Machine Operator Integrator Jobs

At Affirm, we exist for the moments that matter—giving people a clear, predictable way to pay over time, with no hidden fees, no surprises, and no tradeoffs on what matters most. About Enterprise Risk & Internal Audit The Enterprise Risk & Internal Audit department protects Affirm’s operations and long-term success. We identify, assess, and monitor risk across the business. Our work includes internal audits, regulatory assurance, fraud prevention, and crisis planning. The team maintains strong controls, tracks key risk indicators, and ensures readiness for external reviews. We uphold accountability, transparency, and resilience to support responsible growth. About the Team We're looking for a sharp, driven quantitative professional to join our dynamic Model Risk Management (MRM) team. In this role, you will oversee the underwriting and credit risk validation sector - the most critical pillar of Affirm’s MRM framework. This is a unique position designed for a seasoned technical leader who can build, mentor, and manage a high-performing team while remaining deeply hands-on, personally executing validations of our most complex machine learning models. You'll collaborate across the company to shape a best-in-class risk framework, ensuring our models are robust, reliable, and ready for the future. If you're passionate about the intersection of finance, credit risk, and data science, this role is for you. What You'll Do: Sector Leadership & Team Management: Oversee the underwriting and credit risk validation sector. Lead, mentor, and manage a team of talented quantitative professionals while setting the strategic direction for this critical risk domain. Hands-On Model Validation: Execute rigorous, independent validations of sophisticated machine learning models across underwriting and credit risk management. Technical Review: Evaluate conceptual soundness, data integrity, and performance stability through comprehensive testing, in-depth reviews, and continuous

At Affirm, we exist for the moments that matter—giving people a clear, predictable way to pay over time, with no hidden fees, no surprises, and no tradeoffs on what matters most. About Enterprise Risk & Internal Audit The Enterprise Risk & Internal Audit department protects Affirm’s operations and long-term success. We identify, assess, and monitor risk across the business. Our work includes internal audits, regulatory assurance, fraud prevention, and crisis planning. The team maintains strong controls, tracks key risk indicators, and ensures readiness for external reviews. We uphold accountability, transparency, and resilience to support responsible growth. About the Team We're looking for a sharp, driven quantitative professional to join our dynamic Model Risk Management (MRM) team. In this role, you will oversee the underwriting and credit risk validation sector - the most critical pillar of Affirm’s MRM framework. This is a unique position designed for a seasoned technical leader who can build, mentor, and manage a high-performing team while remaining deeply hands-on, personally executing validations of our most complex machine learning models. You'll collaborate across the company to shape a best-in-class risk framework, ensuring our models are robust, reliable, and ready for the future. If you're passionate about the intersection of finance, credit risk, and data science, this role is for you. What You'll Do: Sector Leadership & Team Management: Oversee the underwriting and credit risk validation sector. Lead, mentor, and manage a team of talented quantitative professionals while setting the strategic direction for this critical risk domain. Hands-On Model Validation: Execute rigorous, independent validations of sophisticated machine learning models across underwriting and credit risk management. Technical Review: Evaluate conceptual soundness, data integrity, and performance stability through comprehensive testing, in-depth reviews, and continuous

Reolink , a leader in intelligent visual technology for homes and businesses, was founded in 2009 by a group of engineers with a strong commitment to and passion for smarter security solutions. Our products are now trusted by millions of users across more than 110 countries and regions worldwide. Building on this trust, we continue expanding our presence and bringing our innovations to more markets around the globe. Reolink remains committed to delivering advanced, reliable, and user‑centric solutions that empower people to protect what matters most. AI Algorithms Engineer (PHD / Master Degree Only) 5 Work Days Per Week Office Near to Kaki Bukit MRT, Singapore Relocate Near Tai Seng MRT in August / September 2026 Medical Benefits Provided Entitled to Yearly Bonus & Performance Bonus Job Requirements: PHD / Master Holder in Computer Science, Applied Mathematics, Electrical Engineering, Pattern Recognition, Artificial Intelligence, Automatic Control, Operations Research, Biology, Physics / Quantum Computing, Neuroscience, Statistics or a related field. Familiar with common machine learning and deep learning algorithms and keeping track with the latest SOTA implementations . Strong programming skill in Python, C / C++ , proficient in mathematical / statistical concepts and exceptional coding skills Hands-on experience with AI / ML frameworks be familiar such as Caffe, PyTorch, TensorFlow, MxNet etc. Have rich project experience in machine learning and deep learning , be familiar with common algorithm models, such as CNN, RNN, LSTM, Transformer, ViT, etc., and be able to improve and innovate models according to actual problems. Experience in familiar the design, parameter tuning and optimization methods of neural network models is a plus Experience in model compression and in the transplantation and op

The Prediction & Behavior ML team is responsible for developing machine learning (ML) algorithms that learn and predict behaviors from data, applying them both on-vehicle to influence driving behavior and off-vehicle to provide ML capabilities to simulation and validation. Given the tight integration of behavior forecasting and motion planning, our team collaborates closely with the Planner team to advance overall vehicle behavior. We also work closely with our Perception, Simulation, and Systems Engineering teams to accelerate our ability to validate our driving performance. As a Learned Trajectory Machine Learning Engineer you will be responsible for developing deep learned models that produce trajectories for our vehicles to drive. Given the tight integration of behavior prediction and motion planning, you will closely collaborate with the Planner and Perception teams in the advancement of our overall vehicle behavior. In this role, you will: You will develop new deep learning models that use imitation learning and reinforcement learning to generate driving plans for our autonomous vehicle. You will also work on techniques to estimate the quality of those driving plans along the dimensions of safety, progress, comfort etc. You will leverage our large-scale machine learning infrastructure to discover new solutions and push the boundaries of the field You will develop metrics and tools to analyze errors and understand improvements of our systems You will collaborate with engineers on Perception, Planning, and Simulation to solve the overall Autonomous Driving problem in complex urban environments Qualifications BS, MS, or PhD degree in computer science or related field Experience with training and deploying transformer-based model architectures and reinforcement learning Experience with production Machine Learning pipelines: dataset creation, training frameworks, metrics pipelines Fluency in Pyt

About the Team DoorDash is building the world's most reliable on-demand, logistics engine for delivery. We are continuing to grow rapidly and expanding our Engineering offices globally! We are looking for Software Engineers, Machine Learning to build and maintain a large scale 24x7 global infrastructure system that powers DoorDash's 3-sided marketplace of Consumers, Merchants and Dashers. About the Role As a Software Engineer, Machine Learning, you’ll be conceptualizing, designing, implementing, and validating algorithmic improvements to the catalog system and our product knowledge graph at the heart of our fast-growing grocery and retail delivery business. You will use our robust data and machine learning infrastructure to implement new ML solutions to make our product knowledge graph accurate, standardized, semantically rich, easily discoverable, and extensible. We’re looking for someone with a command of production-level machine learning and experience with solving end-user problems who enjoys collaborating with multi-disciplinary teams. This role is hybrid with some in-office time expected and will report to an Engineering Manager. You're excited about this opportunity because you will... Develop advanced machine learning models to improve ads efficiency and quality. Design and build optimization algorithms for budget pacing and automated bidding to achieve various advertising goals. Establish a data-driven framework to understand how the bid density and market competitiveness would affect advertising value and platform revenue. Develop new data solutions (eg. embeddings and consumer profiles) to target the relevant audience. Be responsible for the end-to-end ML lifecycle, including ideation, offline model training, online shadowing/deployment, experimentation, and post-launch monitoring/measurement. Build and extend the current data/ML infrastructure to empower Ads data applications including data analysis, ML modeling, and experimentati

About the Role As a Senior Software Engineer, Machine Learning, you’ll be conceptualizing, designing, implementing, and validating algorithmic improvements to the catalog system and our product knowledge graph at the heart of our fast-growing grocery and retail delivery business. You will use our robust data and machine learning infrastructure to implement new ML solutions to make our product knowledge graph accurate, standardized, semantically rich, easily discoverable, and extensible. We’re looking for someone with a command of production-level machine learning and experience with solving end-user problems who enjoys collaborating with multi-disciplinary teams. We expect Senior Engineers to be able to own projects end-to-end and mentor their junior and mid level peers. This role is hybrid with some in-office time expected and will report to an Engineering Manager. You're excited about this opportunity because you will... Develop advanced machine learning models to improve core parts of your teams scope. Be responsible for the end-to-end ML lifecycle, including ideation, offline model training, online shadowing/deployment, experimentation, and post-launch monitoring/measurement. Work on creating novel ML & AI solutions that push both our business and the industry forward. Scale our systems and services to fuel the growth of our business. Completely disrupt logistics by tackling bleeding-edge, technical problems We're excited about you because you have... M.S., or PhD. in a technical field such as computer science, mathematics, statistics, physics or equivalent. 5+ years ML industry experience with a solid understanding of machine learning algorithms and fundamentals. Proficiency in using AI coding tools (e.g., Claude Code, Codex, Cursor) in the full software development lifecycle, including designing, generating code, testing, monitoring and releasing software Experience building data/feature engineering pipelines at scale using Pyspark and Snowflak

About the Team DoorDash’s GenAI Platform team sits within Machine Learning Platform and builds the shared infrastructure that helps DoorDash, Wolt, and Deliveroo teams safely bring GenAI-powered products, agents, automation, and personalization to production. Our mission is to increase the velocity of business impact from GenAI. A central pillar of that work is running frontier open-weight LLMs and VLMs (such as GLM, Qwen, Kimi, and DeepSeek) ourselves — real-time GPU serving, high-throughput batch inference, and fine-tuning on autoscaling GPUs — delivering large cost and latency wins (for example, a billion embeddings produced roughly 20× cheaper and visual models served roughly 72% cheaper). We also own core platform surfaces including the LLM Gateway, Agent Gateway, evals infrastructure, guardrails, and cost attribution. About the Role You will join a small, high-leverage team building production infrastructure for Generative AI at DoorDash, with a primary focus on our open-weights model platform spanning inference and fine-tuning: real-time GPU serving, high-throughput batch inference, and model fine-tuning. You’ll work across model serving and inference engines, fine-tuning and training pipelines, GPU autoscaling and utilization, batch pipelines, backend services, and observability. This role is ideal for an engineer who enjoys pushing the cost/performance frontier of GPU inference and fine-tuning in a fast-moving technical area where product needs, model capabilities, vendor ecosystems, and cost/performance tradeoffs are evolving quickly. You’re excited about this opportunity because you will… Build the infrastructure that helps DoorDash teams move GenAI ideas from prototype to production, increasing the velocity of business impact from AI across the company. Work on our open-weights serving stack — real-time GPU endpoints, high-throughput batch inference, and fine-tuning (SFT/DPO/LoRA) — alongside the LLM Gateway, Agent Gateway, evals infrastructure, guardrai

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 our next Principal Machine Learning Engineer in Twilio’s Customer Memory Team. About the job In this role, you will build the foundational AI/ML capabilities that power intelligent engagement experiences for Twilio customers - letting any application, human or AI agent, or channel know who a customer is, what they have done, and how best to reach them. This role requires a builder and curious mindset, someone who can bridge the gap across theoretical research, production-grade experimentation and enterprise quality software. You will lead rapid research cycles to solve complex problems regarding contextual intelligence and large scale ML problems ensuring every interaction feels seamless and personalized. Responsibilities In this role, you’ll: Build out new functionality within a fast moving product seeing rapid adoption. Take a nebulous idea, design a rigorous experiment, and execute it within weeks. Conduct deep-dive research

About the Role Chime’s Data Science and Machine Learning team is building models, services, and platforms that transform how millions of users manage and grow their financial lives. We are looking for a hands-on Tech Lead Manager with deep technical expertise in machine learning and data science, particularly within the Growth and Marketing domain. Beyond technical proficiency, we value creativity, user empathy, and strong collaboration. As a Tech Lead Manager within our Growth and Marketing team, you will lead a talented group of data scientists and machine learning engineers to develop innovative growth and marketing models. These models will provide critical insights into acquiring, retaining and growing Chime members, broaden access to credit, and ensure financial inclusivity. You will play a pivotal role in creating innovative, ground-up products while driving the development of cutting-edge acquisition and retention models and solutions. If you are passionate about marketing, growth, customer acquisition and retention models, this role could be a great fit for you. In this role, you can expect to Lead and inspire a high-performing team of data scientists and ML engineers, ensuring the successful development and deployment of machine learning solutions for customer acquisition, conversion and retention. Drive strategic direction for ML initiatives in marketing, engagement, and growth by identifying opportunities where AI/ML can optimize our customer funnel. Oversee the end-to-end development of machine learning models such as lifetime value prediction, churn risk modeling, customer segmentation, marketing attribution, referral recommendations, and personalized communications. Collaborate cross-functionally with marketing, product, growth, and engineering teams to align machine learning initiatives with business objectives. Leverage transactional and behavioral data to enhance customer targeting, optimize acquisition spend, and improve retention strategies. Esta

At Gilead, we’re creating a healthier world for all people. For more than 35 years, we’ve tackled diseases such as HIV, viral hepatitis, COVID-19 and cancer – working relentlessly to develop therapies that help improve lives and to ensure access to these therapies across the globe. We continue to fight against the world’s biggest health challenges, and our mission requires collaboration, determination and a relentless drive to make a difference. Every member of Gilead’s team plays a critical role in the discovery and development of life-changing scientific innovations. Our employees are our greatest asset as we work to achieve our bold ambitions, and we’re looking for the next wave of passionate and ambitious people ready to make a direct impact. We believe every employee deserves a great leader. People Leaders are the cornerstone to the employee experience at Gilead and Kite. As a people leader now or in the future, you are the key driver in evolving our culture and creating an environment where every employee feels included, developed and empowered to fulfil their aspirations. Join Gilead and help create possible, together. Job Description This Data Platform Engineer will have the unique opportunity to apply cutting-edge data and analytics technologies to one of the most meaningful challenges in healthcare: ensuring the quality of medicines that improve and save lives. As a pivotal member of R&D Quality, this role will help transform how quality insights are generated, scaled, and acted upon across Gilead's drug development and clinical research programs. Through the development of robust data pipelines and advanced analytics platforms, the successful candidate will enable more proactive quality oversight, smarter decision-making, and continuous improvement, ultimately supporting Gilead's mission to deliver life-changing t

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. With over half a billion rides and counting, Lyft is solving hard problems in a flourishing domain with a lot of data and creative solutions in Marketplace, Mapping, Fraud, Growth and beyond. We're actively building the next-generation Machine Learning (ML) platform for low-cost, ultra-immersive transportation to improve people’s lives using modern ML with peta-byte scale data. Our Machine Learning Engineers are excited to work on these challenging problems and redefine solutions to directly impact various aspects of Lyft's primary business. If you are a student with experience in machine learning workflows, passionate about solving challenging problems using data and working in a dynamic, creative, and collaborative environment, this opportunity is for you! Responsibilities: Contribute to the design, build, train and test of Machine Learning models Write production-level code to convert ML models into working pipelines Partner with Product Managers, Data Scientists, and fellow ML Engineers to frame Machine Learning problems within the business context Analyze experimental and observational data, communicate findings to support decisions Participate in code and spec reviews to ensure code quality and distribute knowledge Experience: Currently pursuing a Bachelor's, Master's, or PhD degree in Computer Science or a related technical field from a university in Canada (required) , with a graduation date between December 2027 and Summer 2028 (required). For any candidates who are master's students who worked between their bachelor's and master's programs: candidates should also have less than 2 years of relevant full-time work experience Available during Summer 2027 for the internship in Toronto Good understanding and knowledge of ML libraries like scikit-learn, Tensorflow, PyTorch, Keras, MXNet, et

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. With over half a billion rides and counting, Lyft is solving hard problems in a flourishing domain with a lot of data and creative solutions in Marketplace, Mapping, Fraud, Growth and beyond. We're actively building the next-generation Machine Learning (ML) platform for low-cost, ultra-immersive transportation to improve people’s lives using modern ML with peta-byte scale data. Our Machine Learning Engineers are excited to work on these challenging problems and redefine solutions to directly impact various aspects of Lyft's primary business. If you are a student with experience in machine learning workflows, passionate about solving challenging problems using data and working in a dynamic, creative, and collaborative environment, this opportunity is for you! Responsibilities: Contribute to the design, build, train and test of Machine Learning models Write production-level code to convert ML models into working pipelines Partner with Product Managers, Data Scientists, and fellow ML Engineers to frame Machine Learning problems within the business context Analyze experimental and observational data, communicate findings to support decisions Participate in code and spec reviews to ensure code quality and distribute knowledge Experience: Currently pursuing a Bachelor's, Master's, or PhD degree in Computer Science or a related technical field from a university in Canada (required) , with a graduation date between December 2027 and Summer 2028 (required). For any candidates who are master's students who worked between their bachelor's and master's programs: candidates should also have less than 2 years of relevant full-time work experience Available during Summer 2027 for the internship in Toronto Good understanding and knowledge of ML libraries like scikit-learn, Tensorflow, PyTorch, Keras, MXNet, et

About the role Chime’s Machine Learning Platform (MLP) team builds and operates the infrastructure, tooling, and developer experience that powers machine learning across the company. We enable data scientists and ML engineers to develop, train, deploy, and monitor models reliably and efficiently. As a Senior Software Engineer on the Machine Learning Platform team, you will design and build scalable systems spanning traditional machine learning and emerging AI workloads, including model training, feature computation, real-time inference, foundation-model access, evaluation, and agentic orchestration. You’ll work at the intersection of distributed systems, cloud infrastructure, applied machine learning, and AI product engineering. This role focuses on creating secure, reliable, and reusable platform capabilities that help teams choose the right approach, from conventional predictive models to LLM-powered and multi-step agentic systems, while maintaining strong standards for evaluation, observability, governance, privacy, and cost efficiency. In this role, you can expect to Design, build, and operate scalable ML and AI infrastructure on AWS. Design and operate shared platform capabilities for LLM and agentic workloads, including model access, prompt and configuration lifecycle, retrieval, tool integration, state management, and workflow orchestration. Build evaluation frameworks for non-deterministic AI systems, including offline benchmarks, regression testing, online quality signals, human feedback, and failure analysis. Establish observability, reliability, and governance for models and agents, covering traces, model and prompt versions, tool calls, latency, token usage, quality, safety, privacy, and cost. Help teams make principled architecture decisions across traditional ML, LLM-powered applications, and agentic workflows, and contribute to the platform’s technical roadmap. Build distributed training, batch inference, and large-scale processing systems using

Who We Are Nuro believes self-driving vehicles are the most immediate and profound opportunity for AI to drive positive change in the physical world. Safer streets, more time for what matters, and easier access to the world around us, that’s why we’re building a universal autonomy platform: self-driving for all roads and all rides. Founded in 2016, Nuro is a physical AI company developing Level 4 autonomous driving technology for a wide range of vehicles, use cases, and markets. Powered by the Nuro Driver™, our universal autonomy platform enables the global mobility ecosystem to deploy autonomy at scale, from robotaxis and logistics fleets to personal vehicles. With years of real-world deployment experience and a flexible, partner-led business model, Nuro is working toward a future where millions of autonomous vehicles powered by our technology help make everyday life safer, easier, and more connected. Nuro has raised over $2B in capital from Uber, NVIDIA, Google, Softbank, Fidelity, T. Rowe Price, and other leading investors. About the Team Our robotics team is growing and we are looking for an ML Software Engineer to join our Online Mapping team. We are searching for an engineer with robotics and machine learning expertise to work on challenging problems in the design and implementation of onboard mapping models and algorithms, data and label management, as well as training pipelines. About the Role Building robust ML and/or mapping systems that work with real data (cameras, LiDAR, etc.) in uncertain environments, and a strong desire to contribute to the future of robot navigation for logistics and transportation. About the Work Research, develop, and implement state-of-the-art online mapping models and algorithms. Analyze and characterize the performance of the online mapping system, identifying opportunities for architecture, data or evaluation improvements in a E2E ML system. Work cross functionally with other ML teams to integrate our models

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators. At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators. At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for e