Senior Machine Learning Operations Engineer Jobs

Sr. Data Scientist The team + the role Pendo's GTM Intelligence Team turns data into measurable outcomes across Sales, Marketing, and Customer Engineering. We combine analysis, ML models, and internal tooling to answer high-value business questions and help GTM teams work faster and more effectively. We measure success by the real business value our work creates. As a Senior Data Scientist, you'll own the full lifecycle of intelligence solutions, from problem definition and analysis through model development, stakeholder enablement, and ongoing iteration. You'll work directly with GTM teams to surface high-value business problems and answer them with the right mix of analytics and modeling, translating what you find into decisions that stick. The best person for this role has strong modeling instincts, genuine curiosity about how GTM businesses operate, and the judgment to know when a complex model is the right tool — and when a well-framed SQL query gets you there faster. This role is based in Raleigh, NC and follows Pendo's hybrid model: in-office 3 days per week. What this looks like day-to-day Leverage data analysis, machine learning, and predictive modeling to identify opportunities and mitigate risks for our GTM teams, from problem framing through delivery and ongoing iteration Work collaboratively with data & AI engineers, analysts, revenue operations, and GTM stakeholders to ensure your work is actionable, interpretable, and clearly connected to business decisions Translate model outputs and analytical findings into clear business narratives through slides, write-ups, presentations, and async video Leverage AI-assisted development tools (Cursor, Claude Code) to accelerate delivery and prototype faster, while applying the critical thinking to validate, refine, and own the output Share and build reusable patterns, model documentation, and technical findings with the broader team Answer high-value business questions through analysis and experimentation: dev

About Ema Ema is building the world’s leading Agentic AI platform to transform enterprise productivity. We enable organizations to delegate repetitive tasks to Ema, the Universal AI Employee, delivering 10x gains in workforce efficiency, across functions. Founded by former executives from Google, Coinbase, Flipkart, and Okta, our team includes engineers from premier tech companies and graduates of Stanford, MIT, UC Berkeley, CMU, and IITs. We are backed by industry leading investors including Accel, Naspers/Prosus, Section32, and angels like Sheryl Sandberg and Dustin Moskovitz. Headquartered in Silicon Valley and with offices in London, Bangalore and Vancouver, Ema is at the frontier of what Agentic AI can do in production — we ship real systems that run real business processes at scale. Role: Senior Technical Support Specialist (Enterprise Agentic AI) Company: Ema Unlimited Inc. Location: London Employment Type: Full-time/Remote 1. About Ema (Why Ema) Ema is building the world’s first Universal AI Employee — a production-grade agentic AI platform that automates real enterprise workflows across HR, IT, Finance, and Operations. Ema’s customers do not run demos. They replace mission-critical, manual business processes with agentic AI systems that operate across multiple SaaS tools, APIs, and human-in-the-loop workflows. In this world, support is not reactive . Support is production reliability, trust preservation, and system learning . At Ema, Senior Technical Support Specialists are operators of live AI systems , not ticket handlers. 2. Role Overview The Senior Support Engineer owns the health, reliability, and trustworthiness of Ema’s deployed agentic AI systems in production. This role sits at the intersection of: AI behavior Workflow orchestration Enterprise integrations Customer trust Engineering feedback loops This is: ❌ Not L1 / call-center support, ❌ Not a “just escalate to engineering” role, ❌ Not reactive firefighting only This is : A senior technical escal

Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way. The Community You Will Join: Machine Learning and Artificial Intelligence are at the heart of the Airbnb product. From Trust to Payments, and from Customer Service to Marketing we rely on ML to ensure that guests and hosts have the best possible experience with Airbnb. The CS AI product team is responsible for driving CSxAI (Customer Support x Artificial Intelligence) initiatives by adopting the Generative AI technologies to enable an intelligent, scalable and exceptional service experience. The team develops and enhances various AI models, ML services and tools including LLM fine-tuning, alignment and optimization, RAG/Search, LLM evaluation and testing automation, feedback-based learning and guardrail for a wide range of applications in Airbnb. The Difference You Will Make: As a senior staff machine learning engineer, you will be responsible for fine-tuning state-of-the-art LLMs for diverse use cases while optimizing models for high-performance deployment on Airbnb’s ML Infrastructure. You will partner with product managers, software engineers, data scientists and operation teams to brainstorm, design and develop AI products such as AI Assistant, Autonomous agent, recommendation, travel planning, and many more products that make meaningful impacts in the world of travel. A Typical Day: Work with large scale structured and unstructured data; explore, experiment, build and continuously improve foundation models for Airbnb product, business and operational use cases. Create a multi-year tech roadmap that enables our team to stay on the leading edge of the rapidly evolving AI landscape and

Location Details: At GoDaddy the future of work looks different for each team. Some teams work in the office full-time, others have a hybrid arrangement (they work remotely some days and in the office some days) and some work entirely remotely. Remote: This is a remote position, so you’ll be working remotely from your home. You may occasionally visit a GoDaddy office to meet with your team for events or meetings. Join our team Our Global Sustaining Engineering team sits at the intersection of software engineering and infrastructure, ensuring the services our customers depend on are fast, resilient, and always available. As a Senior Site Reliability Engineer, you'll take direct ownership of production services — from initial design through day-to-day operation — while partnering with product, engineering, and security teams to build and maintain business-critical systems. In this role, you will deepen your technical expertise and grow your leadership presence by mentoring the next generation of SREs. You will also gain hands-on experience with intelligent tooling in real-world workflows. What you'll get to do... Design, implement, and operate scalable, highly available production services while diagnosing and resolving complex infrastructure, network, and application issues Build and maintain alerting pipelines, dashboards, and SLO-driven monitoring strategies using Icinga, Prometheus, and Grafana Lead incident response end-to-end — performing root-cause analysis, authoring blameless post-mortems, and driving corrective actions to closure Develop and extend Infrastructure as Code coverage and build internal tooling that eliminates manual, repetitive operational work Mentor SRE I and SRE II engineers through code reviews, debugging sessions, and knowledge-sharing talks Apply LLM-driven log analysis, anomaly detection, and generative AI tools to accelerate incident response and runbook creation — validating all outputs before use Your experien

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. Company Description Okta is the leading independent provider of enterprise identity. The Okta Identity Cloud enables organizations to securely connect the right people to the right technologies at the right time. With over 6,500 pre-built integrations, Okta customers can easily and securely use the best technologies for their business. Over 7,950 organizations — including JetBlue, Nordstrom, Slack, and Twilio — trust Okta to protect the identities of their workforces and customers. Position Description We are looking for an experienced Senior Software Engineer – UI to join our Identity Platform engineering team. You will own the design and delivery of complex, enterprise-grade frontend experiences that power Okta's identity lifecycle management capabilities — including admin configuration flows, wizard UIs, real-time progress tracking, and bulk operation workflows. You will partner closely with Product Management, UX, and backend engineers to translate complex enterprise identity requirements into intuitive, accessible, and performant web applications. This is a hybrid position. Job Duties and Responsibilities - Frontend Ownership: Independently own and deliver complex UI features end-to-end — from design collaboration through production deployment. - Architecture & Standards: Lead frontend architectural decisions, enforce code quality, accessibility, perfor

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 Infrastructure Platform and Shared Services Team Okta authenticates, authorizes and provisions millions of users a day. The service is hosted on Amazon Web Services (AWS) across multiple availability zones and geographically separated regions. The service is designed for high throughput and 99.999 availability. We're looking for a technical leader to help us continue to scale the service with great people and reliable, cost-effective, and efficient infrastructure, processes, and tooling. As the Sr. Manager of Infrastructure Platform and Shared Services, you will oversee multiple teams focused on Edge networking, K8s platform, Observability, automation platform & tooling. What you’ll be doing Lead the Infra platform and shared services org and various initiatives across SRE & Infrastructure organization. Build a world-class observability platform and monitoring capabilities enabled with self-service Accelerate the velocity of SRE and product engineering by developing robust platforms, powerful tooling, and intuitive self-service capabilities. Own the design and operation of scalable, self-service Cloud infrastructure platforms (e.g. Observability Platform, SRE Productivity, deployments, and Edge Infrastructure) Lead, mentor, and grow a high-performing team of engineers and managers across SRE and infrastructure shared services domains. Perform engineering design evaluations and ensure the completion of projects within resource,

At Anyscale , we're on a mission to democratize distributed computing and make it accessible to software developers of all skill levels. We’re commercializing Ray , a popular open-source project that's creating an ecosystem of libraries for scalable machine learning. Companies like OpenAI , Uber , Spotify , Instacart , Cruise , and many more, have Ray in their tech stacks to accelerate the progress of AI applications out into the real world. With Anyscale, we’re building the best place to run Ray, so that any developer or data scientist can scale an ML application from their laptop to the cluster without needing to be a distributed systems expert. Proud to be backed by Andreessen Horowitz, NEA, and Addition with $250+ million raised to date. About the Role Anyscale's security and compliance needs are growing as we work with larger and more demanding customers. Compliance is increasingly a customer-facing, contractual function rather than an internal exercise, and we are looking for someone to own it. This role owns that function end to end: our audits, our evidence base, our risk register, and the security diligence that customers put us through before and during a contract. You will work directly with the Head of Security and across engineering, IT, legal, and sales. This is a program-ownership role with the autonomy and accountability that implies. You will not have a senior compliance function above you to defer to; you are that function. In your first year, success looks like a complete and defensible evidence base with clean audit outcomes, a repeatable way to answer customer security diligence, and a risk register that leadership actually uses. What You'll Do Own our SOC 2 Type II and ISO 27001 programs, and future frameworks as we take them on, including scope, evidence, control operation, and the relationship with our external auditors. Own and complete the control evidence base in our compliance automation platform, moving controls from partially substantia

We are looking for a Quantitative Equity Analyst to join our Quantitative Equity Team! We are a high-performance team embedded in a top-performing quantitative equity fund that manages over $78+ billion USD in financial assets. We are dedicated to the mission-critical operation of our investment engine—a well-tuned machine responsible for generating key decisions that drive trades and investment insights. Leveraging finance skills and cutting-edge technology, we ensure data quality, continuous process improvement, and operational excellence. As a core member of our team, you'll collaborate with investment experts to tackle challenging analytical problems, be accountable to ensure accurate and timely trade generation, and drive operational innovation. Based in West Coast Vancouver, we value mentorship, collaboration, and growth in a supportive and innovative environment. Join us to make a significant impact on our investment engine and overall success. What You Will Do This is an exciting full-time role for individuals who are passionate about learning the quantitative equity investment management business and excited to tackle a broad range of investment, mathematical, and technology challenges. You will start with a comprehensive training program, learning about various elements of quantitative equity investment management and our investment process. You will then continue to a specialized role utilizing data science and process engineering skillsets to accelerate the Quantitative Equities Team’s various investment functions. Your specialized role may involve building, scaling, managing and/or analyzing our quantitative model, portfolios, data assets and optimizers. You will be supported with coaching and mentorship from senior members of the team. We are creating the conditions for you to grow your career steadily over time. Investment Process Management The team you will be joi

Since 2003, Entrata has evolved from a visionary, student-led startup into a global leader in AI-driven property management technology. Today, we power the industry's most essential operating system, serving owners and residents worldwide through a comprehensive suite of intelligent leasing, payment, and communication tools powered by cutting-edge AI. With a proven track record of sustained growth and a global team of more than 2,200 employees, we offer the rare combination of established stability and high-velocity innovation. Recognized by the Silicon Slopes Hall of Fame and the Utah Business Fast 50, Entrata fosters a culture of radical transparency and entrepreneurial energy. At Entrata, we create an environment where different perspectives are valued and respected. Those perspectives challenge assumptions, strengthen our decisions, and raise the bar as we reshape the global living experience through AI-powered solutions. We are seeking a Senior Machine Learning Engineer to help build and scale Entrata’s applied AI capabilities. This role will focus on adapting and fine-tuning foundation models for property management use cases, building reliable model training and evaluation pipelines, and deploying AI systems into production.

Senior Machine Learning Engineer Description - We are looking for a Senior MLOps Engineer to design, build, and operate the infrastructure that enables machine learning models and large language models to be deployed safely, reliably, and at scale. In this role, you will create the end-to-end capabilities required to move models from experimentation into production, expose them through secure and highly available endpoints, and enable users and applications to interact with AI-powered services. You will work across AWS and Databricks to establish robust CI/CD pipelines, model-serving infrastructure, observability, governance, rollback mechanisms, and operational standards. You will partner closely with data scientists, machine learning engineers, software engineers, security teams, and platform engineers. The ideal candidate combines strong cloud and DevOps engineering skills with a practical understanding of machine learning systems, LLM deployment patterns, and production reliability. Key Responsibilities MLOps Platform and Architecture Design and implement a scalable MLOps platform using AWS and Databricks. Define reference architectures and reusable deployment patterns for traditional machine learning models, deep learning models, and large language models. Build standardized workflows that move models from development and validation into staging and production. Develop self-service capabilities that allow data scientists and ML engineers to deploy models without manually managing infrastructure. Establish clear separation between development, testing, staging, and production environments. Design multi-region or multi-availability-zone architectures where required by business continuity and availability objectives. CI/CD and

We're transforming the grocery industry At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers. Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table. Instacart is a Flex First team There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work. Overview The Digital Twin Platform team at Instacart is on a mission to understand exactly what is on store shelves at all times — bringing the precision and depth of a smart warehouse to every local grocery store across North America. Inventory estimates power some of the most critical products at Instacart, from search to logistics, and this team sits at the center of it all. Operating like a startup within a larger company, the team drives the end-to-end shelf data supply chain: ingesting data from retail partners, actively collecting novel inventory observations, developing sophisticated models, and integrating those outputs into live products at scale. We are looking for a Senior Machine Learning Engineer to help build the next generation of platforms for understanding, observing, and predicting inventory levels and in-store stocking dynamics in real time. In

We're transforming the grocery industry At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers. Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table. Instacart is a Flex First team There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work. Overview The Digital Twin Platform team at Instacart is on a mission to understand exactly what is on store shelves at all times — bringing the precision and depth of a smart warehouse to every local grocery store across North America. Inventory estimates power some of the most critical products at Instacart, from search to logistics, and this team sits at the center of it all. Operating like a startup within a larger company, the team drives the end-to-end shelf data supply chain: ingesting data from retail partners, actively collecting novel inventory observations, developing sophisticated models, and integrating those outputs into live products at scale. We are looking for a Senior Machine Learning Engineer to help build the next generation of platforms for understanding, observing, and predicting inventory levels and in-store stocking dynamics in real time. In

Role Purpose We’re looking for a Staff/Senior Machine Learning Engineer with deep expertise in computer vision and biometrics to lead the design and scaling of face recognition systems in production. You’ll build and train models, and own ML systems end-to-end on AWS. The final job level for this role will be determined following the interview process. What You’ll Do Lead the design and development of computer vision systems for biometrics (face attributes, detection, quality, and recognition) Rigorous fairness analysis and benchmarking of biometric models across various datasets and operating conditions. Architect, train, and optimize models using PyTorch, Tensorflow, and/or JAX Own and evolve end-to-end ML pipelines, from data ingestion to deployment. Design automated pipelines (Airflow) for data ingestion and cleaning. You will be responsible for curating balanced training sets and generating synthetic data to address both quality and diversity gaps. Production Engineering: Own the path to production. Optimize models for low-latency inference (quantization, distillation, TensorRT/ONNX) and manage deployment on AWS. Mentor ML engineers, conduct code/design reviews, and drive technical best practices across the Computer Vision team. What We’re Looking For Experience: 5+ years of industry experience in Machine Learning, with at least 3 years dedicated to Biometrics or Face Analysis. Deep expertise in computer vision and biometrics, especially face recognition. Fairness & Ethics: You understand the sources of algorithmic bias in Computer Vision and have practical experience measuring and mitigating disparate impact. Strong Engineering: Expert proficiency in Python (both machine learning and vision libraries such as Pillow, OpenCV, PyTorch, etc). You write clean, modular, production-ready code. Systems Architecture: Experience designing end-to-end ML pipelines (Data to Train to Deploy) and working with workflow orchestrators like Airflow. Cloud Native: Hands-on ex

Machine Learning Engineer IV – (Computer Vision) We’re looking for a Staff/Senior Machine Learning Engineer with deep expertise in computer vision and biometrics to lead the design and scaling of face recognition systems in production. You’ll build and train models, and own ML systems end-to-end on AWS. The final job level for this role will be determined following the interview process. What You’ll Do Lead the design and development of computer vision systems for biometrics (face attributes, detection, quality, and recognition) Rigorous fairness analysis and benchmarking of biometric models across various datasets and operating conditions. Architect, train, and optimize models using PyTorch, Tensorflow, and/or JAX Own and evolve end-to-end ML pipelines, from data ingestion to deployment. Design automated pipelines (Airflow) for data ingestion and cleaning. You will be responsible for curating balanced training sets and generating synthetic data to address both quality and diversity gaps. Production Engineering: Own the path to production. Optimize models for low-latency inference (quantization, distillation, TensorRT/ONNX) and manage deployment on AWS. Mentor ML engineers, conduct code/design reviews, and drive technical best practices across the Computer Vision team. What We’re Looking For Strong industry experience in Machine Learning, dedicated to Biometrics or Face Analysis. Deep expertise in computer vision and biometrics, especially face recognition. Fairness & Ethics: You understand the sources of algorithmic bias in Computer Vision and have practical experience measuring and mitigating disparate impact. Strong Engineering: Expert proficiency in Python (both machine learning and vision libraries such as Pillow, OpenCV, PyTorch, etc). You write clean, modular, production-ready code. Systems Architecture: Experience designing end-to-end ML pipelines (Data to Train to Deploy) and working with workflow orchestrators like Airflow. Cloud Native: Hands-on exper

About the Team The Strategic Finance team at OpenAI plays a critical role in shaping the company’s long-term trajectory. We partner closely with Product, Engineering, and Go-To-Market teams to inform high-stakes decisions through rigorous data science and economic modeling. As part of our expanding Data Science function, we’re building a best-in-class Forecasting capability to drive real-time, data-driven decision-making across user growth, revenue, compute infrastructure, and more. We are developing scalable forecasting infrastructure to help us understand and anticipate business dynamics in an increasingly complex, usage-based world. Our models are foundational to planning, pricing, operational efficiency, and growth strategy - supporting key investment decisions and unlocking OpenAI’s full potential. About the Role We’re looking for a senior Machine Learning Data Scientist to lead our forecasting initiatives. You’ll be one of the founding members of the Forecasting pillar within Strategic Finance Data Science, responsible for building and scaling robust, interpretable, and production-ready forecasting systems. Your models will power critical business decisions by predicting core metrics such as DAU/WAU, revenue, LTV, compute consumption, and profitability. This is a highly cross-functional role, requiring technical excellence, strong product intuition, and business acumen. You’ll collaborate with product managers, researchers, engineers, and finance leaders to operationalize forecasting insights, influence company-wide strategy, and build foundational forecasting capabilities at OpenAI. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Build statistical and machine learning models to solve forecasting needs across product, finance, infrastructure, and GTM domains. Own the end-to-end modeling lifecycle , including scoping, feature engineerin