍 London• £190K – £230K/yr
21 days ago

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role Anthropic is building the Forward Deployed Engineering team to help the world's most ambitious organizations adopt Claude in ways that are transformative, safe, and lasting. Our Technical Deployment Leads (TDLs) and Forward Deployed Engineers (FDEs) embed with strategic customers to ship production AI applications that solve real business problems. Our delivery model pairs two roles: FDEs own the technical artifact, and TDLs own the engagement end to end, from statement of work (SOW) through production deployment. As a Manager of Technical Deployment in EMEA, you lead a team of TDLs embedded with strategic customers. You own engagement portfolio health across your team, set the bar for delivery quality, and define where we play: which customers and which use cases are ready for production AI today. Your work will directly influence Anthropic's product direction and establish Anthropic as the trusted partner for AI transformation across the region. This role is based in London. This is a player-coach role. You need to be credible in architecture conversations with a customer's engineering leads and equally comfortable in front of executive sponsors. You will also lead the most complex engagements yourself when the stakes call for it. Most of your impact will come through the people you hire and the standard you hold them to. You won't write production code, but you will pressure-test the technical decisions your TDL team makes with FDEs. Responsibilities Hire, develop, and retain a team of TDLs embedded in engagements across EMEA. Set a high bar for delivery judgment, technical fluency, and customer presence, and run the

ailogisticsprocurement
View job →
A
1mo ago

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role Anthropic is building the Forward Deployed Engineering team to help the world's most ambitious organizations adopt Claude in ways that are transformative, safe, and lasting. Our Technical Deployment Leads (TDLs) and Forward Deployed Engineers (FDEs) embed with strategic customers to ship production AI applications that solve real business problems. Our delivery model pairs two roles: FDEs own the technical artifact, and TDLs own the engagement end-to-end — from statement of work (SOW) through production deployment. As a Manager of Technical Deployment for Financial Services, you own engagement portfolio health across your vertical. You set the bar for delivery quality and build the playbooks and evaluation frameworks that let the practice scale. Your work will directly influence Anthropic's product direction and establish Anthropic as the trusted partner for AI transformation across the Fortune 100. This is a player-coach role. You need to be credible in architecture conversations with a customer's engineering leads and equally comfortable in sales conversations in front of executive sponsors, and you will lead the most complex engagements yourself when the stakes call for it. Most of your impact will come through the people you hire and the standard you hold them to. You won't write production code, but you will pressure-test the technical decisions your TDL team makes with FDEs. Responsibilities Hire, develop, and retain a team of TDLs embedded in Financial Services engagements. Set a high bar for delivery judgment, technical fluency, and customer presence, and run the interviews that hold it. Manage each TDL directly

ailogistics
View job →

P-988 At Databricks, we are passionate about enabling data teams to solve the world's toughest problems, from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers and customer obsessed, we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started. Lakebase enables teams to deliver applications faster with an optimized database developer experience, integration with the lakehouse, and simplified operations. It provides a managed Postgres transactional layer for application state and workloads that combine operational data, analytics, and AI. You'll join as one of the key engineers building out the Lakebase product. As the Technical Lead on the Lakebase Manager (LBM) team, you will drive, build, and operate the central control plane that owns the core logic for Lakebase: database creation and deletion, wake-up and suspend, maintaining computes on hot standby, HA failover, and more. LBM interacts with every Lakebase component (storage, compute, proxy, and console) and manages the full database lifecycle at scale, with a focus on reliability. This is a hands-on individual-contributor role: you lead the team technically and partner with the team's engineering manager, who owns people management and delivery planning. The stack is Go, Rust, PostgreSQL, and Kubernetes. The impact you will have: Set the technical direction for LBM and own the quality and reliability of what the team ships, driving execution on the hardest, highest-risk parts. Drive architecture and design, and write code on the hardest parts of your team's projects. Set and uphold high technical standards through a

postgresqlkubernetesai
View job →

Integration Reliability Engineer, Technical Operations About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career. About the team APAC Payins TechOps is a newly formed team based in Singapore. Our charter is to improve the health and resilience of our payment acquiring volume, making it easier for Stripe to build and operate the integrations that support hundreds of billions of dollars in payments annually. Our team partners closely with payments and platform engineering teams to assess systems or processes that create high operational workloads, then develops durable solutions via code, tooling, data, and process improvements. We are responsible for the financial data quality of key systems at Stripe, ensuring that data is quarantined without impacting downstream systems while implementing the right changes upstream to prevent recurring issues. The team's work has a direct impact on Stripe's ability to expand into new markets and offer more sophisticated payment features to merchants. What you’ll do Responsibilities Scope and lead technical initiatives end-to-end: identify problems worth solving, propose the right solution approach, and deliver on that solution — not just execute on a pre-defined plan. Investigate problems in systems by tracing problems through Stripe’s stack. You’ll examine code, write SQL queries, read logs, and inspect data pipelines to understand system behavior, then make changes to address. Examine updates being made by Stripe’s financial partners to understand impact, and make the changes within Strip

sqlgitrest
View job →
M
MongoDB
📍 Austin• Full-time• $67K – $132K/yr
8mo ago

MongoDB is the next-generation database that helps businesses transform their industries by harnessing the power of data. The world’s most sophisticated organizations, from ground breaking startups to the largest companies use MongoDB to build applications never before possible. We're looking for a high-energy, detail-oriented and hands-on individual to join the Revenue Team as a Senior Accountant, Technical Revenue. We are looking to speak to candidates who are based in Austin, Palo Alto or NYC for our hybrid working model and will primarily be responsible for analyzing and reviewing complex revenue transactions, providing direction on technical revenue accounting issues and articulating accounting impact to our business partners during the contract negotiation process. In addition, this role will participate in month-end and quarter-end close activities and adhoc projects. This is a great opportunity to join and grow with a strong accounting team at a high growth, enterprise software company! Team Description The Revenue team is an extremely visible, high-performing team, ultimately responsible for accurate financial reporting of revenue. This will entail performing monthly close procedures, preparing detailed write-ups of revenue arrangements and providing recommendations for accounting-related terms during negotiations of revenue contracts. Additionally, this team is also responsible for designing and maintaining controls over reporting of revenue and assisting in quarterly forecasting activities for revenue and billings. Candidate Profile Bachelor’s Degree in Accounting or related discipline; CPA a plus Team player and effective communicator with all levels of management and cross functional organizations 3+ years of progressive experience in revenue accounting and operation in the technology industry Proficient knowledge of revenue and related pronouncements (ASC 606) Experience working in a SOX-controlled environment preferred Knowledge

mongodbawsazure
View job →
🔔

Get new technical writer sr jobs by email

Daily job updates · Unsubscribe anytime