Production Supervisor Jobs

Fin , now part of Salesforce, is 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, giving modern support teams one single system. Together with Salesforce, the #1 AI CRM, where humans with agents drive customer success, we're building the future of customer experience. Here, ambition meets action. Tech meets trust. And innovation isn't a buzzword, it's a way of life. The world of work as we know it is changing, and we're looking for Trailblazers who are passionate about bettering business and the world through AI. Ready to level up your career at the company leading workforce transformation in the agentic era? You're in the right place. Agentforce is the future of AI, and you are the future of Salesforce. What's the opportunity? We’re looking for Staff Product Engineers to join the AI Group to build Fin's AI-powered products. Product Engineers working in ML work closely with both our ML Scientists and product teams. They must deeply understand our product, our customers, our ML tech stack and our broader product stack. Our group is responsible for defining new ML features, researching appropriate algorithms and technologies, and rapidly getting first prototypes in our customers’ hands. We are an extremely product focussed team. We work in partnership with Product and Design functions of teams we support. Our team's dedicated Engineers enable us to 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 pr

Fin , now part of Salesforce, is 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, giving modern support teams one single system. Together with Salesforce, the #1 AI CRM, where humans with agents drive customer success, we're building the future of customer experience. Here, ambition meets action. Tech meets trust. And innovation isn't a buzzword, it's a way of life. The world of work as we know it is changing, and we're looking for Trailblazers who are passionate about bettering business and the world through AI. Ready to level up your career at the company leading workforce transformation in the agentic era? You're in the right place. Agentforce is the future of AI, and you are the future of Salesforce. What's the opportunity? We’re looking for Staff Product Engineers to join the AI Group to build Fin's AI-powered products. Product Engineers working in ML work closely with both our ML Scientists and product teams. They must deeply understand our product, our customers, our ML tech stack and our broader product stack. Our group is responsible for defining new ML features, researching appropriate algorithms and technologies, and rapidly getting first prototypes in our customers’ hands. We are an extremely product focussed team. We work in partnership with Product and Design functions of teams we support. Our team's dedicated Engineers enable us to 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 pr

Fin , now part of Salesforce, is 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, giving modern support teams one single system. Together with Salesforce, the #1 AI CRM, where humans with agents drive customer success, we're building the future of customer experience. Here, ambition meets action. Tech meets trust. And innovation isn't a buzzword, it's a way of life. The world of work as we know it is changing, and we're looking for Trailblazers who are passionate about bettering business and the world through AI. Ready to level up your career at the company leading workforce transformation in the agentic era? You're in the right place. Agentforce is the future of AI, and you are the future of Salesforce. What's the opportunity? We’re looking for Staff Product Engineers to join the AI Group to build Fin's AI-powered products. Product Engineers working in ML work closely with both our ML Scientists and product teams. They must deeply understand our product, our customers, our ML tech stack and our broader product stack. Our group is responsible for defining new ML features, researching appropriate algorithms and technologies, and rapidly getting first prototypes in our customers’ hands. We are an extremely product focussed team. We work in partnership with Product and Design functions of teams we support. Our team's dedicated Engineers enable us to 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 pr

Staff Embedded SW/FW Engineer (Bringup) Graphcore is a globally recognised leader in Artificial Intelligence computing systems. The company designs advanced semiconductors and data centre hardware that provide the specialised processing power needed to drive AI innovation, while delivering the efficiency required to support its broader adoption. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. We are opening a new AI Engineering Campus in Bengaluru which will play a central role in Graphcore's work building the future of AI computing. Job Summary We have an exciting opportunity to be part of a collaborative, cross-functional development team developing C code used to validate cutting-edge, high-performance AI chips and platforms. You will play a critical role in supporting new product introductions and post-silicon validation. Working within the Post-Silicon Bringup team, you will be involved with bringing first silicon to life, developing code primarily in C to configure and exercise systems and sub-systems on new silicon devices, and working closely with many other teams to help it become a fully characterised and working product, reporting project status/progress to program management on a regular basis. You will have the opportunity to, and be responsible for, leading, mentoring, and providing technical guidance to other engineering team members. In this role, you can leverage your experience and industry knowledge to architect and drive implementation of continuous improvements to test infrastructure and processes. The Team The Post-Silicon Bringup team sits within the Architecture and Validation team, we are responsible for bringup and validation of new silicon when it returns from manufacture, enabling and supporting the production SW and FW teams to bring up their software and supporting the Silicon Characterisation team. Respons

About the Team The Intelligence & Investigations team helps OpenAI understand and respond to the risks that can accompany increasingly capable AI. Our work has two central responsibilities: investigating potential high-severity misuse or harm involving our models, and monitoring and characterizing risks to OpenAI, our users, and the broader world. We bring together analysts, investigators, engineers, and other subject matter experts to turn complex signals into a clearer picture of what matters and support informed action. About the Role As an engineer on Intelligence & Investigations Engineering, you will build the systems that support both sides of this mission: giving OpenAI’s leadership superhuman situational awareness of important risks and developments, and accelerating expert investigators and analysts as they assess potential high-severity misuse or harm. You will design, prototype, ship, and maintain end-to-end products that use OpenAI’s models and infrastructure to make sense of large, complex information environments. These systems will surface meaningful signals, synthesize important developments, and help people make well-informed decisions when the stakes are high. You will work directly with analysts, investigators, and other subject matter experts to understand their needs and build products that make their work faster, more effective, and more scalable. Your engineering work will be central to how the team investigates potential misuse, develops situational awareness, and informs decisions. We’re looking for engineers who combine strong technical and analytical skills with product judgment and the ability to move between rapid prototyping and reliable production systems. You should be comfortable working with ambiguous problems, complex data, and evolving AI capabilities—and excited to build tools that expand what human experts can understand and accomplish. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the

Synthesia is the world’s leading AI video platform for business, used by over 90% of the Fortune 100. Founded in 2017, the company is headquartered in London, with offices and teams across Europe and the US. As AI continues to shape the way we live and work, Synthesia develops products to enhance visual communication and enterprise skill development, helping people work better and stay at the center of successful organizations. Following our recent Series E funding round, where we raised $200 million, our valuation stands at $4 billion. Our total funding exceeds $530 million from premier investors including Accel, NVentures (Nvidia's VC arm), Kleiner Perkins, GV, and Evantic Capital, alongside the founders and operators of Stripe, Datadog, Miro, and Webflow. Welcome to the video first world From your everyday PowerPoint presentations to Hollywood movies, AI will transform the way we create and consume content. Today, people want to watch and listen, not read — both at home and at work. If you’re reading this and nodding, check out our brand video . Despite the clear preference for video, communication and knowledge sharing in the business environment are still dominated by text, largely because high-quality video production remains complex and challenging to scale—until now…. Meet Synthesia We're on a mission to make video easy for everyone. Born in an AI lab, our AI video communications platform simplifies the entire video production process, making it easy for everyone, regardless of skill level, to create, collaborate, and share high-quality videos. Whether it's for delivering essential training to employees and customers or marketing products and services, Synthesia enables large organizations to communicate and share knowledge through video quickly and efficiently. We’re trusted by leading brands such as Heineken, Zoom, Xerox, McDonald’s and more. Read stories from happy customers and what 1,200+ people say on G2 . In 2023, we were one of 7 European companies t

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! Role Overview: Design and implement novel research ideas, ship state of the art models to production, and maintain deep connections to academia and the government. We have one of the highest ratio of compute to engineers in the world. We do not delineate strongly between engineering and research. Everyone will contribute to writing production code and conducting research depending on individual interest and organizational needs. We have all the compute, data, and talent available for you to do your best work. Key Responsibilities: Design, build and scale agentic AI systems for serving mission critical use cases. Research, implement, and experiment with ideas on our supercompute and data infrastructure. Learn from and work with the best researchers in the field. Execute across the full AI stack and ship products to serve public interest. Qualifications: Canadian citizenship and eligibility for security clearance ( required for this role ). Extremely strong software engineering skills. Proficiency in Python and related ML frameworks. Experience training, evaluating, and using (as an end-user) LLMs. Experience using large-scale dis

Why RoboForce RoboForce is an AI robotics company developing Physical AI–powered Robo-Labor for dull, dirty, and dangerous work. The company's robots are engineered for demanding industrial environments, with a focus on real-world deployment and scalability. We are looking for a Senior / Staff AI Research Scientist, Foundation Models to advance robotic embodied intelligence. In this role, you will develop algorithms that enable robots to understand their environment, interpret and execute tasks, and communicate seamlessly with humans — with a particular focus on building and training world models that allow robots to predict, plan, and generalize across complex physical tasks. Responsibilities Design and deploy vision-language(-action) models (VLM/VLA) for contextual understanding and generalized robot action policies. Develop and train world models for action-conditioned prediction, long-horizon planning, and environment simulation — enabling robots to reason about the consequences of their actions before execution. Research approaches to improve world model fidelity using multi-modal inputs including vision, language, proprioception, and spatial representations. Develop foundation models with spatial reasoning capabilities to achieve high-precision robotic actions. Integrate multi-modal data sources (vision, language, speech, etc.) to enable natural human-robot communication. Optimize and deploy models as production-grade solutions on RoboForce robotic platforms. Requirements PhD degree in Machine Learning, Robotics, or related field, or Master's degree with 4+ years of relevant experience. Proficiency in Python and deep learning frameworks (e.g., PyTorch, JAX). Expertise in large foundation models (VLM, VLA, etc.). Strong understanding of world model architectures and action-conditioned generative modeling for robot learning. Decent understanding of multimodal models, modern ML architectures (transformers, diffusion models, etc.). Requires 5 d

Role Overview You’re a seasoned Site Reliability Engineer who loves owning complex infrastructure, making things run faster, safer, and with less manual effort. In this Staff‑level role, you’ll design and operate VMware‑based private cloud platforms that power mission‑critical SaaS products used by customers around the world. You’ll work across Linux, Windows Server, networking, storage, and automation frameworks to increase reliability, reduce toil, and modernize a global datacenter environment. You’ll have the scope to set technical direction, build automation at scale, and mentor engineers while staying hands‑on with VMware vSphere, F5/AVI load balancers, and hybrid Active Directory. Here’s a breakdown of what you’ll do (not all of it, just the important stuff) Lead the architecture, deployment, and ongoing optimization of VMware vSphere–based private cloud infrastructure across multiple global datacenters. Design and build automation using PowerShell/PowerCLI, Ansible, Python, and CI/CD tools to streamline provisioning, configuration, and compliance. Administer, harden, and troubleshoot Linux (RHEL/CentOS/Ubuntu) and Windows Server environments that host enterprise and SaaS workloads. Integrate and manage Active Directory for authentication, access control, and service accounts across hybrid on‑prem and cloud environments. Partner with network and security teams to manage firewalls, VPNs, storage, and load balancers (F5 BIG‑IP, AVI/NSX Advanced Load Balancer) for highly available services. Document architectures and runbooks, participate in on‑call and change management, and mentor engineers while influencing long‑term reliability and automation strategy. These are the essentials you’ll need to get an interview 10+ years of experience in systems or infrastructure engineering, including operating large‑scale enterprise or SaaS datacenter environments. Deep hands‑on expertise with VMware vSphere (ESXi, vCenter, DRS, HA, vMotion, distributed switches) in production

Who is Artefact? Artefact is a next-generation strategy and data consulting firm dedicated to transforming organizations through data and AI. We combine the rigor of top-tier strategy consulting with deep expertise in data, digital, and analytics to help clients achieve tangible business impact. With 1,800+ consultants, data scientists, and engineers across 23 countries, we work with global leaders such as Samsung, L’Oréal, Orange, and Sanofi. Our Romandie office (Geneva/Lausanne) is at the heart of Artefact’s growth, advising clients on their most pressing strategic challenges — from AI strategy and governance to digital transformation roadmaps and new business model design. Main Responsibilities As a Senior Technical Consultant / Senior AI Engineer , you will lead the design and delivery of impactful AI and data solutions. You’ll combine hands-on engineering with client advisory, guiding multi-disciplinary teams from opportunity framing to production deployment. Own solution architecture & delivery: Define end-to-end architectures (data, ML/LLM, APIs, security), make build/buy decisions, and drive projects from PoC to production with reliability, observability, and cost in mind. Lead complex PoCs & pilots: Scope, prototype, and validate AI/ML use cases (incl. LLMs/GenAI, RAG, fine-tuning, evaluation) and convert successful pilots into scalable products. Advanced programming & modeling: Build, adapt, and evaluate ML/DL/LLM models using Python (PyTorch, TensorFlow, HuggingFace, LangChain/LlamaIndex), including prompt engineering, fine-tuning/LoRA, vector search, and safety/guardrails. Cloud & MLOps/LLMOps: Design and operate solutions on Azure, GCP, or AWS (CI/CD, containers, model serving, feature stores, vector DBs, monitoring, eval pipelines). Client advisory & stakeholder management: Translate business goals into technical roadmaps, present to senior stakeholders, manage risks and trade-offs, and ensure measurable business impact. Quality, se

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! Role Overview: Large Language Models (LLMs) continue to push the boundaries of what AI systems can do — but inference is still the bottleneck. The Model Efficiency team is responsible for pushing the limits of LLM inference efficiency across our foundation models. We explore and ship breakthroughs across the model execution stack, including: model architecture and MoE routing optimization decoding and inference-time algorithm improvements software/hardware co-design for GPU acceleration performance optimization without compromising model quality 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. Key Responsibilities: As a Staff Research Engineer, you will develop, prototype, and deploy techniques that materially improve how fast and efficiently our models run in production.

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! Role Overview: Our team is a fast-growing group of researchers and engineers focused on building reliable ML systems and pushing the boundaries of LLM inference efficiency. We develop techniques that improve how models execute in production, driving lower latency, higher throughput, and consistent quality across diverse workloads. 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. Job Responsibilities: As an engineer on this team, you’ll work across the inference stack to improve core performance metrics by diving deep into model execution, identifying bottlenecks, and developing innovative optimizations. You’ll collaborate closely with modeling and systems teams to experiment, measure, and ship improvements that meaningfully accelerate inference. As the team evolves, you’ll

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role: When you see what modern language models are capable of, do you wonder, "How do these things work? How can we trust them?" The Interpretability team at Anthropic is working to reverse-engineer how trained models work because we believe that a mechanistic understanding is the most robust way to make advanced systems safe. Think of us as doing "neuroscience" of neural networks using "microscopes" we build - or reverse-engineering neural networks like binary programs. More resources to learn about our work: Our research blog - covering advances including Monosemantic Features and Circuits An Introduction to Interpretability from our research lead, Chris Olah The Urgency of Interpretability from CEO Dario Amodei Engineering Challenges Scaling Interpretability - directly relevant to this role 60 Minutes segment - Around 8:07, see a demo of tooling our team built New Yorker article - what it's like to work on one of AI's hardest open problems Even if you haven’t worked on interpretability before, the infrastructure expertise is similar to what's needed across the lifecycle of a production language model: Pretraining: Training dictionary learning models looks a lot like model pretraining - creating stable, performant training jobs for massively parameterized models across thousands of chips Inference: Interp runs a customized inference stack. Day-to-day analysis requires services that allow editing a model's internal activations mid-forward-pass - for example, adding a "steering vector" Performance: Like all LLM work, we push up against the limits of hardware and software. Rather than squeezing the last 0.1%, we are foc

DataHub is an AI & Data Context Platform adopted by over 3,000 enterprises, including Apple, CVS Health, Netflix, and Visa. Innovated jointly with a thriving open-source community of 13,000+ members, DataHub's metadata graph provides in-depth context of AI and data assets with best-in-class scalability and extensibility. The company's enterprise SaaS offering, DataHub Cloud, delivers a fully managed solution with AI-powered discovery, observability, and governance capabilities. Organizations rely on DataHub solutions to accelerate time-to-value from their data investments, ensure AI system reliability, and implement unified governance, enabling AI & data to work together and bring order to data chaos. The Challenge As AI and data products become business-critical, enterprises face a metadata crisis: No unified way to track the complex data supply chain feeding AI systems Engineering teams struggling with data discovery, lineage, and governance Organizations needing machine-scale metadata management, not just human-browsable catalogs Why This Matters This is where infrastructure meets impact. The metadata layer you'll build will directly power the next generation of AI systems at massive scale. Your code will determine how safely and effectively thousands of organizations deploy AI, affecting millions of users worldwide. The Role We're looking for an exceptional Staff, Backend engineer to lead development of DataHub's Platform framework – the core that connects diverse data systems and powers our metadata collection capabilities. You'll Build Scalable, fault-tolerant ingestion systems for enterprise-scale metadata Clean, intuitive APIs for our connector ecosystem Event-driven architectures for real-time metadata processing Schema mapping between diverse systems and DataHub's unified model Versioning systems for AI assets (training data, model weights, embeddings) You Have 8+ years building production-grade distributed systems Advanced Python and API design ex

About Appier Appier is an AI-native Agentic AI as a Service (AaaS) company that uses artificial intelligence (AI) to power business decision-making. Founded in 2012 with a vision of democratizing AI, Appier’s mission is turning AI into ROI by making software intelligent. Appier now has 17 offices across APAC, Europe and U.S., and is listed on the Tokyo Stock Exchange (Ticker number: 4180). Visit www.appier.com for more information. About the role Software engineers (Ad Cloud Bidding) at Appier Tokyo office build a wide range of platforms and services that interconnect data and AI with our customers and users. As a Staff Software Engineer , you will play a critical role in designing and building scalable and performant backend architecture, owning and driving the technical roadmap for sizable projects or services. You will also take responsibility for service operations – ensuring reliability, availability, and efficient deployment of large-scale distributed systems. Responsibilities Engage in the design of large-scale backend systems and distributed services Contribute to technical roadmap and planning Collaborate with cross-functional teams to deliver robust and high-performance systems Troubleshoot production issues and contribute to root cause analysis Ensure high reliability through best practices in service operation, monitoring, and deployment Participate in on-call rotations and lead incident response when required About You [Minimum qualifications] 8+ years of experience in software development Proficient in modern C++ programming (C++11 and later) Familiar with Unix/Linux environments Solid understanding of system programming Experience in developing low-latency (millisecond-scale) and high-throughput (>1K QPS per machine) systems Experience in service optimization and performance tuning Strong sense of ownership and good problem-solving skills [Preferred qualifications] Experience in modern build systems Experience in operation automation tools Ex