System Verification Co Design Engineer in New York

ROLE SUMMARY We are looking for a Senior Data Scientist to lead complex data science engagements that combine traditional statistical modelling with Generative AI. You will work hands-on with very large datasets across disparate systems and formats, translate ambiguous business problems into rigorous analytical solutions, and present those solutions clearly to C-level stakeholders. This is a delivery-first role with a fast track into technical leadership: alongside your own project work, you will help guide junior data scientists and shape how Lynx builds and ships data science solutions. KEY RESPONSIBILITIES Solution Design & Delivery Design and deliver end-to-end solutions for defined data science problems, combining classical modelling, data transformation, and Generative AI / LLM techniques. Work hands-on with very large datasets across disparate stores and formats, from ingestion and transformation through to modelling and validation. Apply statistical and machine learning methods to business problems such as customer retention, campaign management, and commercial performance optimisation. Client Communication & Leadership Present results and prepare client-ready materials for project stakeholders, including C-level audiences, translating technical work into clear business narratives. Lead smaller data science workstreams, with support from internal leadership and the PMO, including day-to-day guidance for junior team members. Partner with delivery and account teams to scope problems, set realistic timelines, and manage stakeholder expectations. Knowledge Building Create reusable documentation, presentations, and code libraries during projects so future engagements can build on prior work. Participate in internal education, research, and knowledge-sharing initiatives that raise the technical bar across the practice. SKILLS, QUALIFICATIONS AND EXPERIENCE 8+ years of overall experience in data science, with a track record of leading analytic

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam. About the Team The Embedded Insights team supports Plaid’s mission to build a world-class suite of intelligence products. We identify the best opportunities to use machine learning in Plaid products, prove out those opportunities, and collaborate with cross-functional partners to turn them into real-world production systems. About the Role As a Senior Machine Learning Engineer on Embedded Insights, you will help shape Plaid’s future by building machine learning-powered products and features. You will initially support the Plaid App, working on a 0-to-1 consumer-facing product and helping establish product-market fit for a new business line. You will work closely with product managers, data scientists, engineers, customers, and other machine learning engineers to translate ambiguous opportunities into effective ML systems that create measurable customer value. In supporting the Plaid App, you will: Build machine learning-based features for a 0-to-1 consumer-facing product. Partner with product managers to translate ambiguous business requirements into machine learning problems and influence product strategy and roadmap decisions. Rapidly iterate and experiment to help drive product

Become a part of our caring community Most AI engineering jobs are a thin wrapper around a model API. This role is different. We build the platform that transforms millions of clinical documents into trusted, actionable data. Our systems use large language models (LLMs) to read medical records, extract structured facts, answer complex questions with citations back to the source document, and route ambiguous cases to human experts for review. Our users make decisions that impact real healthcare outcomes, so “good enough” is not good enough. Building AI systems that are accurate, reliable, auditable, and scalable is at the core of this role. As a Senior AI Applied Engineer, you will design, build, deploy, and operate production AI systems used at scale within one of the largest health insurers in the United States. You will own solutions end-to-end, from user experience and APIs to model orchestration, evaluation frameworks, infrastructure, and production operations. Why Join Us Build production AI systems where LLMs are in the critical path, not just demos or proofs of concept. Work on extraction, retrieval, agentic workflows, and human-review systems that process real healthcare data at scale. Own projects end-to-end across frontend, backend, AI orchestration, infrastructure, deployment, and operations. Solve challenging problems around accuracy, explainability, traceability, and reliability in regulated environments. Ship quickly in a small, high-impact team that embraces AI-assisted development and rigorous quality standards. Build systems that continuously improve through expert feedback, evaluations, and human-in-the-loop workflows. Key Responsibilities Design, develop, and deploy full-stack AI-powered application

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Washington D.C., London and Amsterdam. We believe Plaid has the power to be the next-gen Credit Bureau - supporting large scale adoption of cash flow into the credit underwriting process. The Credit Decisioning platform team is responsible for building best-in-class cashflow based insights products that enable lenders to make more holistic lending decisions and empower broader access to Credit products for prospective borrowers. We own the systems and tooling that form the platform to build and serve these insights at huge scale, partnering with our Data partners to release new products yearly. You will be defining the future architecture of Credit insights products and executing against an ambitious product roadmap. You will partner with our Product, Data Science, and Machine Learning team to iterate on and productionize new insights that enable our customers to make more holistic lending decisions. Responsibilities: Leading technical architecture and execution across credit insights products: everything from data fetching and online feature serving for API requests, to offline production pipelines and tooling for model training. Scaling and evolving the architecture through an expected ~100x increase in load from deterministic factors

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We're looking for strong backend engineers who love building a developer tools used by the largest AI companies in the world. You’ll be building for things at scale, but also for new AI workflows that change every day. Requirements: Experience building and shipping modern web applications end-to-end. We care more about what you’ve built than how many years you’ve been building. Comfort working across the stack: TypeScript on the frontend, Python services on the backend, and ClickHouse for data and analytics. Deep knowledge of observability tools and patterns used for large-scale workloads such as custom sandboxes, training and inference for large language (LLM) and diffusion models. Experience with at least one of: billing/payments systems, B2B SaaS tooling, or enterprise software, or LLM / diffusion models inference and training loads. Strong product instincts; yo

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We’re looking for an Infrastructure Security Engineer to design and secure the core systems that power our platform. This role focuses on building security directly into our infrastructure—from container isolation and orchestration to identity and secrets management in a multi-tenant, cloud-native environment. You’ll work closely with engineering teams to define secure primitives and ensure our platform is resilient, scalable, and trustworthy by design. This is a hands-on, deeply technical role focused on real systems, not compliance or policy. What You'll Do: Platform & Runtime Security Design and improve isolation mechanisms for multi-tenant workloads (containers, sandboxing, execution environments) Strengthen boundaries between customers, workloads, and internal systems Identify and mitigate risks in distributed, dynamic compute environments Container &

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? Our team is a fast-growing group of committed researchers and engineers. The mission of the team is to build reliable machine learning systems and optimize audio inference serving efficiency using innovative techniques. As an engineer on this team, you will work on advancing core audio model serving metrics, including latency, throughput, and quality by diving deep into our systems, identifying bottlenecks, and delivering creative solutions for audio processing and streaming workloads. You’ll collaborate closely with both the training and serving infrastructure teams to ensure seamless integration between model development and deployment, with a special focus on real-time and streaming audio inference. Please Note: We have offices in Toronto, Montreal, San Francisco, New York, Paris, Seoul and London. We embrace a remote-friendly environment, and as part of this approach, we strategically distribute teams based on interests, expertise, and time zones to promote collaboration and flexibility. You'll find the Model Efficiency team concentrated in the EST and PST time zones, these are our preferred locations. You may

At Datadog, we're on a mission to build the best platform in the world for engineers to understand and scale their systems, applications, and teams. We operate at high scale, enabling seamless collaboration and problem-solving among Dev, Ops, and Security teams globally for tens of thousands of companies. Our engineering culture values pragmatism, honesty, and simplicity to solve hard problems the right way. APM at Datadog is on its way to redefine how users interact with their telemetry. We are integrating intelligence directly into troubleshooting workflows to help engineers find root causes faster, navigate complex distributed systems seamlessly, and optimize application performance with minimal cognitive load. APM provides deep visibility from end-user interactions to backend services and we are now expanding this foundation with new AI-driven insights, guidance, and automation. As a Product Manager II for APM, you will work with world-class engineers, designers, and partner product teams to shape the future of Distributed Tracing, Performance Analysis, and Intelligent Troubleshooting. You will help build advanced capabilities that scale to thousands of customers and make sophisticated observability workflows accessible to every engineer, from experts to beginners. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What you will do: Develop a deep understanding of APM customers, their performance challenges, telemetry workflows, and competitors Lead conversations with design partners and strategic customers to uncover real-world performance issues, validate product assumptions, and guide solutions from early prototypes through General Availability Define and deliver the next generation of APM features with engineering and design, especially agentic on

Datadog is seeking curious, driven interns to join our Product Management team and help build products that improve how engineers monitor and understand their systems. As a Product Management Intern, you'll support the product development lifecycle by partnering closely with Engineering, Design, and Product Marketing to bring new ideas and features to life. You'll gain hands-on experience working on products that serve highly technical customers while contributing to meaningful business and user outcomes. Interns are embedded directly within product teams, working on meaningful initiatives alongside full-time Product Managers and contributing to actual product decisions. Our platform processes over 100 trillion events per day across 30,000+ customers in a multi-cloud environment -- giving you direct exposure to large-scale, real-time systems built by engineers, for engineers. It's an environment where you'll develop product thinking, technical communication, and cross-functional collaboration skills by doing the work, not just observing it. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Conduct customer discovery conversations and gather feedback to better understand user needs Drive product initiatives from concept through launch alongside Engineering, Design, and Product Marketing teams Translate customer and business needs into clear product requirements and engineering priorities Analyze customer feedback, product data, and market insights to help inform product decisions Prepare and deliver technical product demonstrations and communication materials Develop technical understanding of Datadog’s observability platform and cloud infrastructure products Who You Are: Targeting a 2028 full-time graduation or start date Pursuing a degree in

At Datadog, we’re on a mission to build the best platform in the world for engineers to understand and scale their systems, applications, and teams. We operate at high scale, enabling seamless collaboration and problem-solving among Dev, Ops, and Security teams globally for tens of thousands of companies. Our engineering culture values pragmatism, honesty, and simplicity to solve hard problems the right way. The Observability Data Platform (ODP) is the backbone of everything Datadog delivers – powering how data is ingested, stored, routed, and surfaced across every product at planet scale. As a Senior Product Manager for ODP, you will work with world-class engineers and cross-functional partners to shape how the platform is deployed, controlled, and operated. You will define product direction across the control plane and data layer, translate complex infrastructure trade-offs into clear roadmap decisions, and help customers get the most from their observability investment – regardless of architecture, topology, or scale. At Datadog, we place value in our office culture – the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You Will Do: Develop a deep understanding of the Observability Data Platform customers – platform engineers, SREs, and product managers that own the product verticals – their infrastructure challenges, deployment topologies, and cost-to-serve trade-offs. Define product direction across multiple ODP surfaces, including the control plane and data layer, by articulating clear problem statements and desired outcomes, and partnering with engineering on technical approach and sequencing Lead conversations with design partners and strategic customers to understand real-world platform pain points, validate product assumptions, and guide solutions from early prototypes through General Availability Develop a co

Datadog is seeking a Director of Product Management to lead our AI Observability portfolio and shape how organizations build, monitor, and scale AI systems in production. This role leads LLM Observability and helps define the next wave of innovation across GPU Monitoring, Distributed AI Monitoring, and emerging research-oriented tooling such as Model Lab. You will set the vision and strategy for this rapidly growing area, expanding established products while incubating new capabilities that deliver deep visibility into AI infrastructure, model performance, and distributed AI environments. As AI becomes core to modern applications, this team plays a critical role in ensuring customers can deploy and scale AI with confidence. We’re looking for a builder-minded product leader with strong technical depth and hands-on curiosity - someone who has built or worked closely with AI-powered products and understands the realities of production AI. You will lead a team of product managers and partner closely with engineering and design to advance Datadog’s leadership in AI observability. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Own the vision and strategy for AI-driven products, ensuring alignment with overall company goals and customer needs. This will include managing our embed program to enhance the capabilities of existing products as well as developing dedicated and independent AI products. Lead and mentor a team of product managers, helping them grow and advance their careers while ensuring the delivery of high-quality, AI-powered features. Collaborate with cross-functional teams including engineering, data science, marketing, and sales to deliver AI product solutions that meet customer needs and business objectives. Identify new opportunities for

G&A at Datadog rapidly scales the physical space, hiring, onboarding, and financial and legal systems to keep our business running in top form. As a Deal Desk Analyst, you will work cross-functionally with our Sales Operations, Billing, Contracts and Legal teams to provide quoting and deal structuring support to the Global Sales Team. This will be a growth position as Datadog’s business continues to expand. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Develop in-depth knowledge of Datadog’s licensing and pricing models to provide deal structuring and quoting support to our global sales teams Be a creative problem solver who finds a way to meet customers’ needs while adhering to Datadog’s selling policies Solve customer satisfaction issues following execution of the deal Actively negotiate deals directly with the customer as needed Work cross functionally across various stakeholder groups including legal, contracts, sales operations, order management, revenue, finance and product management Function as point of contact and subject matter expert for Sales on deal pricing matters Drive adherence to internal controls, protocols and business rules Who You Are: At least 4 years of overall experience including related processes such as sales operations, finance, sales strategy, and sales enablement At least 2 years of experience with deal structuring/quoting complex SaaS transactions for a fast-growing multi-national company Working knowledge of revenue recognition principles Must be comfortable representing the company to customers in negotiations and resolving customer satisfaction issues Strong attention to detail Ability to multi-task Strong communication skills Ability to work in fast paced, high press

A World-Changing Company Palantir builds the world’s leading software for data-driven decisions and operations. By bringing the right data to the people who need it, our platforms empower our partners to develop lifesaving drugs, forecast supply chain disruptions, locate missing children, and more. The Role Forward Deployed Infrastructure Engineers (FDIEs) build, operate, and maintain the infrastructure that powers Palantir’s platforms and production deployments. As an FDIE intern, you’ll work alongside full-time FDIEs to deploy and operate Palantir software across real production environments, automate manual processes, and develop novel solutions to infrastructure challenges using tools like Foundry and Apollo. Every day looks different — you might be debugging a distributed systems issue, building automation to replace a manual runbook, or designing infrastructure improvements that scale across multiple deployments. You’ll be treated as a full member of the team, with real ownership over the work you take on. Core Responsibilities As an FDIE intern, your responsibilities look similar to those at a small startup, with the resources, stability, and mentorship of an established tech company. You’ll work in small teams with minimal supervision and own end-to-end execution of real infrastructure projects. Your day might span discussing systems architecture with fellow engineers, debugging a production issue, building automation to eliminate a manual process, or deploying new Palantir products across production environments. FDIE interns are treated just like full-time engineers, with significant freedom and ownership over their work. Specifically, you can expect to: Deploy and operate Palantir software across production environments, including monitoring, alerting, configuration management, and upgrades Debug, improve, and optimize Palantir’s services and infra

Abbott is a global healthcare leader that helps people live more fully at all stages of life. Our portfolio of life-changing technologies spans the spectrum of healthcare, with leading businesses and products in diagnostics, medical devices, nutritionals and branded generic medicines. Our 122,000 colleagues serve people in more than 160 countries. JOB DESCRIPTION: About Abbott Abbott is a global healthcare leader, creating breakthrough science to improve people’s health. We’re always looking towards the future, anticipating changes in medical science and technology. Our diagnostic solutions are used in hospitals, laboratories, and clinics around the globe. The crucial information derived from our tests, instruments and informatics systems are often the first step in patient care decision making for hundreds of health conditions from heart attacks to blood disorders to infectious diseases and cancers. Working at Abbott At Abbott, you can do work that matters, grow, and learn, care for yourself and family, be your true self and live a full life. You’ll also have access to: Career development with an international company where you can grow the career you dream of. Employees can qualify for free medical coverage in our Health Investment Plan (HIP) PPO medical plan in the next calendar year. An excellent retirement savings plan with high employer contribution Tuition reimbursement, the Freedom 2 Save student debt program and FreeU education benef

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! The Opportunity We're seeking an experienced Head of Non-Tech Talent to lead our comprehensive hiring strategy for all non-technical roles. This is a pivotal position as we build out our capabilities across General and Administrative (G&A) Go to Market (GTM) Finance, Legal, and other business-critical functions. You'll transform how we attract, hire, and develop top talent beyond while building and coaching a high performing global talent team. This is an opportunity to join an ambitious high performing, scale up company. Key Responsibilities Strategic Talent Leadership: Develop and execute the non-tech talent strategy aligned with Cohere's growth plan and business objectives while partnering with TA leads across the organization Team Development & Coaching: Recruit, mentor, and develop a high-performing team of non-tech recruiters, sourcers, and coordinators; create career paths and succession plans Process Innovation: Design and implement scalable hiring processes for non-technical roles while maintaining our high-quality standards Business Partnership: Serve as the primary talent advisor to our Talent Leads and partne