Production Associate Jobs

About the Team OpenAI’s Legal team plays a crucial role in advancing our mission by tackling innovative and fundamental legal issues in AI. The team includes professionals from diverse legal fields—technology, AI, infrastructure, privacy, IP, corporate, employment, tax, regulatory, and litigation—who collaborate closely with colleagues across the company. If you are passionate about being a technology lawyer working on cutting-edge challenges, you’ll thrive here. About the Role We are seeking an experienced attorney to serve as the commercial legal lead for Marketing. Based in San Francisco, you will be a primary legal partner to OpenAI’s rapidly growing global Marketing organization, supporting high-impact campaigns, creative production, talent and creator relationships, sponsorships, events, and the agreements and rights that make that work possible. You will work closely with Marketing, Communications, Partnerships, Procurement, Finance, Product, and colleagues across Legal, including Product, Privacy, Regulatory, and IP/Brand, to deliver practical advice at the pace of the business. This is a unique opportunity to help shape OpenAI’s Marketing efforts, negotiate sophisticated transactions, and build scalable legal frameworks for responsible global growth. We operate on a hybrid work model of three days per week in the office and offer relocation support for new employees. In this role, you will: Serve as the commercial legal lead for Marketing, partnering closely with Brand, Creative, Product Marketing, Design, Film and Photo, Performance Marketing, Partner Marketing, Communications, and regional teams from concept through launch. Draft and negotiate a wide range of marketing and entertainment agreements, including agency, production, talent and creator, sponsorship, event, media, content-licensing, marketing-technology, and vendor agreements. Structure and clear the rights needed for campaigns and content, including talent and appearance releases, publicity and

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. Engineering Manager, Cloud Efficiency Snowflake runs large scale cloud infrastructure to deliver its own service — production and internal deployments, Kubernetes fleets, CI/CD, etc. Our cloud spend is in billions of dollars per year. We are looking for an experienced Engineering Manager to lead the Cloud Efficiency engineering team. In this role, you will own the technical vision and execution for building a unified, self-serve cloud efficiency platform along with AI skills and agents that makes resource usage and spend attributable and governable while driving insights and optimization of our cloud spend. AS AN ENGINEERING MANAGER IN CLOUD EFFICIENCY, YOU WILL: Lead and grow our talented team of software engineers, fostering a culture of technical excellence, ownership, and continuous learning. Drive the roadmap for Cloud Efficiency — translating company-level spend objectives into engineering systems: authoritative cost data, resource ownership registry, attribution pipelines, cost and unit economics modeling, observability, governance policies, and optimization workflows — in partnership with Product, Engineering, Finance, and Data Science. Set technical strategy for backend systems, data pipelines, and APIs that measure, attribute and surface cost and usage insights at

About the Role: We're hiring Senior and Staff Data Platform Engineers to join the Data Infrastructure teams in Toronto. Together these teams own the infrastructure that processes billions of events per day: Spark-on-Kubernetes, Flink and Kinesis pipelines, a multi-petabyte Delta Lake, a large-scale MemoryDB feature store, Databricks multi-environment operations, and the catalog and lifecycle systems that govern it. The team is small and senior. Each engineer owns major platform components: you design it, build it, and support it in production. This is a hybrid-role based out of our Toronto office. You must be willing to travel to our Toronto office two days/week. What You'll Do: Spark-on-Kubernetes — EKS-based compute platform for Spark workloads: cluster configuration, Pod Identity IAM, job environment setup, Kustomize overlays, and shadow canary validation Event ingestion — Rust services and Flink jobs processing billions of events per day over Kinesis; throughput, reliability, on-call response, and AI-assisted operational tooling to reduce toil Platform infrastructure — Terraform modules for environment provisioning, cross-account AWS IAM, ARC runner infrastructure, and CI/CD for data platform changes Feature store and ML compute — Flink-based real-time feature pipelines feeding a large-scale MemoryDB cluster; GPU capacity governance and Databricks multi-environment operations for ML training workloads Workflow orchestration and CDC — Airflow-based DAG deployment, change data capture pipeline operations, and data quality monitoring Your Background: 3+ years building and operating production data platform infrastructure at the cluster or platform level, across Spark, Flink, Kinesis, Kubernetes, or equivalent Deep experience in at least one of: Spark-on-K8s cluster operations, Rust-based data or systems engineering, Kubernetes platform engineering and IaC, or data catalog and governance tooling Production AWS experience or equivalent: EKS, S3, Kinesis, and mu

We're looking for an ML Data & Platform Engineer to own the infrastructure that powers our speech AI models: the pipelines that source and prepare training data, and the platform that trains, evaluates, and serves them in production. Speech AI has a data problem most ML teams don't, and you'll be at the centre of solving it, working as part of our ML team to remove friction across the entire lifecycle and get better models into production faster. This is a broad, cross-functional role suited to someone who enjoys working across the full stack: data infrastructure, distributed systems, and production ML, and who takes ownership of problems end to end rather than waiting to be told what to fix. What you'll do Designing, building, and maintaining scalable data pipelines for ingesting, transforming, validating, and storing large datasets used to train our models Developing and maintaining web scraping and data acquisition solutions to keep training datasets fresh, high-quality, and available at scale Building and operating the infrastructure that lets the ML team deploy and evaluate new models quickly, and that serves models efficiently and reliably in production Optimising infrastructure for both iteration speed and production reliability, including GPU utilisation, job scheduling, and training efficiency Implementing observability (monitoring, logging, alerting) across data pipelines and ML systems to catch issues early and keep things running smoothly Troubleshooting complex issues across distributed systems, spanning data infrastructure, training, and inference Continuously improving our data and MLOps practices, and helping shape the roadmap for how our platform evolves as we scale What you'll need Strong proficiency in Python and SQL, with a solid backend or data engineering foundation Hands-on experience with containerisation and orchestration (Docker, Kubernetes), and working with a major cloud provider Experience building data pipelines and ETL/ELT processe

Senior Container Security Engineer – CVE Remediation & Image Hardening About the Role We are looking for a hands-on Senior Container Security Engineer to lead vulnerability remediation and image hardening across Linux-based container environments. This role focuses on deep operating system and container security engineering rather than simple vulnerability scanning. You will analyze, remediate, rebuild, harden, and continuously optimize container images used in modern cloud-native platforms. You will work closely with platform engineering, DevOps, infrastructure, and security teams to build automated remediation pipelines, reduce the attack surface, and deliver production-ready hardened images. What You’ll Do - Own end-to-end CVE remediation across Linux-based container images. - Analyze vulnerabilities across OS packages, libraries, runtimes, and dependencies. - Patch, rebuild, validate, and maintain hardened container images at scale. - Reduce attack surface by removing unnecessary packages, binaries, services, and dependencies. - Build and scale automated remediation pipelines for continuous image patching. - Improve image security posture while minimizing operational disruption. - Generate, validate, and maintain SBOMs to support supply chain visibility and compliance. - Integrate remediation workflows into CI/CD and GitOps pipelines. - Optimize image size, startup performance, and operational efficiency. - Research emerging Linux, container, Kubernetes, and software supply chain threats. - Troubleshoot complex dependency, package compatibility, and runtime security issues. - Help define internal standards for hardened images and secure software delivery. What You Bring - 5+ years of experience in Linux systems engineering, platform engineering, DevSecOps, security engineering, or SRE. - Deep understanding of Linux distributions (Debian, Ubuntu, Alpine, RHEL). - Strong hands-on experience with Docker, Kubernetes, and

SpaceXAI’s mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity. We operate with a flat organizational structure. All employees are expected to be hands-on and to contribute directly to the company’s mission. Leadership is given to those who show initiative and consistently deliver excellence. Work ethic and strong prioritization skills are important. All employees are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates. ABOUT THE ROLE: As an ideal candidate you have a good understanding of how highly scalable and reliable production infrastructure is built. Most of our backend infrastructure is written in Rust. So familiarity with a compiled language such as C++, Rust, or Go is highly beneficial. RESPONSIBILITIES: Build the SpaceXAI API that serves our models to developers worldwide Own the end-to-end system responsible for high-throughput inference, handling billions of tokens per minute with low latency and high availability, including model serving infrastructure, request routing, SDK development, rate limiting, observability, and efficient scaling BASIC QUALIFICATIONS: Expert knowledge of either Rust or C++ Experience in designing, implementing, and maintaining reliable and horizontally scalable distributed systems Knowledge of service observability and reliability best practices Experience in operating commonly used databases such as PostgreSQL, Clickhouse, and MongoDB PREFERRED SKILLS AND EXPERIENCE: Experience with LLM inference engines and serving frameworks (e.g., SGLang, TensorRT, vLLM) Experience designing or building with agent SDKs and agent orchestration frameworks Experience with Docker, Kubernetes, and containerized applicatio

Opportunity ThermalWorks LLC is seeking an experienced Quality Assurance Manager to serve as the technical quality authority and liaison across our customer field sites, European contract manufacturer sites and internal quality control function. This is a cross-functional, high-visibility role that sits at the intersection of manufacturing, field service, and quality leadership. The ideal candidate brings deep hands-on experience with mission-critical mechanical systems — particularly hydronic cooling, chiller platforms, and data center infrastructure — combined with the discipline and communication skills to document findings clearly and present them to leadership. This role is hands-on and will require mechanical knowledge of HVAC systems as well as quality related processes such as 8D problem solving and Six Sigma methodologies. This position is preferably based in Barcelona, but can also be based in Madrid or Bilbao. This role has a travel requirement of 20-40% depending on where based. Key Responsibilities Include but are not limited to: Factory Quality Support new and existing production at ThermalWorks manufacturing operations in Europe to identify quality concerns for first article inspections or before production units ship Review assembly, wiring, piping, and commissioning documentation against engineering specifications and approved submittals Coordinate findings with factory leadership and flag hold conditions requiring resolution prior to release Document inspection outcomes and provide written reports to the Director of Quality Customer Site Quality Perform on-site QA/QC inspections at customer data center locations to verify ThermalWorks equipment installation, commissioning, and service work meets required standards Work with EU Director of Operations when customer issues arise Drive 8D problem solving for technical customer issues and coordinate investigation and corrective actions with TW Engineering and Operations personnel Create cus

About us EVERY™ is a leading VC-backed food tech ingredient company and market leader using precision fermentation to create animal proteins without the animal for the global food and beverage industry. EVERY™ is a team of passionate change-makers who are reimagining the factory farm model with a kinder, more sustainable alternative. Leveraging precision fermentation to produce hyper-functional and one-to-one replacement proteins from microorganisms, EVERY™ is on a mission to decouple the world’s proteins from the animals that make them. We are a passionate, determined (and fun!) team with a vital objective, and we're on the lookout for like-minded people to join our mission. For more information, visit www.every.com The Downstream Process Engineer II will be an integral member of our downstream process development team. You will use experimentation to optimize Every’s production process and then see the results of your changes in action at pilot and commercial-scale biomanufacturing sites. This is an excellent opportunity for someone with laboratory and tech transfer experience, who wants to make an impact at scale. What you'll Accomplish Optimize the Every downstream process via an iterative cycle. Improvements are developed in the laboratory, scaled up to an external pilot plant, and learnings are taken back to the lab for further troubleshooting and improvement. Perform various unit operations at the Every HQ such as TFF, depth filtration, chromatography, spray drying and other purification/separation processes. Develop and review tech transfer documentation to ensure successful scale up trials. Travel to external pilot plants to review the scale up of novel processes. Coordinate with third parties such as pilot scale equipment vendors to arrange internal and external trials. Partner with Every scientists and engineers to bring their bench ideas to pilot scale. Analyze results and report data to enable appropriate interpretation and

**English version below** Doit être local à Montréal Vous souhaitez travailler dans le domaine de la technologie au sein d'une banque d'investissement? Nous recherchons une personne pour rejoindre une équipe dynamique en tant qu’ Ingénieure Fiabilité de Site (Site Reliability Engineer) pour l’un de nos clients. Le Site Reliability Engineering (SRE) est une discipline orientée production, axée sur l’amélioration de la disponibilité des services systèmes, de l’observabilité, de l’évolutivité, de la performance et de la fiabilité des produits technologiques, en appliquant de solides principes d’ingénierie logicielle et en adoptant les technologies et outils les plus récents. Nous serions ravis de vous rencontrer si vous : Vous intéressez aux systèmes distribués et au travail sur des services hautement évolutifs, fiables et à grande échelle. Aimez évoluer dans un environnement dynamique et n’avez pas peur de changer les choses pour les améliorer. Appréciez les nouveaux défis technologiques et la résolution de problèmes complexes. Croyez qu’une équipe qui collabore efficacement est véritablement plus intelligente que la personne la plus brillante qui la compose. Aspirez à évoluer en tant que personne, coéquipier·e et ingénieur·e. Faites preuve de détermination, de motivation et d’un profond sens des responsabilités. À propos de mtrois : Depuis 2010, mtrois aide ses clients à résoudre leurs défis commerciaux et technologiques. Nous sommes une société de conseil en technologie et en affaires avec une main-d'œuvre mondiale qui réalise des projets commerciaux et informatiques significatifs dans certaines des plus grandes organisations de services financiers du monde. Services principaux Consulting et Conseil Services gérés Programme de diplômés Alumni Programme Alumni Pro Nous avons une présence mondiale et sommes experts dans la fourniture d'une qualité exceptionnelle à notre base de clients, offrant des services de conseil dans les domaines du risque, de la réglementa

NK Securities Research is a leading financial firm that leverages cutting-edge technology and sophisticated algorithms to trade the financial markets. Founded in 2011, we have gained invaluable experience in the field of High-Frequency Trading (HFT) across different asset classes. Role Overview We’re looking for engineers who can take AI work beyond experiments and make it hold up in production. You’ll work closely with quant researchers and infra engineers to build AI systems that actually get used improving research speed and internal tooling without slowing down the core stack. We value engineers who think about trade-offs, test what they build, and care about how things run in production. What You’ll Build Production AI Ship models that meet defined latency and reliability expectation Add monitoring, rollback, and guardrails before anything goes live Optimise inference across CPU/GPU environments when it matters Integration into Real Systems Plug AI into data-heavy workflows without hurting performance Work within existing low-latency architecture instead of fighting it Profile and remove bottlenecks rather than guessing AI for Engineers & Researchers Build tools that genuinely speed up research and development Improve code understanding, review workflows, and internal knowledge retrieval Keep systems auditable and predictable LLM & Retrieval Systems Implement structured RAG and embedding pipelines with validation in place Create safe integration layers between models and internal systems Performance & Standards Track latency, drift, and stability — not just accuracy Build observability into everything you ship Help raise the bar for how AI is engineered here What We’re Looking For Strong Python fundamentals Clear thinking around system design and performance trade-offs Experience deploying AI systems in production (1–5 years is typical) Familiarity with transformers, embeddings, or LLM deployment Nice to have: Exposure to C++ / Rust / Go E

What we’re doing isn’t easy, but nothing worth doing ever is. Diligent builds helpful robots that work safely and autonomously in real world environments. We move quickly, solve messy problems, and care deeply about reliability at scale. We’re hiring a Manufacturing Reliability Engineer to own production test for our robots at our contract manufacturer: you’ll design and run robust end-to-end test protocols, provision fleets of robots for production, and own the KPIs that define production quality. This role is based in Austin, TX. However, the position will require 50% travel to the Milwaukee, WI area and requires close collaboration across software, hardware, operations, and product engineering teams. Key Responsibilities End-to-end test process ownership. Create, validate, and maintain production test protocols and gating criteria from incoming inspection through final test and shipment. Provisioning of bots. Design and operate provisioning flows (imaging, firmware deployment, configuration, validation) and the tooling/fixtures needed to provision and handoff robots for production. KPIs and continuous improvement. Own key production metrics — First Pass Yield (FPY), cycle time, and test coverage — and drive continuous improvements to meet throughput and quality targets. Test automation & infrastructure. Architect, implement, and maintain automated test frameworks, harnesses, and test rigs used at the CM site. Ensure tests are stable, fast, and provide actionable failure data. Cross-functional escalation & RCA. Lead root-cause analysis for field and production failures; coordinate corrective actions with design, firmware, and CM engineering to close quality loops. On-site production leadership. Be the onsite technical authority at the contract manufacturer: train operators, debug failures on the line, and continuously refine processes with CM partners. What Success Looks Like Improved FPY and reduced rework rates across production builds. Reduced per

Staff Backend Engineer- Tech Lead |100% Remote | US- SaaS Fintech (Product based firm) Role Responsibilities: Design, develop, and maintain systems on the payments team with primary focus on backend Collaborate with cross-functional teams—product, and design Participate in sprint planning, feasibility assessments, and code reviews Write clean, maintainable, and testable code in Focus on scalability, security, performance, observability, auditability, testability and long-term maintainability Contribute to improving SDLC processes and engineering best practices Troubleshoot production issues and deliver timely resolutions What We're Looking For: 8-12 years of backend engineering experience with a high agency mindset Deep expertise in any of the backend languages (Go or Ruby preferred) Solid grasp of payments domain Proven experience working in Agile/Scrum environments Strong API development skills (RESTful architecture) Excellent problem-solving and communication abilities AI fluent Bonus Points For: (Good to have skills) Experience with payment gateway integrations Familiarity with PCI compliance and secure coding practices Skills in performance optimization (DB, code, etc.) Exposure to GCP or other cloud platforms

Role: Engineering Manager – Communications Location: Remote Team size: 15 engineers (backend + frontend) Type: Full-time About the Role We’re looking for an Engineering Manager who thrives at the crossroads of leadership, hands-on engineering, and solving problems that don’t come with an instruction manual. You’ll lead a team of talented backend and frontend engineers who are building the bridges between systems that power the full customer journey for financial institutions. In this role, you won’t just be overseeing work, you’ll be rolling up your sleeves, writing and reviewing production code, guiding architecture decisions, and coaching engineers to deliver their best work. The systems you’ll help build will connect modern cloud APIs with decades-old banking platforms, bringing reliability and elegance to what often starts as messy complexity. Our integration platform touches everything—from communication stacks to core banking systems, lending and mortgage platforms, payment gateways, and AI Platform. Every integration is an opportunity to shape how our customers experience our products end-to-end. And because we take an AI-augmented approach to software development, you’ll be part of a team that uses AI tools to augment SDLC and write better code, automate testing, and ship faster without compromising quality. What You’ll Be Doing Lead by Example – Stay hands-on with coding, designing architectures and reviewing code while guiding the team toward engineering excellence. Own the Integration Layer – Architect and scale connections across diverse systems, from sleek modern APIs to finicky legacy protocols. Champion the Customer Experience – Partner with Product, Implementation, and customer teams to ensure integrations truly solve real-world challenges. Collaborate Without Boundaries – Work closely with other engineering leaders to ship features that feel seamless across products. Build for the Long Run – Keep systems observable, reliable, and perform

Job Overview: We are looking for a Senior GenAI Developer to design, build, and productionize agentic AI systems—LLM-powered agents that can plan, use tools, orchestrate workflows, and operate reliably under enterprise constraints. You will own key parts of the agent architecture (planning, tool use, memory, evaluation, safety/guardrails, and observability) and deliver end-to-end solutions across RAG, function/tool calling, multi-agent coordination, and scalable deployment. Key Responsibilities Design and implement agentic systems: single-agent and multi-agent architectures (planner/executor, supervisor-worker, routing, reflection, critique, task decomposition). Build robust tool-using agents: function calling, tool schemas, tool authorization, retries, rate limiting, and sandboxing. Implement RAG + memory patterns: retrieval strategies, hybrid search, context assembly, long-term memory, and grounding/citation behaviors. Develop workflow orchestration for agent execution (state machines/graphs), concurrency controls, and deterministic execution where possible. Productionize GenAI services: APIs, background jobs, streaming responses, caching, and cost/latency optimization. Establish agent evaluation: golden sets, simulation-based evals, LLM-as-judge with mitigations, task success metrics, regression testing. Build observability and safety: tracing, token/tool telemetry, anomaly detection, prompt injection defenses, data leakage prevention, policy enforcement. Collaborate with product, security, and platform teams to deliver enterprise-ready solutions and integrate with internal systems (data, identity, workflow). Mentor engineers, set coding standards, and contribute to architecture reviews and technical roadmaps. Required Qualifications 6+ years software engineering experience; 2+ years building LLM/GenAI systems in production. Strong programming skills in Python (required) and/or TypeScript/Node.js. H

Fanatics Commerce is the global leader in licensed sports merchandise, operating a vertically integrated platform that designs, manufactures, and delivers officially licensed apparel, jerseys, headwear, and collectibles for major leagues, teams, and events worldwide. With more than 900 e-commerce sites and a global omnichannel presence across digital, in-venue, and retail, Fanatics Commerce reaches fans in over 180 countries and powers official fan experiences for many of the world's most iconic sports properties. At Fanatics, we bring our BOLD Leadership Principles to life every day - building championship teams, obsessing over fans, acting with entrepreneurial speed, and delivering with a determined and relentless mindset. ROLE OVERVIEW The Graphic Designer Headwear – Mitchell & Ness is a creative, passionate, and driven design professional who applies a strong command of brand identity, color theory, and apparel production techniques to develop seasonal sports apparel assortments for Fanatics Commerce's licensed sports business. Partnering closely with in-house design teams, this role maintains corporate branding and seasonal creative direction that enhances individual league programs through compelling visual storytelling. The Graphic Designer, Licensed Sports Apparel delivers business and fan impact through BOLD leadership and execution excellence, leveraging data, automation, and AI-enabled insights. HOW WILL YOU DRIVE IMPACT Success is measured by the ability to deliver results through BOLD capabilities and measurable outcomes. Team & Leadership Impact (Build Championship Teams) Partner cross-functionally with in-house design teams to maintain corporate branding standards and align seasonal creative direction across league programs. Confidently influence team creative output by sharing fresh perspectives and new ideas through clear written and verbal communication with internal partners. Collaborate effectively across all departments, contributing equ