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Become a part of our caring community Help shape practical, responsible AI solutions that improve healthcare experiences and outcomes. Humana’s Enterprise AI organization develops safe, scalable AI solutions across our Insurance and CenterWell businesses. We bring together product managers, data scientists, engineers, policy experts, and business leaders to apply emerging technology to meaningful healthcare challenges. As Associate Director of Applied AI, you will lead teams that design, build, and deploy enterprise AI solutions, with a focus on generative AI and intelligent agents. You will connect technical strategy to business needs, guide responsible delivery in a regulated environment, and help teams turn promising ideas into measurable outcomes for members, patients, and associates. Key Responsibilities Lead and mentor teams developing production-ready AI solutions that improve healthcare delivery, member experiences, and business operations. Help define and execute the roadmap for applied AI initiatives in alignment with enterprise priorities and business needs. Guide the evaluation and adoption of machine learning, generative AI, large language models, multimodal models, and intelligent agent technologies. Oversee scalable APIs, frameworks, data pipelines, retrieval-augmented generation solutions, and agent orchestration capabilities. Partner with product, data science, engineering, architecture, security, and business teams to translate requirements into reliable solutions. Establish standards for AI evaluation, obse

About the Team The Legal team is building the next generation of AI-powered products and experiences for the legal industry. We are exploring how advanced AI systems can transform legal workflows, improve access to information, and enable legal professionals and organizations to work more effectively. As a founding member of the Legal engineering team, you will help define the technical foundation for this new product area from the earliest stages. You’ll operate at the intersection of AI, product, and real-world legal workflows—identifying opportunities, building prototypes, and turning emerging ideas into scalable products that can create meaningful impact. We operate with a startup-like mindset inside OpenAI: small teams, rapid iteration cycles, and a willingness to explore bold ideas, learn quickly, and adapt based on user feedback. Our goal is to build products that meaningfully improve how legal professionals work while leveraging OpenAI’s cutting-edge models and infrastructure. About the Role As a Founding Full-Stack Software Engineer on the Legal team, you will help imagine, build, and scale new AI-powered products for the legal industry. You’ll work across the stack to design intuitive user experiences, build robust backend systems, and create the foundations for products used by legal professionals and organizations around the world. You’ll have significant ownership from the earliest stages—working closely with product, design, research, and go-to-market partners to understand customer needs, shape product direction, and deliver high-impact solutions. This includes rapidly prototyping new concepts, building production-quality applications on top of OpenAI’s platforms, and developing new technical approaches when existing systems are not sufficient. We’re looking for engineers who thrive in ambiguity, have strong product instincts, and enjoy building from 0→1. You should be comfortable moving quickly, making thoughtful technical decisions, and taking owner

About the Team The Safety Systems team is dedicated to ensuring the safety, robustness, and reliability of AI models and their deployment in the real world. Building on the many years of our practical alignment work and applied safety efforts, Safety Systems addresses emerging safety issues and develops new fundamental solutions to enable the safe deployment of our most advanced models and future AGI, to make AI that is beneficial and trustworthy. Learn more about OpenAI’s approach to safety About the Role As an Analytics Engineer in Safety Systems, you will play a pivotal role in building a data-centric culture, enhancing decision-making processes, and driving strategic initiatives through analytics. You will partner closely with Engineering, Research, and Data Science to develop and maintain canonical data sources and source-of-truth dashboards that enable both people and AI agents across the organization to derive trustworthy, actionable insights. You will own the consumption layer for safety metrics: defining intuitive, reliable ways for stakeholders across Safety Systems, partner teams, and leadership to understand the safety of our products, answer safety-related questions independently, and inform product decisions and company strategy. Most importantly, you will be a core member of the Safety Systems team, collaborating with researchers and engineers to advance our goals of safe, robust, and reliable AI. 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: Design and maintain canonical datasets that serve as sources of truth for safety metrics. Develop and refine data products such as dashboards, reports, agent-enabled workflows, and machine-readable interfaces that empower stakeholders to extract and analyze data independently. Work closely with stakeholders in Engineering, Research, and Data Science to understand their decision-making n

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 As a member of the Capacity Strategy & Operations team, you will sit at the intersection of supply intelligence, demand forecasting, and cross-functional execution, turning a complex, fast-moving hardware market into a predictable, reliable foundation for our customers and internal engineering teams. This is not a purely analytical role. You will own the end-to-end capacity planning process: from translating customer commitments and growth forecasts into concrete supply requirements, to coordinating fulfillment across vendors, finance, and the infrastructure team, to building the systems that make all of this repeatable and scalable. When supply is constrained and tradeoffs are unavoidable, you are the person in the room who can model the options, make a clear recommendation, and drive alignment fast. You are a strong fit if you have operated at the intersection of strategy and execution before — someone who is equally comfortable building a capacity model in a spreadsheet and running a cross-functional war room when a customer deployment is at risk. EXAMPLE INITIATIVES Demand-Supply Alignment Framework: Build and own the process that translates customer pipeline, signed commitments, and growth projections into a forward-looking GPU demand signal — so the team is never caught flat-footed when a customer scales faster than expected. Constrained Allocation Playbook: Define the decision framework for how Basete

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 Platform team within the Infrastructure organization. As a senior member of Baseten's Platform Team, you will own the systems that let every engineer at Baseten prove their code works before it reaches production. Our product runs mission-critical AI inference for customers who measure downtime in dollars per second, which means our internal bar for correctness, performance, and failure tolerance has to be exceptional. Your focus is the full testing stack: fast and reliable unit test tooling, integration harnesses that spin up realistic environments on demand, load and performance testing for GPU-backed inference workloads, and resilience testing that deliberately breaks things so our customers never have to find out what happens when a node dies mid-request. This is a builder role with org-wide leverage. You won't be writing tests for other teams — you'll be building the frameworks, harnesses, and feedback loops that make writing good tests the path of least resistance, and you'll set the standards for what "well-tested" means at Baseten. RESPONSIBILITIES Own Baseten's testing strategy end to end — define the standards, the tiers, and the tooling that engineering teams build against. Build and maintain unit, integration, load and performance testing frameworks Design end to end test infrastructure that provisions realistic dependencies

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

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 Platform team within the Infrastructure organization. As an early member of Baseten's Platform Team, you will be pivotal in building internal infrastructure to support our engineering organization. You will own the deployment platform, release pipelines, and rollout safety mechanisms that allow engineers across Baseten to deploy changes rapidly while minimizing operational risk. Our mission is to make production deployments fast, safe, and increasingly autonomous. If you are passionate about elegant solutions—like streamlined monorepos, lightning-fast CI pipelines, and thoughtfully designed shared libraries—you'll thrive at Baseten. RESPONSIBILITIES Design and build continuous deployment infrastructure that safely rolls out changes across dozens of Kubernetes clusters and global regions. Develop systems for progressive delivery, including canary releases, staged rollouts, and automated rollback. Improve engineering velocity by reducing friction in the release pipeline and automating manual operational workflows. Work with product and infrastructure teams to ensure their services are deployable, observable, and resilient at scale. Implement and evolve deployment methodologies such as GitOps, infrastructure-as-code, and progressive delivery patterns. Build systems that automatically evaluate deployment health using metrics, logs, traces,

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 Marketing Operations Manager who can own and harden the systems layer of Baseten's Marketing engine. Marketing at Baseten is scaling fast — more spend, more campaigns, more model launches, more inbound. The systems underneath (Our ESP, CRMs, forms, tracking, routing, alerting) need an owner who treats them like production infrastructure that cannot go down. When something breaks, it costs us time, pipeline, and trust in the data. This role exists so it doesn't break. You’ll simultaneously build for the future and re-think assumptions about our tech stack in the age of agents. This is an offensive play that gives the rest of the team leverage and superpowers to hit our ambitious goals. This is NOT an IT or service role. This is a core member of the marketing team who implements technology to achieve outcomes. RESPONSIBILTIES Own the marketing tech stack end-to-end: ad platforms, email systems, tracking, pixels, forms, connectors. Build defense-in-depth on inbound: spam/bot protection, rate limiting, email/domain validation, sync gating — and the alerting to catch anomalies before they hit sales or leadership dashboards. Enforce data integrity: UTM governance, campaign membership, lifecycle stages, lead scoring and routing logic, field-level hygiene, canonical metric definitions. Operationalize the web request pipeline with our dev agency: structured briefs, tickets, SLAs, and launch-day runb

Software Engineer - III About the Role GHX is building a next-generation Intelligent Process Automation (IPA) platform powered by LLMs and AI-native document understanding. We extract structured data from complex healthcare procurement documents — Purchase Orders, invoices, contracts — at scale across cloud environments. As a member of the IPA engineering team, you will bridge strong software engineering with applied AI. You will design and ship Python services, integrate LLM APIs, build AI agents, create skills and validate the output of LLMs to build document extraction pipelines, and own evaluation infrastructure that ensures production quality. This is not a research role — it is a hands-on engineering role where AI fluency amplifies solid software craft. Core Responsibilities Python Development & Automation Build and maintain Python-based automation services and IPA workflows Develop platform-agnostic solutions supporting future migration across automation tooling Build reusable libraries, frameworks, and components for automation projects Integrate automation solutions with REST APIs and enterprise applications Deploy and monitor automation bots on AWS (Lambda, ECS, SQS, S3) AI & LLM Integration Integrate LLM APIs (like Anthropic Claude, OpenAI, Azure AI) into production pipelines Design classification and extraction prompts for diverse document types (POs, invoices, contracts) Write prompts that function as formal specifications — unambiguous, edge-case-aware Build and iterate few-shot, chain-of-thought, and structured output templates Own prompt library versioning, rollback strategy, and prompt lifecycle management AI & LLM Integration Integrate LLM APIs (like Anthropic Claude, OpenAI, Azure AI) into production pipelines Design classification and extraction prompts f

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Every day, millions of riders and drivers depend on Lyft to get where they're going. When something goes wrong along the way, they expect us to make it right — quickly, clearly, and without friction. How fast and how well we resolve those moments shapes whether people keep choosing Lyft. The Self-Serve Intelligence team, within the Safety & Customer Care org, is composed of engineers building the AI-powered systems that do exactly that: resolving rider and driver suboptimal experiences without agent involvement through AI Assist (e.g. AI Agents), automations, and self-serve workflows. Our goal is to make getting help feel effortless. We design and build backend services, APIs, and GenAI-powered products that combine robust engineering with applied AI to deliver reliable, scalable self-serve experiences. We are looking for a highly motivated, collaborative, team-focused and technically strong Software Engineer to join our Self-Serve Intelligence team. As a member of this team, you will build the services and AI-powered products that resolve customer issues autonomously. Every day, you'll partner with machine learning engineers, product, design, data science, and operations on high-impact projects — from shipping new AI Agent capabilities, to building the evaluation pipelines that keep their quality high, to improving the backend services underneath them. You'll bring strong engineering instincts, genuine curiosity about applied AI, and a willingness to work through ambiguity in a space that changes month to month. Responsibilities: Write well-crafted, well-tested, readable, and maintainable code Partner with senior engineers to design, build, and ship backend services and GenAI-powered products (e.g. AI Agents) that resolve rider and driver suboptimal experiences Independently lead tasks fro

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why This Role? North is Cohere’s AI workspace platform for enterprises: a secure, customizable environment where companies can use AI across their real workflows while maintaining control over sensitive data. North connects AI agents with workplace tools, applications, and business context, helping users delegate complex work, build automations, inspect outputs, and collaborate with AI in production environments. As North becomes more capable, one of the most important questions is also one of the hardest: how do we know whether the model is actually getting better for the workflows customers care about? This role is about being the voice of North inside modelling. You will build the evaluation systems, feedback loops, and applied modelling workflows that make sure model progress translates into better product outcomes for North users. You will work closely with North product teams, customer-facing teams, and modelling teams to define what “good” means across the product surface, turn real usage and product direction into high-quality evals, and use those evals to guide model selection, patches, and regular model updates. This i

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why This Role Is Different This is not a typical “Applied Scientist” or “ML Engineer” role. As a Member of Technical Staff, Applied ML, you will: Work directly with enterprise customers on problems that push LLMs to their limits. You’ll rapidly understand customer domains, design custom LLM solutions, and deliver production-ready models that solve high-value, real-world problems. Train and customize frontier models — not just use APIs. You’ll leverage Cohere’s full stack: CPT, post-training, retrieval + agent integrations, model evaluations, and SOTA modeling techniques. Influence the capabilities of Cohere’s foundation models. Techniques, datasets, evaluations, and insights you develop for customers will directly shape the next generation of Cohere’s frontier models. Operate with an early-startup level of ownership inside a frontier-model company. This role combines the breadth of an early-stage CTO with the infrastructure and scale of a deep-learning lab. Wear multiple hats, set a high technical bar, and define what Applied ML at Cohere becomes. Few roles in the industry combine application, research, customer-facing engineeri

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why This Role Is Different This is not a typical “Applied Scientist” or “ML Engineer” role. As a Member of Technical Staff, Applied ML, you will: Work directly with enterprise customers on problems that push LLMs to their limits. You’ll rapidly understand customer domains, design custom LLM solutions, and deliver production-ready models that solve high-value, real-world problems. Train and customize frontier models — not just use APIs. You’ll leverage Cohere’s full stack: CPT, post-training, retrieval + agent integrations, model evaluations, and SOTA modeling techniques. Influence the capabilities of Cohere’s foundation models. Techniques, datasets, evaluations, and insights you develop for customers will directly shape the next generation of Cohere’s frontier models. Operate with an early-startup level of ownership inside a frontier-model company. This role combines the breadth of an early-stage CTO with the infrastructure and scale of a deep-learning lab. Wear multiple hats, set a high technical bar, and define what Applied ML at Cohere becomes. Few roles in the industry combine application, research, customer-facing engineeri

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why this role? As a Member of Technical Staff on our Applied ML team, you will work directly with customers to quickly understand their greatest problems and design and implement solutions using Large Language Models. You’ll apply your problem-solving ability, creativity, and technical skills to close the last-mile gap in Enterprise AI adoption. You’ll be able to deliver products like early startup CTOs/CEOs do and disrupt some of the most important industries and institutions globally! As a Member of Technical Staff, you will: Plan and execute large-group projects that carry through from ideation to production. Bring cross-functional alignment across engineering, product and other disciplines. Mentor a distributed team of engineers in subject matter expertise. Identify opportunities and gaps in existing models and strategize what to work on. Work closely with product teams to develop solutions. Engage in collaborations with our partner organizations. Assist our legal teams with preparation of patents on developed IP. Join us at a pivotal moment, shape what we build and wear multiple hats! You may be a good fit if you have: Prio

NVIDIA has continuously reinvented itself over two decades. Our invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing. NVIDIA is a “learning machine” that constantly evolves by adapting to new opportunities that are hard to solve, that only we can address, and that matter to the world. This is our life’s work, to amplify human creativity and intelligence. Make the choice to join us today. Design-for-Test Engineering at NVIDIA works on groundbreaking innovations involving crafting creative solutions for DFT architecture, verification and post-silicon validation on some of the industry's most complex semiconductor chips. What you'll be doing: As a senior member in our team, you will work with pre-silicon and post-silicon data analytics - visualization, insights and modeling. Design and uphold sturdy data pipelines and ETL processes for the ingestion and processing of DFX Engineering data from various origins Lead engineering efforts by collaborating with cross-functional teams (execution, analytics, data science, product) to define data requirements and ensure data quality and consistency You will work on hard-to-solve problems in the Design For Test space which will involve application of algorithm design, using statistical tools to analyze and interpret complex datasets and explorations using Applied AI methods. In addition, you will help develop and deploy DFT methodologies for our next generation products using Gen AI solutions. You will also help mentor junior engineers on test designs and trade-offs including cost and quality. What we need to see: BSEE (or equivalent experience) with 5+, MSEE with 3+, or PhD wi