Machine Millwright Titleist Jobs

Upwork Inc.’s (Nasdaq: UPWK) family of companies connects businesses with global, AI-enabled talent across every contingent work type including freelance, fractional, and payrolled. This portfolio includes the Upwork Marketplace, which connects businesses with on-demand access to highly skilled talent across the globe, and Lifted, which provides a purpose-built solution for enterprise organizations to source, contract, manage, and pay talent across the full spectrum of contingent work. From Fortune 100 enterprises to entrepreneurs, businesses rely on Upwork Inc. to find and hire expert talent, leverage AI-powered work solutions, and drive business transformation. With access to professionals spanning more than 10,000 skills across AI & machine learning, software development, sales & marketing, customer support, finance & accounting, and more, the Upwork family of companies enables businesses of all sizes to scale, innovate, and transform their workforces for the age of AI and beyond. Since its founding, Upwork Inc. has facilitated more than $30 billion in total transactions and services as it fulfills its purpose to create opportunity in every era of work. Learn more about the Upwork Marketplace at Upwork.com and follow us on LinkedIn , Facebook , Instagram , TikTok , and X ; and learn more about Lifted at Go-Lifted and follow on LinkedIn . Interested in joining our Talent Community? Perhaps, the right role for you is just around the corner. Feel free to submit your resume and we'll keep your resume ready for the right role. Upwork has various exciting roles as our company continues to grow. If you didn't find a role currently open that fit your skill set, then please feel free to join our talent community. The Upwork Talent Community, will hold your resume and contact you as soon as a role opens that may fit your specific skills and career goals. Come change how the world works. At Upwork, you’ll shape the future of work for a global, remote-

Fin is the AI Customer Agent company on a mission to help businesses provide perfect customer experiences. Our AI Agent Fin is the highest-performing AI Customer Agent on the market today, enabling businesses to deliver impeccable, always-on customer support across the customer journey – from service, to sales, to ecommerce. Powered by our own AI models, Fin resolves complex customer issues end-to-end across every channel, with minimal set-up and integration. Fin can also be combined with our natively integrated Intercom help desk for one single system that is designed to meet the needs of modern day support teams. Founded in 2011, Fin became one of the fastest growing companies and remains one of the largest private software companies in the world with nearly 30,000 global businesses using our products to transform their customer support. Driven by our core values, we push boundaries, build with speed and intensity, and relentlessly deliver incredible value to our customers. What's the opportunity? Fin's AI Group is responsible for defining new ML products, researching appropriate algorithms and technologies, and rapidly getting first prototypes in our customers’ hands. We are extremely product-focussed. Our team of 50+ ML scientists, ML engineers, designers and researchers works in partnership with other teams across the whole company. We move to production fast, often shipping to beta in weeks after a successful offline test. We are very passionate about applying machine learning technology, and have productized everything from classic supervised models, to cutting-edge unsupervised clustering algorithms, novel applications of transformer neural networks and fine-tuned LLMs. We test and measure the real customer impact of everything we deploy. We plan to double in size, and are on the lookout for an experienced manager to manage a team of highly-performing ML scientists. Engineering managers in Fin are not just people

The AI Retrieval team powers the intelligence behind Asana's AI features by finding relevant work graph content and delivering it to LLM context windows. Our work enables AI features that truly understand your work—both within and outside of Asana—and use that understanding to take action. We also own Asana's traditional search experience. As a Staff Software Engineer on the AI Retrieval team, you'll build the systems that make Asana's AI smart and responsive. You'll tackle challenging problems in search and retrieval, working to improve the speed, cost-efficiency, and quality of our systems while expanding their capabilities to new data sources. This role is based in our Warsaw office with an office-centric hybrid schedule. The standard in-office days are Monday, Tuesday, and Thursday. Most Asanas have the option to work from home on Wednesdays. Working from home on Fridays depends on the type of work you do, and your recruiter can share more about the in-office requirements. We offer a Contract of Employment (UoP) for our employees in Poland. What you'll achieve Reduce the latency and cost of our retrieval system, making Asana's AI features faster and more efficient Improve the quality and relevance of search results to help users find exactly what they need Expand the retrieval system's capabilities to query new Asana objects and third-party data sources Build and optimize search infrastructure using OpenSearch/ElasticSearch Contribute to ML-powered features like embeddings-based retrieval and semantic search Collaborate with cross-functional partners in New York City while building strong relationships with your Warsaw-based peers About you 6+ years of experience writing code in a production environment Demonstrates curiosity about AI tools and emerging technologies, with a willingness to learn and leverage them to enhance productivity, collaboration, or decision-making Hands-on experience in search engineering, including with OpenSearch or ElasticSearch E

The AI Retrieval team powers the intelligence behind Asana's AI features by finding relevant work graph content and delivering it to LLM context windows. Our work enables AI features that truly understand your work—both within and outside of Asana—and use that understanding to take action. We also own Asana's traditional search experience. As a Senior Software Engineer on the AI Retrieval team, you'll build the systems that make Asana's AI smart and responsive. You'll tackle challenging problems in search and retrieval, working to improve the speed, cost-efficiency, and quality of our systems while expanding their capabilities to new data sources. This role is based in our Warsaw office with an office-centric hybrid schedule. The standard in-office days are Monday, Tuesday, and Thursday. Most Asanas have the option to work from home on Wednesdays. Working from home on Fridays depends on the type of work you do, and your recruiter can share more about the in-office requirements. We offer a Contract of Employment (UoP) for our employees in Poland. What you'll achieve Reduce the latency and cost of our retrieval system, making Asana's AI features faster and more efficient Improve the quality and relevance of search results to help users find exactly what they need Expand the retrieval system's capabilities to query new Asana objects and third-party data sources Build and optimize search infrastructure using OpenSearch/ElasticSearch Contribute to ML-powered features like embeddings-based retrieval and semantic search Collaborate with cross-functional partners in New York City while building strong relationships with your Warsaw-based peers About you 6+ years of experience writing code in a production environment Demonstrates curiosity about AI tools and emerging technologies, with a willingness to learn and leverage them to enhance productivity, collaboration, or decision-making Hands-on experience in search engineering, including with OpenSearch or ElasticSearch

As organizations rapidly adopt AI applications and agentic systems, security teams need visibility and control over how these technologies are being used. Datadog's AI & Data Security product helps customers discover, secure, and govern AI usage across their environments ensuring sensitive data is properly managed from model training through production. As a Product Manager II for AI & Data Security, you will own capabilities for AI discovery, posture management, and data security; giving customers complete visibility into their AI applications, agents, and enabling ecosystem, with prioritized actions to operate AI systems securely. You'll partner with engineering, design, security research, and GTM teams to define and ship platform capabilities that help organizations adopt AI at 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’ll Do: Own the roadmap for AI & Data Security capabilities, including AI and data discovery & posture management. Define how security teams can assess and manage the security posture of AI-enabled systems, including configuration risks, sensitive data exposure, and policy violations. Work closely with engineers and designers to deliver new product capabilities end-to-end, from early concept through launch and iteration. Partner with Datadog security researchers to identify emerging risks in AI systems and translate them into actionable product features. Engage with customers to understand how they are adopting AI and validate solutions that help them operate these systems securely. Collaborate with go-to-market teams to enable adoption and communicate the value of AI security capabilities to customers. Who You Are: You have 3+ years of product management experience building technical products, ideally in security,

As organizations rapidly adopt AI applications and agentic systems, security teams need visibility and control over how these technologies are being used. Datadog's AI & Data Security product helps customers discover, secure, and govern AI usage across their environments ensuring sensitive data is properly managed from model training through production. As a Product Manager II for AI & Data Security, you will own capabilities for AI discovery, posture management, and data security; giving customers complete visibility into their AI applications, agents, and enabling ecosystem, with prioritized actions to operate AI systems securely. You'll partner with engineering, design, security research, and GTM teams to define and ship platform capabilities that help organizations adopt AI at 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’ll Do: Own the roadmap for AI & Data Security capabilities, including AI and data discovery & posture management. Define how security teams can assess and manage the security posture of AI-enabled systems, including configuration risks, sensitive data exposure, and policy violations. Work closely with engineers and designers to deliver new product capabilities end-to-end, from early concept through launch and iteration. Partner with Datadog security researchers to identify emerging risks in AI systems and translate them into actionable product features. Engage with customers to understand how they are adopting AI and validate solutions that help them operate these systems securely. Collaborate with go-to-market teams to enable adoption and communicate the value of AI security capabilities to customers. Who You Are: You have 3+ years of product management experience building technical products, ideally in security,

Senior Product Manager - Search Datadog’s Search team helps users – both human and agents – find answers to their questions. Search is a critical function in Datadog, and touches many product surfaces: the query editors in product homepages and dashboards, search bars for finding relevant assets, the global cmd+k navigation search, and the MCP tools that our Bits AI agent uses to respond to natural language prompts. Search is a full-stack team: owning user-facing search components, backend search ranking systems, and machine learning models to produce recommendations. The Search team is relatively new, and still growing. We have recently built out agentic search tools, and we are looking for a leader to help us expand to ambitious orchestration systems that deliver accurate results, and proactive recommendations across both keyword and semantic search. Beyond this, you’ll have room to influence how Datadog thinks about Search as a strategic surface. What you’ll do: Define and deliver how Datadog's AI agents discover the right context and tools to answer natural-language questions accurately and at scale Stay on top of industry trends in UI and agentic search experiences and capabilities Collaborate with Applied AI teams to integrate ranking, personalization, and recommendation models that scale across both human and agentic users Define and monitor KPIs for search quality, adoption, and downstream impact on user productivity; use them to drive data-informed decision making Engage directly with customers and internal product teams to deeply understand search journeys across query editors, global navigation, and natural-language agent interfaces Who you are: You have experience with search, ranking, or recommendation systems You are familiar with or very interested in MCP servers and differences between human and agentic UX You have a sharp eye for design and strong opinions on the micro-interactions — keyboard navigation, autocomplete behavior, loading

As a Senior Product Manager for AI & Data Security at Datadog, you will define and deliver capabilities that help organizations securely adopt and scale AI across their applications and infrastructure. You’ll focus on building products that provide visibility into AI systems and data usage, assess security posture, and enable teams to manage risk across the AI lifecycle. This role sits at the intersection of security, AI, and cloud platforms, and is ideal for a PM who thrives in emerging, ambiguous problem spaces. You will work cross-functionally to shape how customers discover, understand, and secure AI-powered systems in production. 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 and drive the roadmap for AI & Data Security capabilities, including data security posture management and data loss prevention Define how customers assess and manage the security posture of AI systems, including risks related to configuration, data exposure, and policy compliance Partner with engineering and design to deliver end-to-end product capabilities, from concept through launch and iteration Collaborate with security research teams to identify emerging risks in AI systems and translate them into actionable product features Engage with customers to understand AI adoption patterns and validate solutions that enable secure, scalable operations Define and track success metrics such as product adoption, usage, and impact on customer security workflows Who You Are: &l

As a Research Scientist on our team, you will partner with Research Engineers, working on fundamental research problems and collaborating with Datadog's product and engineering teams to translate research advances into products. Building on our track record of AI-powered solutions (e.g., Bits AI , Bits Evolve , and our time series foundation model ), Datadog AI Research tackles high-risk, high-reward problems grounded in real-world challenges in cloud observability and security. We are focused on two research areas: World Models for Observability -- Training multimodal foundation models that learn the joint dynamics of distributed systems across metrics, traces, logs, topology, and events. These models power advanced forecasting, anomaly detection, root cause analysis, counterfactual simulation ("what if?"), and provide a learned planning backbone for our autonomous agents. Trained Agents for Observability -- Post-training models to operate autonomously across Datadog's domain. SRE incident response is our first target, with a clear path to code repair, security response, and infrastructure optimization. We build the simulation environments, RL training loops, and evaluation infrastructure needed to train agents that match or surpass frontier models at a fraction of the cost. What You'll Do: Conduct research in generative AI and machine learning, building specialized foundation models and trained agents for observability Train multimodal models on large-scale, diverse telemetry data (metrics, logs, traces, topology, events) using distributed training infrastructure Design and build simulated environments and RL training loops for on-policy agent training and evaluation Collaborate with cross-functional teams (Product, Engineering) to integrate capabilities like multimodal world modeling and autonomous agents into Datadog's products Stay at the forefront of foundation models, world models, and RL-based agent research Contribute to r

Datadog is looking for a resourceful and creative Associate Field Marketing Manager to lead event strategy and execution for Datadog's AI product line across the East and Canada region. This role is ideal for someone who is passionate about AI and developer communities, enjoys getting hands-on with technical audiences, and wants to build a market-leading brand presence for Datadog's AI offerings. As part of the NAMER Field Marketing team, you will own the strategy, planning, and execution of a mix of practitioner-focused events, hands-on workshops, and surround activations at major AI conferences. This role is critical to scaling awareness and adoption of Datadog's AI products, and to building durable relationships with AI customers, prospects, and the broader developer community. 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 strategy, planning, and end-to-end execution of AI practitioner events, hands-on workshops, and meetups across the East and Canada Lead surround and off-site activations at major AI conferences (e.g., NVIDIA GTC, Ray Summit, AI Engineer Summit, and similar industry events) to build brand visibility and drive engagement with target audiences Partner with Product Marketing and AI/ML product teams to translate Datadog's AI observability and LLM monitoring capabilities into compelling, technically credible event content Design and continuously improve hands-on workshop curriculum and live demos that showcase Datadog's AI products to practitioners and technical decision-makers Build scalable, repeatable event playbooks and toolkits so programs can be run consistently across multiple markets Manage vendors, venues, budgets, staffing, and on-site logistics, ensuring every event reflects Datadog's brand and delivers a seamles

As a Research Scientist on our team, you will partner with Research Engineers, working on fundamental research problems and collaborating with Datadog's product and engineering teams to translate research advances into products. Building on our track record of AI-powered solutions (e.g., Bits AI , Bits Evolve , and our time series foundation model ), Datadog AI Research tackles high-risk, high-reward problems grounded in real-world challenges in cloud observability and security. We are focused on two research areas: World Models for Observability -- Training multimodal foundation models that learn the joint dynamics of distributed systems across metrics, traces, logs, topology, and events. These models power advanced forecasting, anomaly detection, root cause analysis, counterfactual simulation ("what if?"), and provide a learned planning backbone for our autonomous agents. Trained Agents for Observability -- Post-training models to operate autonomously across Datadog's domain. SRE incident response is our first target, with a clear path to code repair, security response, and infrastructure optimization. We build the simulation environments, RL training loops, and evaluation infrastructure needed to train agents that match or surpass frontier models at a fraction of the cost. What You'll Do: Conduct research in generative AI and machine learning, building specialized foundation models and trained agents for observability Train multimodal models on large-scale, diverse telemetry data (metrics, logs, traces, topology, events) using distributed training infrastructure Design and build simulated environments and RL training loops for on-policy agent training and evaluation Collaborate with cross-functional teams (Product, Engineering) to integrate capabilities like multimodal world modeling and autonomous agents into Datadog's products Stay at the forefront of foundation models, world models, and RL-based agent research Contribute to r

Figma is growing our team of passionate creatives and builders on a mission to make design accessible to all. Figma’s platform helps teams bring ideas to life—whether you're brainstorming, creating a prototype, translating designs into code, or iterating with AI. From idea to product, Figma empowers teams to streamline workflows, move faster, and work together in real time from anywhere in the world. If you're excited to shape the future of design and collaboration, join us! Figma’s Observability engineering team builds and operates the systems that give us deep visibility into the health, performance, and efficiency of our platform. From metrics, logs, and traces to cost attribution and budgeting, this team ensures that engineers across Figma can detect issues quickly, understand system behavior at scale, and make informed decisions about reliability and spend. The team owns and evolves our core observability stack—including platforms like Datadog, shared instrumentation libraries, and the agents and operators that power telemetry collection—while continuously raising the bar on signal quality and operational clarity. This team ensures that engineers across Figma can detect issues quickly, understand system behavior at scale, and make informed decisions about reliability. The team owns and evolves our core observability stack—including platforms like Datadog, shared instrumentation libraries, the agents and operators that power telemetry collection, and a host of internally developed components to power AI Trace Observability —while continuously raising the bar on signal quality and operational clarity. As the Engineering Manager for Observability, you will lead a team of five engineers responsible for shaping the future of visibility and efficiency at Figma. You’ll define the strategy for instrumentation standards and cost transparency, drive initiatives to optimize observability footprint and spend, and explore innovative AI-driven approaches to anomaly detection

Join us in building the future of finance. Our mission is to democratize finance for all. An estimated $124 trillion of assets will be inherited by younger generations in the next two decades. The largest transfer of wealth in human history. If you’re ready to be at the epicenter of this historic cultural and financial shift, keep reading. About the team + role We are building an elite team of bold thinkers and sharp problem-solvers who are wired to make an impact. The Ops Platform organization develops internal platforms that replace repetitive manual processes with AI-driven systems. These tools support key areas such as Fraud Operations, Account Operations, Financial Crimes Operations, and Retirement Services. The team works closely with product, data science, and operations partners to deliver reliable systems that improve decision-making and efficiency! As a Software Developer, you will design and build platforms that enable operational teams to investigate and resolve issues more quickly and accurately. You will work with large datasets and signals to create tooling that supports fraud investigation and other operational workflows. You will collaborate with data scientists and machine learning engineers to translate manual processes into automated systems. Your work will focus on improving system reliability, reducing operational effort, and increasing the speed at which new products and features can be supported across Robinhood’s offerings. This role is based in our Toronto, ON office, with in-person attendance expected at least 3 days per week. At Robinhood, we believe in the power of in-person work to accelerate progress, spark innovation, and strengthen community. Our office experience is intentional, energizing, and designed to fully support high-performing teams. What you’ll do You will define technical direction and make architectural decisions for systems that support operational workflows across multiple product lines You will build tools that proces

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. As the Engineering Manager for the Lakehouse Foundation team, you will lead a group of engineers responsible for the foundational data layer that all of Lyft's data systems and emerging AI workloads are built on. The team owns catalog and metadata management, table formats and storage, and the access patterns and gateways through which other engineering teams interact with Lyft's data. As Lyft converges on a unified lakehouse architecture, this team builds and operates the single source of truth that powers analytics, machine learning, experimentation, and every business decision made from data. You will play a key role in shaping the team's technical direction, partnering with peer Data Platform teams on a multi-year platform evolution, and developing engineers who operate with autonomy on systems of significant scale and complexity. Lyft's Infrastructure teams build the foundational systems that the rest of engineering depends on to move fast, ship reliably, and scale efficiently. These are high-leverage roles where the work you and your team do has a multiplicative effect across the company. We're looking for experienced leaders who can balance the discipline of operating critical infrastructure with the curiosity to keep evolving how Lyft builds. Engineering at Lyft is a place where managers and engineers operate with high ownership and strong technical judgment. Our engineers expect their managers to be honest, available, and focused on the work that matters: developing their teams, removing obstacles, and giving people the support they need to do their best work. We build teams that are inclusive, technically rigorous, and have a strong sense of ownership for what they build. Responsibilities: Lead a team responsible for Lyft's foundational data layer, including catalog and metadata management,

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. As an Applied Scientist specializing in Machine Learning and Operations Research on this team, you will develop mathematical models and launch algorithms that power these key pricing and ETA decisions. You will leverage your skills to build ML and optimization models and productionalize pipelines that can scale to millions of calls per day while solving critical business problems that have a big impact on the marketplace and rider experience. You will get exposure to a diverse set of real-world problems across optimization, prediction, machine learning, and inference and collaborate closely with teammates and stakeholders across Pricing, from Product Managers to Engineers and Analysts. We are looking for someone who is excited about working in a fast-paced, innovative, and impactful environment, and is adept at balancing complexity and efficiency to translate real world business problems into reliable solutions, systems and decision frameworks. Responsibilities Partner with Data Scientists, Engineers, Product Managers, and Business Partners to frame problems mathematically and within the business context Write production quality code. Design, build and deploy production-grade ML and Optimization models. Able to build custom methods and tooling beyond off-the-shelf libraries. Perform data analysis and build proof-of-concepts to explore and propose ML and Optimization solutions to both new and existing problems. Evaluate machine learning systems against business goals. Collaborate with Engineers to implement algorithms in live systems and ensure the robustness of the systems Establish metrics and development measurement methodologies to monitor the health of our products, as well as the impacts on user and marketplace outcomes Drive collaboration and coordination with cross-functional teams