Machine Vision And Aoi Sr Engineer Jobs

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. REQUIREMENTS Product Positioning & Technical Narrative Own the positioning and messaging for Baseten’s dedicated inference and platform capabilities, including autoscaling, routing, failover, release safety, observability, and cost/performance capabilities. Translate infrastructure-heavy product work into buyer narratives for ML engineering, platform engineering, security, compliance, procurement, and executive audiences. Partner with Product and Engineering to understand the technical architecture, customer value, roadmap tradeoffs, and proof points behind each capability. Define when a capability should be positioned as a platform differentiator, a dedicated inference requirement, a reliability story, a compliance story, or sales enablement. Build messaging that is technically credible without being overly implementation-focused or generic. Launch Strategy & GTM Execution Build and execute launch plans for major dedicated inference and serving platform capabilities, from early internal enablement through external announcement. Decide what deserves a full launch versus what should ship through docs, sales enablement, customer-specific materials, or targeted enterprise outreach. Create launch assets including messaging briefs, landing pages, blog posts, sales decks, one-pagers, FAQs, demo storylines, competitive talk tracks, and customer-facing proof points. Sequence launches and supporting assets based on custom

About the Role The Agents team investigates how to build, align, and scale frontier AI systems that can tackle complex, multi-step tasks and workflows across text and speech, with a particular focus on agentic and scientific domains. Our work sits at the intersection of agent capabilities, human-computer interaction, and infrastructure—from designing post-training methods for agentic behavior to developing evaluation frameworks for open-ended tasks where traditional metrics fall short. As a research intern, you will work on problems at the frontier of agentic AI, where challenges in alignment, reliability, and scalability are deeply intertwined. Projects may involve developing new training recipes for self-learning and long-horizon reasoning, curating datasets for non-deterministic scientific and agentic tasks, studying failure modes in agentic behavior, or building infrastructure that enables agent operations at scale. You'll operate in a space where algorithmic innovation, dataset and interaction design, and systems work come together to push the boundaries of what AI agents can reliably accomplish. Responsibilities Research and implement novel techniques in one or more of our focus areas Design and conduct rigorous experiments to validate hypotheses Document findings in scientific publications and blog posts Communicate the plans, progress, and results of projects to the broader team Requirements Currently pursuing a Ph.D. degree in Computer Science, Electrical Engineering, Information Science, or a related field Publications at leading ML, NLP, or speech conferences or journals (such as NeurIPS, ICML, ICLR, *ACL, EMNLP, Interspeech) Strong knowledge of Machine Learning and Deep Learning fundamentals Experience with deep learning frameworks (PyTorch, JAX, etc.) Understanding of how LLMs work Strong programming skills in Python Familiarity with Transformer architectures and recent developments in foundation models Example Research Directions Training, develo

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. We’re looking for a Field Application Engineer who’s wired for AI/ML, fluent in real-world problem-solving, and excited to build with the people actually using what we make. You will collaborate closely with the sales team and enterprise customers, leveraging your deep technical knowledge in AI to drive the adoption of our products and solutions. This is a customer-facing role that requires both technical expertise and excellent communication skills to convey complex technical concepts to non-technical stakeholders. This role is remote based out of North America with preference near one of our main hubs Santa Clara, CA; Boston, MA; or Toronto,ON. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are You’ve lived in the AI/ML trenches, whether as a field engineer, a solutions architect, or the one tapped in when things needed to “just work.” You speak both machine and human. Whether it’s a researcher or a skeptical executive, you know how to break things down and bring them to life. You’re fired up about generative models, LLMs, and the edge of what’s possible when software meets purpose-built silicon. Work directly with customers in mee

About the Role The Agents team investigates how to build, align, and scale frontier AI systems that can tackle complex, multi-step tasks and workflows across text and speech, with a particular focus on agentic and scientific domains. Our work sits at the intersection of agent capabilities, human-computer interaction, and infrastructure—from designing post-training methods for agentic behavior to developing evaluation frameworks for open-ended tasks where traditional metrics fall short. As a research intern, you will work on problems at the frontier of agentic AI, where challenges in alignment, reliability, and scalability are deeply intertwined. Projects may involve developing new training recipes for self-learning and long-horizon reasoning, curating datasets for non-deterministic scientific and agentic tasks, studying failure modes in agentic behavior, or building infrastructure that enables agent operations at scale. You'll operate in a space where algorithmic innovation, dataset and interaction design, and systems work come together to push the boundaries of what AI agents can reliably accomplish. Responsibilities Research and implement novel techniques in one or more of our focus areas Design and conduct rigorous experiments to validate hypotheses Document findings in scientific publications and blog posts Communicate the plans, progress, and results of projects to the broader team Requirements Currently pursuing a Ph.D. degree in Computer Science, Electrical Engineering, Information Science, or a related field Publications at leading ML, NLP, or speech conferences or journals (such as NeurIPS, ICML, ICLR, *ACL, EMNLP, Interspeech) Strong knowledge of Machine Learning and Deep Learning fundamentals Experience with deep learning frameworks (PyTorch, JAX, etc.) Understanding of how LLMs work Strong programming skills in Python Familiarity with Transformer architectures and recent developments in foundation models Example Research Directions Training, develo

About The Role The Inference Research team is dedicated to building the next generation of efficient, scalable, and reliable serving systems for large foundation models, directly contributing to the mission of advancing open and transparent AI. Our work operates at the critical intersection of cutting-edge model architectures, high-performance systems engineering, and deep hardware optimization. We focus on co-designing software, algorithms, and models to significantly lower the cost and latency of modern AI systems. As a research intern, you will dive into the complexities of distributed inference, compiler-aware optimization, and novel inference-time computation strategies (such as speculative decoding and phase-aware execution). You will be tasked with co-designing and implementing cross-layer optimizations across models, systems, and hardware, with a focus on areas like KV cache design and large-scale serving architectures. Projects aim to unlock unprecedented performance and scale for foundation models, enabling faster serving, larger model deployment (e.g., Mixture-of-Experts), and robust, reproducible evaluation under realistic serving workloads. Responsibilities Design and conduct rigorous experiments to validate hypotheses Communicate the plans, progress, and results of projects to the broader team Document findings in scientific publications and blog posts Requirements Currently pursuing a final year of Bachelor's, Master's, or Ph.D. degree in Computer Science, Electrical Engineering, or a related field Strong knowledge of Machine Learning and Deep Learning fundamentals Experience with deep learning frameworks (PyTorch, JAX, etc.) Strong programming skills in Python Familiarity with Transformer architectures and recent developments in foundation models Preferred Qualifications Prior research experience in foundation models , efficient machine learning , or ML systems . Publications at leading conferences in machine learning or systems (i.e., ML

About The Role The Inference Research team is dedicated to building the next generation of efficient, scalable, and reliable serving systems for large foundation models, directly contributing to the mission of advancing open and transparent AI. Our work operates at the critical intersection of cutting-edge model architectures, high-performance systems engineering, and deep hardware optimization. We focus on co-designing software, algorithms, and models to significantly lower the cost and latency of modern AI systems. As a research intern, you will dive into the complexities of distributed inference, compiler-aware optimization, and novel inference-time computation strategies (such as speculative decoding and phase-aware execution). You will be tasked with co-designing and implementing cross-layer optimizations across models, systems, and hardware, with a focus on areas like KV cache design and large-scale serving architectures. Projects aim to unlock unprecedented performance and scale for foundation models, enabling faster serving, larger model deployment (e.g., Mixture-of-Experts), and robust, reproducible evaluation under realistic serving workloads. Responsibilities Design and conduct rigorous experiments to validate hypotheses Communicate the plans, progress, and results of projects to the broader team Document findings in scientific publications and blog posts Requirements Currently pursuing a final year of Bachelor's, Master's, or Ph.D. degree in Computer Science, Electrical Engineering, or a related field Strong knowledge of Machine Learning and Deep Learning fundamentals Experience with deep learning frameworks (PyTorch, JAX, etc.) Strong programming skills in Python Familiarity with Transformer architectures and recent developments in foundation models Preferred Qualifications Prior research experience in foundation models , efficient machine learning , or ML systems . Publications at leading conferences in machine learning or systems (i.e., ML

Our Global Structure Deliveroo is now part of DoorDash, bringing together teams with even greater reach, scale, and ambition. Depending on your role, you may collaborate with teammates, systems, and leaders across DoorDash and Wolt. Together, we’re unlocking new possibilities as one global team. About the Role Hybrid (3 days per week in the London office required) Individual contributor role Fraud is constantly evolving. As our business grows, so do the ways bad actors seek to exploit our products, promotions, and operations. As the Senior Strategy & Operations Manager for Emerging Fraud & Abuse, you'll lead the discovery, investigation, and mitigation of new and evolving abuse vectors across our platform. Your mission is to identify risks before they become systemic, working across Product, Engineering, Data Science, Operations, Legal, and Policy to design scalable solutions that protect our customers, partners, and business. This isn't a role focused on running existing fraud programmes. It's about identifying what's next. You'll combine deep analytical thinking with strategic problem solving to uncover emerging threats, quantify business impact, influence product strategy, and build new controls that keep us ahead of increasingly sophisticated fraudsters. If you enjoy solving ambiguous problems, following the data, and building solutions where no playbook exists, we'd love to hear from you. What You'll Do Identify Emerging Abuse Proactively identify new fraud patterns, abuse trends, and vulnerabilities across our products, customer journeys, and operational processes. Investigate anomalies, understand attacker behaviours, and translate observations into actionable mitigation strategies. Continuously scan for evolving risks, whether driven by organised fraud, policy loopholes, technological change, or new product launches. Build the Strategy Define the roadmap for emerging fraud prevention across the business. Prioritise risks based on

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. The Agent Gateway Team The Agent Gateway team owns the identity-aware infrastructure that connects enterprise AI agents to the tools, data, and services their organizations authorize. Every call from Claude, Agentforce, Codex, and internal/homegrown agents to a resource flows through us. We enforce authorization, isolate credentials, mint the right token per target, and produce the audit trails that security teams rely on. We are early in a rapidly evolving space. The standards for agent identity (MCP, OAuth token exchange, DCR) are being built under our feet. Our roadmap includes hardening the data plane for on-premises customer deployments, extending policy semantics beyond tool-level allowlists, adding native support for Agent-to-Agent brokered delegation, and scaling to tenants with thousands of virtual MCP servers. The Senior Software Engineer Opportunity Okta is looking for a Senior Software Engineer to help build the Agent Gateway. You will own features and components across the data and control planes, turning technical designs and product requirements into reliable production systems. Working alongside staff engineers, you will implement token exchange, request routing, credential resolution, and policy evaluation as agent identity specifications evolve. This is a hands-on software development role at the intersection of product, security, and infrastructure. You will ship services that handle agentic traffic reliably and performantly at scale. Wha

Who We Are Addepar is a global data and AI platform empowering investment professionals to turn complex financial information into actionable intelligence. Addepar unifies portfolio, market and client data in a total portfolio view and delivers AI-powered insights within investment and client workflows. More than 1,500 firms in 60 countries use Addepar to manage and advise on nearly $10 trillion in assets. Its open platform integrates with 650 software, data and consulting partners to power end-to-end investment operations across firms of all sizes and levels of complexity. Addepar supports clients worldwide with offices in New York City, Salt Lake City, São Paulo, London, Edinburgh, Geneva, Warsaw, Dubai, Pune and Singapore. The Role Addepar has just launched an Alternatives Product offering that gives Addepar clients the option to have their Private Funds data extracted, processed, validated, and ingested directly from Private Fund documents for a more automated end-to-end solution for handling Alternatives on the platform. This white-glove solution combines proprietary machine learning technology that automatically extracts data from Private Funds documents and human-in-loop review to validate any documents that fail to pass confidence and data quality checks. As part of the broader Addepar Data organization, the Alternatives Data Ops team is responsible for the human-in-loop review of Private Funds documents, ensuring clients' Alternatives data is processed, validated, and available in Addepar in a timely manner. This role will include managing a team and reviewing Private Fund statements, modifying data that has been incorrectly extracted by our machine learning models, and reprocessing the data within SLAs. The Alternatives Data Ops team plays a critical role in the success of Addepar's Alternatives offering and requires daily communications with the Alternatives Product Team, Machine Learning Operations, clients, data providers (GPs and Fund Admins), and addi

About Sapience AI Sapience AI is the collective intelligence platform for professional communities. We sit above the CRMs, AMS platforms, and knowledge bases that organizations already run, and we turn the expertise scattered across them into something every member can search, act on, and share. The intelligence a community needs is already inside it. Most organizations just cannot reach it. Knowledge lives in silos, in legacy systems, in the heads of a few experts, and in fragmented records no one can connect. We change that. Our work is grounded in four commitments: technology elevates people and never replaces them, the best expertise is already inside the community, everything is built on trust, and every deployment is purpose-driven for the organization it serves. Let’s achieve more, together. Where this role sits This is a research role focused on the models at the foundation of collective intelligence. You study, adapt, and advance the foundational models that power how Sapience AI understands language, knowledge, and reasoning. You work where research meets the platform: designing experiments, evaluating models, adapting them to the demands of professional communities, and feeding what you learn into the COGENT architecture and MINERVA. You bring scientific rigor to a fast-moving field, and you turn that rigor into advances the product can actually use. Why this role exists The quality of collective intelligence depends on the models beneath it. How well the platform understands a community’s language, grounds its answers, and reasons over knowledge starts with foundational model work done well. The field moves quickly, and not every advance is real or ready. Someone has to separate genuine progress from noise and turn the real advances into something the platform can rely on. The Foundational Model Research Data Scientist does that. You run the experiments, evaluate honestly, and translate frontier progress into dependable capability for Sapience AI. What y

Sapience AI is the collective intelligence platform for professional communities. We sit above the CRMs, AMS platforms, and knowledge bases that organizations already run, and we turn the expertise scattered across them into something every member can search, act on, and share. The intelligence a community needs is already inside it. Most organizations just cannot reach it. Knowledge lives in silos, in legacy systems, in the heads of a few experts, and in fragmented records no one can connect. We change that. Our work is grounded in four commitments: technology elevates people and never replaces them, the best expertise is already inside the community, everything is built on trust, and every deployment is purpose-driven for the organization it serves. Let’s achieve more, together. Where this role sits This role owns the heart of how Sapience AI reasons. You lead the neuro-symbolic approach that combines symbolic knowledge, structure, and rules with neural and language-model capability, the approach that lets the platform reason over a community’s expertise with both flexibility and rigor. You own the direction of the COGENT architecture: how it fuses the KO (knowledge object) graph and symbolic reasoning with neural models, how it stays trustworthy and explainable, and how it advances over time. You lead a specialized team and partner across research, applied AI, and knowledge graph engineering to turn a hard idea into a working system at the center of MINERVA. Why this role exists Pure neural systems are fluent but can be confidently wrong, and they struggle to explain themselves. Professional communities cannot act on answers they cannot trust or trace. Collective intelligence needs reasoning that is both flexible and grounded. Bringing symbolic structure and neural capability together is one of the hardest and most valuable problems in applied AI. It is also the core of what makes Sapience AI different. The Head of Neuro-Symbolic AI owns that problem. You set the

At ClickUp, we're building the future of work: the first truly converged AI workspace unifying tasks, docs, chat, calendar, and enterprise search, all supercharged by context-driven AI. We are an AI-native company. Every team member is expected to leverage AI daily, and we evaluate AI fluency as part of our hiring process. Join us and help redefine what's possible. 🚀 About the Role ClickUp is looking for an FP&A Manager to serve as the financial business partner across three functions: R&D, G&A, and Corporate. You'll own the full cycle of forecasting, month-end close, and budget vs. actuals reporting for each, partnering directly with department leaders and the accounting team. This is a high-autonomy role on a lean Strategic Finance team where you'll have real ownership from day one. What You'll Do R&D: Own expense management, vendor and invoice approvals, headcount planning, non-headcount forecasting, cloud infrastructure cost tracking, and month-end variance analysis and leadership reporting. G&A: Drive expense forecasting, headcount planning, vendor approvals, and month-end close activities including variance analysis and BvA reporting for G&A departments. Corporate: Prepare board of directors, QFR, and investor-ready reporting decks. Manage billings actualization and forecasting, and deliver monthly finance readouts to executive leadership. Partner with Accounting through the monthly close cycle, including soft close, hard close, and results review with budget owners. Maintain rolling forecasts, provide variance commentary for material deviations, and lock forecasts on a monthly cadence. Collaborate cross-functionally with recruiting, procurement, and department leaders on headcount and spend decisions. Leverage AI tools to accelerate forecasting workflows, variance commentary, and ad-hoc analysis, setting the bar for AI-augmented FP&A on the team. What We're Looking For 5+ years of FP&A or strategic finance experience, ideally

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. About Okta Secures AI Team The Okta Secures AI Team is building the future of digital identity management. The way companies are using agents and allowing them access is undergoing a fundamental shift, enabling teams to move fast while staying secure. Our North Star is clear: To get AI right, you have to get identity right. We are not just managing identities; we are building the industry's first Identity Security Fabric for the agentic era. As organizations rapidly deploy AI, these non-human entities are acting with access to critical tools, often bypassing traditional perimeters and creating a 'Shadow AI' crisis. Our mission is to move identity from a reactive gatekeeper to a unified control plane, transforming AI risk into business ROI. We are tackling this by implementing a comprehensive four-pillar maturity model: Discover, Onboard, Protect, and Govern. We are driving innovation by defining the standards for Agentic Identity—including pioneer work with securing AI Agents and support for protocols like MCP. You will be helping us build the infrastructure that allows enterprises to scale AI safely, ensuring every access decision—whether made by a human or an automated agent—is authenticated, authorized, and audited at scale. We are a diverse team of engineers, product managers, and designers who are bringing Okta’s expertise in identity to define the future of Agent Identity management, focusing on enablement while staying secure. About the role &n

About Us: Comfrt is one of the fastest-growing direct-to-consumer brands, dedicated to blending mental wellness, inclusivity, and elevated comfort into every piece we create. Our mission goes beyond clothing — we strive to build a community where everyone feels supported and seen. About the Job: The Senior Manager of Logistics owns the strategic and operational management of Comfrt's outbound carrier network and parcel optimization initiatives. This role leads national and regional parcel carriers, LTL, and final-mile carrier relationships through data-driven negotiations and multi-carrier strategy. By applying advanced analytics, carrier profitability modeling, zone-skipping strategies, and AI-powered optimization, this role reduces single-carrier risk, drives cost savings, and scales logistics operations efficiently. This role enables Comfrt's D2C expansion across new markets and channels while maintaining service excellence, sustainability commitments, and unit economics. Outbound logistics is the final mile of Comfrt's customer promise and directly impacts both customer satisfaction and margins. This role translates strategic revenue and margin targets into practical carrier network design, rate contracts, and operational execution. By managing multi-carrier contingency, optimizing parcel economics through dimensional weight reduction, implementing sustainable packaging innovations, and maintaining service level commitments, this role builds a scalable operating model that supports rapid expansion without service or cost surprises. This role is critical to Comfrt's competitive positioning in D2C and multi-channel fulfillment markets. Responsibilities: Outbound Carrier Network Strategy & Multi-Carrier Optimization [40%] Own relationships with national parcel carriers (UPS, FedEx, DHL), regional carriers, USPS, LTL providers, and emerging logistics partners; maintain quarterly business reviews aligned to carrier profitability models and performance score

Who we are At Twilio, we’re shaping the future of communications, all from the comfort of our homes. We deliver innovative solutions to hundreds of thousands of businesses and empower millions of developers worldwide to craft personalized customer experiences. Our dedication to remote-first work , and strong culture of connection and global inclusion means that no matter your location, you’re part of a vibrant team with diverse experiences making a global impact each day. As we continue to revolutionize how the world interacts, we’re acquiring new skills and experiences that make work feel truly rewarding. Your career at Twilio is in your hands. . Hiring and how we work We use Artificial Intelligence (AI) to help make our hiring process efficient. That said, every hiring decision is made by real Twilions! Also, while we are a remote-first company, you may be asked to report in person on an ad-hoc basis for team gatherings, functional off-sites or customer meetings. . See yourself at Twilio Join the team as Twilio’s next emerging Fraud Researcher. About the job This position is needed to detect emerging fraud trends and behaviors on Twilio Network, across all channels - voice, messaging and email. You will work on researching new fraud behaviors by analyzing industry trends and analyzing billions of events using AI tools. Responsibilities In this role, you’ll: Perform independent research using AI tools to identify novel emerging fraud trends Work with data scientists to create ML models to detect fraud behaviors at scale Continuously stress test our network for vulnerabilities Analyze large-scale messaging and voice traffic to identify novel patterns of fraudulent activity, including AIT and ATO. Develop and execute proactive fraud mitigation strategies to protect customers and the network. Collaborate with data science and engineering teams to refine detection models and reduce false positives. Conduct in-depth investigations int