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Machine Learning Research Scientist in San Francisco

238 active opportunities · Updated October 2026

Explore current machine learning research scientist jobs in San Francisco. Filter by work mode, employment type, experience, department, date posted and distance.

O
📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -80.2%

About the Team The Monetization team is a new cross-functional group working across engineering, product, research, and design to build the foundational systems that will help OpenAI scale access to intelligence responsibly. Our mission is to develop user-first, privacy-preserving monetization products—including next-generation ads experiences—that strengthen user trust, unlock economic opportunity, and support OpenAI’s long-term innovation. Monetization plays a critical role in enabling OpenAI to continue pushing the boundaries of AI capabilities while ensuring the benefits of AGI are broadly shared. We believe monetization must be aligned with user value, uphold rigorous privacy and safety standards, and sustain a healthy ecosystem of developers and businesses. This team operates in a greenfield environment and moves quickly through prototyping, experimentation, and iterative deployment. We partner closely with Product, Design, and Research to bring research breakthroughs into real-world systems at global scale. About the Role We’re looking for an experienced Software Engineer to help build the machine learning infrastructure that powers OpenAI’s monetization and ads systems. In this foundational role, you’ll design and develop the platform layer that enables teams to build, train, deploy, serve, monitor, and continuously improve machine learning models used across advertising and monetization products. You’ll work across the full ML lifecycle, from large-scale data pipelines and feature infrastructure to training systems, model serving, experimentation platforms, and monitoring frameworks. The systems you build will support high-throughput, low-latency advertising workloads while maintaining strict standards for reliability, privacy, security, and performance. This role sits at the intersection of machine learning systems, distributed infrastructure, and monetization, offering the opportunity to shape the core platforms that help translate model innovation into m

AWSRestMachine LearningAI
O
📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -80.2%

About the Team The Interpretability team studies internal representations of deep learning models. We are interested in using representations to understand model behavior, and in engineering models to have more understandable representations. We are particularly interested in applying our understanding to ensure the safety of powerful AI systems. Our working style is collaborative and curiosity-driven. About the Role OpenAI is seeking a researcher passionate about understanding deep networks, with a strong background in engineering, quantitative reasoning, and the research process. You will develop and carry out a research plan in mechanistic interpretability, in close collaboration with a highly motivated team. You will play a critical role in helping OpenAI ensure future models remain safe even as they grow in capability. This will make a significant impact on our goal of building and deploying safe AGI. In this role, you will: Develop and publish research on techniques for understanding representations of deep networks. Engineer infrastructure for studying model internals at scale. Collaborate across teams to work on projects that OpenAI is uniquely suited to pursue. Guide research directions toward demonstrable usefulness and/or long-term scalability. You might thrive in this role if you: Are excited about OpenAI’s mission of ensuring AGI benefits all of humanity, and are aligned with OpenAI’s charter . Show enthusiasm for long-term AI safety, and have thought deeply about technical paths to safe AGI. Bring experience in the field of AI safety, mechanistic interpretability, or spiritually related disciplines. Hold a Ph.D. or have research experience in computer science, machine learning, or a related field. Thrive in environments involving large-scale AI systems, and are excited to make use of OpenAI’s unique resources in this area. Possess 2+ years of research engineering experience and proficiency in Python or similar languages. Are deeply curious. About OpenA

PythonAWSRestMachine Learning
O
📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -80.2%

About the Team OpenAI’s Hardware organization develops system and infrastructure solutions designed for the unique demands of advanced AI workloads. We work closely with research, software, and external hardware partners to shape the next generation of AI systems, from silicon through full-scale deployments. Our team focuses on understanding and optimizing performance across the full system stack—ensuring that architectural decisions are grounded in rigorous, quantitative analysis of real-world workloads. About the Role We are seeking a Performance Modeling Lead to build and lead a small, high-impact team responsible for answering forward-looking architectural questions across AI infrastructure systems. You will develop modeling frameworks and methodologies to evaluate system-level tradeoffs and guide key design decisions. Your work will directly influence reference architectures, vendor designs, and long-term infrastructure strategy. This role sits at the intersection of AI workloads, system architecture, and quantitative modeling, and requires strong technical judgment, ownership, and the ability to translate complex analysis into clear, actionable guidance. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance. Key Responsibilities Build and own a performance modeling framework/toolchain to evaluate AI systems across multiple levels of abstraction. Analyze and quantify architectural tradeoffs across compute, memory, networking, storage, and system topology. Develop performance models to guide decisions on: scale-up vs. scale-out architectures interconnect and network design memory hierarchy and system balance. Translate modeling outputs into clear recommendations for internal teams and external hardware vendors. Influence reference designs and vendor roadmaps through data-driven insights. Partner closely with machine learning, systems, and hardware teams to understand workload characte

AWSRestMachine LearningAI
O
📍 San Francisco, California, United States· Full-time
✓ High-confidence listingCompany trend -80.2%
Quick readStrong listing-quality and freshness signals

About the Team The Product & Platform teams at OpenAI are responsible for delivering the company’s most impactful offerings—such as ChatGPT, our API platform, and new enterprise capabilities—to a global and diverse customer base. These systems must perform at scale and deliver exceptional experiences to developers, consumers, and businesses alike. The ChatGPT Multimodal team works across voice, image generation, and other multimodal experiences to turn frontier research capabilities into reliable products. The team connects product usage and failure patterns with research, evaluation, data, inference, capacity, and external partnerships so that model and product improvements translate into better experiences for users. About the Role We are seeking a Technical Program Manager to build the flywheel that helps ChatGPT multimodal products learn from real-world usage and improve quickly. You will lead programs spanning production-signal mining, evaluation and data pipelines, research-to-production parity, multimodal capacity planning, and complex cross-functional dependencies for voice and image-generation launches. You will work closely with product engineering, research, Human Data, inference and capacity teams, safety partners, and external vendors or product partners. Success requires technical depth, strong systems thinking, comfort with ambiguity, and the ability to turn fragmented or manual work into durable mechanisms that teams adopt. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Build a system for mining production conversations and product signals to identify representative multimodal workflows, user needs, and failure modes. Establish and maintain evaluations for the highest-priority multimodal behaviors and use cases, with clear coverage, quality standards, and ownership. Package production signals into decision-ready data and

AWSRestMachine LearningAI
B
📍 San Francisco, California, United States· Full-time· Remote
✓ High-confidence listingCompany trend -79.1%
Quick readStrong listing-quality and freshness signals

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE We’re looking for a high-performing strategic finance professional to join our growing GTM Finance team. Our business grows with our customers' usage, which makes the finance function highly strategic at Baseten: growth, pricing, margin, and capacity decisions are business model decisions. You'll sit at the center of them, partnering directly with GTM leadership and reporting into a finance team with a seat at the table for the calls that shape the company's trajectory. This role is ideal for someone with 3 to 7 years of experience across strategic finance, investing, and/or investment banking who wants broad exposure to company-building inside a fast-scaling AI infrastructure company. Experience at a usage-based software company is a plus. RESPONSIBILITIES Own financial planning, forecasting, and budgeting processes for the GTM org Build and maintain financial models across revenue, S&M spend, headcount, and strategic bets Analyze the metrics that define a usage-based business – ARR, gross margin, consumption trends, retention, and GTM efficiency Partner with GTM leaders to set targets, evaluate growth initiatives, shape pricing, and design sales compensation Help prepare board materials, investor updates, and fundraising analyses Improve financial reporting, dashboards, and operational rigor so our infrastructure scales as fast as our revenue Work cross-functionally to turn ambiguous business questions int

SQLRestMachine LearningAI
B
📍 San Francisco, California, United States· Full-time· Remote
✓ High-confidence listingCompany trend -79.1%
Quick readStrong listing-quality and freshness signals

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE The largest, most demanding enterprises run on Baseten, and they bring exacting requirements for how people, services, and agents access the platform. This is the founding role for our identity and authorization team within enterprise engineering. You'll own the identity and access layer of the Baseten platform: the authorization model, credential systems, and admin experiences that enterprise IT teams use to govern access for organizations like Harvey, HubSpot, and Notion. You'll design and build Baseten's fine-grained authorization system from the ground up to support the workflows customers depend on today while giving them cleaner, more precise ways to manage access as the platform grows. Authorization at Baseten requires low-latency permission checks at high request volume, consistent contracts and behaviors across the product suite, and strong security guarantees for mission-critical, highly regulated workloads. EXAMPLE INITIATIVES Recent and upcoming work in this area: Fine-grained authorization for users, service accounts, and agentic workloads: per-resource permissions at the organization, team, and workload scope to support both common workflows and complex enterprise access policies Programmatic authentication allowing high-compliance customers to connect service principles securely via short-lived, workload-based credentials Agent credentials that grant an agent exactly the access it needs for the gi

PythonKubernetesMachine LearningAI
B
📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -79.1%

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products. THE ROLE Forward Deployed Engineers work directly with the largest and fastest-growing AI companies in the world, owning their technical outcomes on Baseten and taking on the hardest problems in serving and improving models at scale. The work spans the model lifecycle: inference, post-training, and the systems that tighten the loop between them. Act as each account's de facto CTO on Baseten, with final accountability for how their workloads are designed, run, and scaled. Take customer objectives from vague to shipped: frame the problem, define the spec and success criteria, build the PoC, and carry it through to production quickly, using the right tools for the problem. Design the evals and benchmarks that isolate where quality or performance falls short, then close the gap yourself, whether that means optimizing inference, improving the model through post-training, or reworking the eval itself. Be the first responder to mission-critical failures including triage, owning the fix directly or route to the owning team and stay accountable until it ships. Build internal systems so that each engagement is faster than the last. This includes tooling and automation for eval and deployment infrastructure, and the recipes and reference implementations that make the product more self-serve. Shape the product itself, channeling what your accounts need into the roadmap and shipping fixes and features into Baseten's codebase yourse

KubernetesRestMachine LearningAI
O
📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -80.2%

About the Team OpenAI’s mission is to ensure that artificial general intelligence benefits all of humanity. Safely delivering increasingly capable AI systems requires scalable technical safeguards, clear ownership of emerging risks, rigorous deployment readiness, and close coordination across research, engineering, product, operations, legal, policy, and external partners. Our Technical Program Managers lead complex, high-stakes initiatives that turn safety commitments into deployed systems and measurable outcomes. We work across model development, infrastructure, product, and operational response to help ensure our technology is deployed responsibly and cannot be used to cause serious real-world harm. About the Role We’re seeking Technical Program Managers to drive complex product, platform, and safety initiatives across ChatGPT, API, enterprise, and related deployment environments. These roles operate at the intersection of technical strategy and execution: you will turn safety and product priorities into actionable plans, influence architectural and operational decisions, and deliver durable capabilities across model, infrastructure, application, and platform layers. Depending on the role, you may enable sensitive or high-impact model deployments, integrate safeguards into cloud and API platforms, prevent violent misuse and other serious harms, improve detection and enforcement systems, create platform solutions for safety or establish new programs as risks evolve. You will partner deeply with engineers, researchers, product managers, and operational teams while communicating technical tradeoffs and program decisions to senior leadership. You bring technical fluency, product judgment, and a strong execution record. You’re comfortable navigating ambiguity, advocating for users and developers, balancing safety with model usefulness, and leading cross-functional work with urgency, rigor, and empathy. Specific focus areas and scope will vary by opening and level. Thi

AWSRestMachine LearningAI
B
📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -79.1%

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products. THE ROLE As a Forward Deployed Engineer at Baseten, you will partner directly with customers to architect, build, and deploy high-scale production AI applications on Baseten’s platform. You’ll own the journey with customers from initial exploration to production deployment, translating ambiguous business goals into reliable, observable services with clear quality, latency, and cost outcomes. This role is a great fit for entrepreneurial engineers who want a front-row view into how modern companies adopt AI at scale and who enjoy working across product, software development, performance engineering, and customer-facing implementations. To be clear, this is an engineering role with hands-on coding and software development that also includes aspects of product management, technical customer success, and pre-sales solution engineering mixed in. EXAMPLE INITIATIVES Take a look at these blog posts written by members of our Forward Deployed Engineering team: Forward Deployed Engineering on the frontier of AI The fastest, most accurate Whisper transcription Deploy production-ready model servers from Docker images Deploy custom ComfyUI workflows as APIs RESPONSIBILITIES Develop and maintain software systems and product features using one or more general-purpose programming languages in a production-level environment, with a preference for Python due to its relevance in ML projects. Drive customer impact by designing, implementin

PythonDockerMachine LearningAI
B
📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -79.1%

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products. THE ROLE As a Site Reliability Engineer at Baseten, you'll define and codify the gold standards of day 2 operations for our ML infrastructure platform. You'll envision and build robust systems, processes, automations, and observability tooling that keep our platform reliable at scale — and that empower the broader organization to operate confidently. You'll work closely with engineering, forward-deployed and product teams: learning from recurring failure patterns, turning tribal knowledge into automated mitigations, and raising the operational floor for the entire company. EXAMPLE INITIATIVES You'll work on projects like these as part of the SRE team: Improve Baseten SRE Practices, by instrumenting SLOs and SLIs, improving alerting and observability for all services. Building AI-assisted tooling for incident triage and response. RESPONSIBILITIES Own the reliability of Baseten's multi-cloud Kubernetes infrastructure, including incident response, post-mortems, and remediation tracking. Build and maintain observability infrastructure — metrics, logging, dashboards, and alerting — as code. Author, validate, and improve runbooks for recurring failure patterns, ensuring they're structured for low-context, safe execution. Identify high-frequency failure patterns and convert them into automated mitigations or self-healing automations. Diagnose and resolve runtime issues related to latency, memory behavior, GPU utilization, con

KubernetesGitMachine LearningAI
B
📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -79.1%

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products. ROLE We’re looking for a high-performing strategic finance professional to join our growing GTM Finance team. Our business grows with our customers' usage, which makes the finance function highly strategic at Baseten: growth, pricing, margin, and capacity decisions are business model decisions. You'll sit at the center of them, partnering directly with GTM leadership and reporting into a finance team with a seat at the table for the calls that shape the company's trajectory. This role is ideal for someone with 3 to 7 years of experience across strategic finance, investing, and/or investment banking who wants broad exposure to company-building inside a fast-scaling AI infrastructure company. Experience at a usage-based software company is a plus. RESPONSIBILITIES Own financial planning, forecasting, and budgeting processes for the GTM org Build and maintain financial models across revenue, S&M spend, headcount, and strategic bets Analyze the metrics that define a usage-based business – ARR, gross margin, consumption trends, retention, and GTM efficiency Partner with GTM leaders to set targets, evaluate growth initiatives, shape pricing, and design sales compensation Help prepare board materials, investor updates, and fundraising analyses Improve financial reporting, dashboards, and operational rigor so our infrastructure scales as fast as our revenue Work cross-functionally to turn ambiguous business questions into

SQLRestMachine LearningAI
B
📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -79.1%

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products. THE ROLE We’re looking for a high-performing strategic finance professional to join our growing Finance team. This role is ideal for someone with 3 - 4 years of experience across investment banking, venture capital, private equity and/or strategic finance who wants broad exposure to company-building inside a fast-scaling AI infrastructure company. Experience in strategic finance is a plus, but not required. You’ll work closely with Finance leadership and partner cross-functionally across the Finance leadership team. THE RESPONSIBILITIES Support company-wide financial planning, forecasting, and budgeting processes Build and maintain operating and financial models across revenue, infrastructure costs, hiring, and strategic initiatives Help prepare board materials, investor updates, and fundraising analyses Partner with business leaders to evaluate investments, acquisitions, pricing, growth initiatives, and operational tradeoffs Analyze consumption and infrastructure metrics including ARR, gross margin, usage trends, retention, and efficiency metrics Drive ad hoc strategic projects including market analysis and scenario planning Improve financial reporting processes, dashboards, and operational rigor as the company scales Act as key data and modeling lead on reporting and analysis Assist with finance operations, procurement, and vendor management as needed Work cross-functionally to turn ambiguous business questions into

SQLRestMachine LearningAI
B
📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -79.1%

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products. THE ROLE As a Forward Deployed Engineer at Baseten, you will partner directly with customers to architect, build, and deploy high-scale production AI applications on Baseten’s platform. You’ll own the journey with customers from initial exploration to production deployment, translating ambiguous business goals into reliable, observable services with clear quality, latency, and cost outcomes. This role is a great fit for entrepreneurial engineers who want a front-row view into how modern companies adopt AI at scale and who enjoy working across product, software development, performance engineering, and customer-facing implementations. To be clear, this is an engineering role with hands-on coding and software development that also includes aspects of product management, technical customer success, and pre-sales solution engineering mixed in. EXAMPLE INITIATIVES Take a look at these blog posts written by members of our Forward Deployed Engineering team: Forward Deployed Engineering on the frontier of AI The fastest, most accurate Whisper transcription Deploy production-ready model servers from Docker images Deploy custom ComfyUI workflows as APIs RESPONSIBILITIES Develop and maintain software systems and product features using one or more general-purpose programming languages in a production-level environment, with a preference for Python due to its relevance in ML projects. Drive customer impact by designing, implementin

PythonDockerMachine LearningAI
B
📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -79.1%

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products. THE ROLE We’re looking for a seasoned Frontend Engineer to craft performant and delightful user experiences across Baseten’s core platform. You’ll own critical parts of our web application stack and collaborate cross-functionally with product, design, and backend teams to launch impactful features that help users deploy and manage AI systems at scale. EXAMPLE INITIATIVES You'll get to work on these types of projects as part of our Core Product team: Rolling Deployments Model APIs for frontier models Model training built for production inference RESPONSIBILITIES Design, implement, and maintain responsive, accessible, and user-friendly frontend interfaces using React and TypeScript Collaborate closely with product designers to turn complex ideas into elegant, intuitive UIs Optimize application performance and reliability, with a focus on rendering speed and responsiveness Drive major frontend initiatives, including partnering with backend teams to define APIs and test and refine end-to-end flows Establish best practices, and mentor other engineers on frontend technologies Build reusable component libraries and frontend infrastructure that accelerate product development Partner with backend and platform teams to define and refine APIs and end-to-end flows REQUIREMENTS 5+ years of experience building production-grade web applications Deep expertise in React, TypeScript, and modern web development tooling Track record of bu

TypeScriptReactMachine LearningAI
B
📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -79.1%

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products. THE ROLE Baseten is seeking talented and experienced Software Engineers to join our Observability team within the Infrastructure organization. As an early member of the Observability Team, you will be pivotal in building and shaping the observability experience for our internal and external customers. By joining this team, you’ll have a direct impact on the reliability and operational excellence of Basetens product systems. As Baseten scales its infrastructure across different cloud providers and diverse hardware, the volume and complexity of operational data is growing by orders of magnitude. This team is responsible for building high-throughput ingest pipelines, cost-efficient storage, and agentic diagnostic tools to ensure that we can detect, diagnose, and resolve issues in minutes rather than hours, even as the systems they operate become more complex. RESPONSIBILITIES Design and build scalable telemetry ingest and storage pipelines for metrics, logs, and traces across Baseten’s multi-cloud infrastructure Own and evolve core observability platforms, driving migrations and architectural improvements that improve reliability, reduce cost, and scale with organizational growth Build instrumentation libraries, SDKs, and integrations that make it easy for engineering teams to emit high-quality telemetry from their services Drive alerting and SLO infrastructure that enables teams to define, monitor, and respond to reliabi

PythonRestMachine LearningAI
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