Production Scheduler Enhancement Engineer Jobs

About the Role At FourKites we have the opportunity to tackle complex challenges with real-world impacts. Whether it’s medical supplies from Cardinal Health or groceries for Walmart, the FourKites platform helps customers operate global supply chains that are efficient, agile and sustainable. Join a team of curious problem solvers that celebrates differences, leads with empathy and values inclusivity. As a Senior Customer Engineer, you own the technical customer relationship end to end. You run discovery independently, design integration and agentic workflow architectures for complex enterprise problems, and deploy solutions live with customers — often before they know exactly how to articulate what they need. You write optimized, production-grade code at speed, grounded in strong data structures and algorithms fundamentals, because compressing the time from customer problem to working solution is how FDE delivers its value. You bring genuine innovation to hard problems — your solutions are technically sound, elegant, and often non-obvious. You are the primary technical contact for 2–4 major enterprise accounts, you mentor FDEs on the team, and you are building the skills that will take you into Staff-level technical leadership. What You'll Do Own complex integration and AI agent implementations end-to-end — from technical discovery through go-live and post-launch enhancement — as the primary technical contact for 2–4 enterprise accounts Design integration architectures with explicit attention to error handling, retry logic, observability, failure recovery, and multi-system authentication Design and deploy agentic AI workflows that orchestrate supply chain operations — from requirements through production, including regression testing and validation before each customer deployment Deploy AI agent workflows live with customers present — configuring and troubleshooting in the room during customer calls, not gathering requirements to build later Run customer discovery

Role Purpose At Jumio, we’re building trusted identity solutions powered by machine learning and biometrics. As a Data Engineer II , you will take ownership of designing, building, and scaling data pipelines that power our ML systems. You’ll work closely with ML engineers, platform teams, and product stakeholders to enable robust dataset creation, benchmarking, and production-grade data workflows on AWS. What You’ll Do Design, build, and maintain scalable and reliable data pipelines for dataset creation, transformation, and benchmarking Own and optimize Airflow pipelines on AWS for data processing, orchestration, and evaluation workflows Write efficient, production-grade SQL and Python code for large-scale data processing and analysis Partner closely with ML engineers to enable model training, evaluation, and benchmarking pipelines Improve pipeline performance, reliability, and observability, ensuring high data quality in production Build and maintain systems to support model performance tracking and data drift monitoring Troubleshoot and resolve data issues across pipelines, ensuring minimal impact on ML workflows Contribute to data architecture decisions and best practices across the platform Collaborate cross-functionally with ML, platform, and data teams to support scalable ML infrastructure What We’re Looking For 3–5 years of experience in Data Engineering, Data Platforms, or related roles Strong proficiency in Python and SQL with experience in production systems Hands-on experience with AWS services (S3, EC2, SageMaker or similar) Solid experience building and managing Airflow (or similar orchestration tools) Strong understanding of data engineering fundamentals (ETL/ELT, data modeling, pipeline design) Experience working with large-scale datasets and distributed data systems Experience supporting ML workflows, datasets, or evaluation pipelines Strong problem-solving skills and ability to work independently in a fast-paced environment Nice to Have Experience w

About the Team Training Runtime designs the core distributed runtime that powers everything from early research experiments to frontier-scale model runs. We build robust, scalable, high performance components to support our distributed training workloads. Our priorities are to maximize the productivity of our researchers and our hardware, accelerating progress towards AGI. Within Training Runtime, the Runtime Foundations team develops the distributed OS responsible for orchestrating the large numbers of processes that make up modern training workloads and providing all necessary observability and resilience to operate in frontier scale environments. Our runtime sits beneath training frameworks and on top of research infrastructure, ensuring jobs run reliably across massive clusters while maintaining performance, stability, and observability. Success for us is measured by both system reliability and researcher velocity - enabling ideas to scale from experiments to production training runs. About the Role As a Training Runtime: Runtime Foundations Engineer , you will work on the software that ties thousands of computers together and exposes them as a unified system. This system has to serve individual researchers running multiple parallel experiments, as well as our largest training runs spanning 100’s of thousands and even millions of machines and accelerators. This requires easy to use, introspectable systems that can promote a fast debugging and development cycle, as well as relentless optimization for scale while maintaining stability and performance throughout. You will work primarily in Codex + Rust , building high-performance asynchronous systems with a strong emphasis on performance, correctness, resilience, and scalability. Working at this scale and at the frontier of AI development poses novel challenges. We support many different types of research, and the problems you will be working on are highly ambiguous and require a superb ability to jump into novel d

You will lead a small, hands-on engineering team building the secure, scalable Core Analytics Data Access Platform that accelerates Datadog’s Applied AI and analytics capabilities. The team owns the Data Access Platform — a unified interface that lets AI and analytics teams discover and self-serve production-ready datasets while abstracting underlying systems and embedding required legal and compliance guardrails. In this role you’ll own technical direction, contribute to design and code, and partner closely with Applied AI, Product Analytics, and internal platform teams to provide reliable datasets and APIs for model training and analysis. This role balances day-to-day engineering leadership with long-term platform planning. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Lead a Hands-On Engineering Team: Manage, mentor, and grow a small team of 2–4 data engineers (mix of senior and junior) across Paris and NYC, fostering technical excellence and career development. Own Technical Direction and Delivery: Define architecture, engineering priorities, and the team roadmap for the Data Access Platform, driving implementation of scalable, secure data pipelines and platform services. Contribute to Design and Code: Spend substantial time coding, reviewing, and shipping critical platform components to ensure performance, reliability, and operational excellence. Partner with Internal Stakeholders: Work closely with Applied AI, Internal Product Analytics, product managers, and platform teams to define data contracts, APIs, SLAs, observability, and curated analytical datasets. Ensure Data Security, Governance, and Reliability: Implement access controls, lineage, monitoring, and compliance guardrails to support safe model training and repeatable analytics workflows.

SpaceX was founded under the belief that a future where humanity is out exploring the stars is fundamentally more exciting than one where we are not. Today, SpaceX is actively developing the technologies to make this possible, with the ultimate goal of making life multiplanetary and expanding consciousness to the stars. SpaceXSI is building Super Intelligence to help humanity understand the universe. Our teams are building the full Super Intelligence stack: from our Colossus supercomputers, to Grok models, to our suite of applications, including Grok Bot, Grok Build, Grok Imagine, Grok Voice, and X. We're creating a powerful flywheel where more compute trains better models, better models power more useful products, and what we learn from people using those products shapes what we build next. ABOUT THE ROLE: The Imagine Product team is redefining AI-driven media experiences for Grok users worldwide. In this role, you’ll build and scale robust, high-performance systems that power immersive, multi-modal media interactions—leveraging cutting-edge AI to enable seamless generation, processing, and delivery of images, video, audio, and beyond. Your work will drive engaging, real-time user experiences that captivate and delight millions, turning advanced multimodal models into production-grade features. If you’re a driven problem-solver passionate about AI, media technologies, and creating scalable solutions that shape the future of consumer AI, this is your opportunity to make a lasting impact. RESPONSIBILITIES: Design and implement scalable systems to support Grok's AI-driven media experiences, ensuring high performance, reliability, and low-latency at global scale. Architect robust infrastructure for real-time multi-modal interactions, including handling generation requests, media processing, and seamless integration with frontend and model serving layers. Build and optimize large-scale data pipelines to ingest, process, and analyze multi-modal data (images, video, audio

About the Job: Software powers the world, and LaunchDarkly empowers all teams to deliver and control the best software. As an Senior Infrastructure Engineer on the IDE team, you'll help us build, automate, and improve the systems that keep LaunchDarkly running at scale. Our platform serves over twenty trillion feature flags daily across a global AWS footprint. The IDE team owns the infrastructure layer — networking, compute, CI/CD, databases, observability — and we're looking for someone who wants to make that layer increasingly self-service and automated. You'll write software that replaces manual processes, build tools that help other engineers move faster, and contribute to a culture where operational toil is treated as a bug to be fixed, not a fact of life. As part of our you-build-it-you-run-it culture, all engineers participate in an on-call rotation. Responsibilities: Automate infrastructure provisioning, deployment, and operational workflows Build and improve internal tools and platforms that make other engineers more productive Manage and evolve our AWS infrastructure using Terraform Participate in on-call rotations and turn incident patterns into permanent fixes Collaborate with product engineering teams to understand their infrastructure needs and reduce friction Identify repetitive operational work and replace it with software Qualifications: 8+ years of professional software engineering experience Familiarity with AWS (you've used it; you don't need to have memorized every service) You write code to solve problems — not just configuration, but actual software when the situation calls for it You're curious about how things work and willing to learn new tools quickly A commitment to working in a communicative and collaborative environment You hold yourself and others to a high bar when working with production systems You value code quality, automated testing, and engineering best practices Nice to have (but not required): Experience with Terraform or simi

About the Team IT Systems Operations serves as the operational control layer connecting Security, Engineering, and Employee Technology platforms. The team ensures employee-facing systems, identity workflows, and enterprise applications operate in a predictable, governed, and continuously reliable manner as the organization scales. Beyond implementation, the team establishes structured operating patterns that ensure platform changes, access models, integrations, and lifecycle workflows evolve safely and consistently across the enterprise environment. About the Role This role acts as an operational owner for identity-connected enterprise SaaS platforms and system change controls supporting OpenAI’s compliance requirements. The engineer will be responsible for ensuring that production configuration, access models, and platform changes remain compliant, auditable, and consistently operated through defined controls. You will own and operationalize controlled system and workflow changes across identity platforms, SaaS applications, collaboration tooling, and enterprise infrastructure. You will partner closely with Security, Platform Engineering, and IT Support Operations to: Ensure identity and access workflows behave consistently across systems Implement structured rollout and configuration practices for enterprise applications Improve visibility and traceability of system changes impacting employee workflows Translate operational requirements into durable automation and policy-aligned implementations Success in this role requires not only strong engineering capability, but also sound operational judgment, disciplined documentation practices, and effective cross-functional collaboration. In this role, you will: Enterprise SaaS & Identity Platform Ownership Own administration and operational stewardship of enterprise SaaS and identity-connected platforms, ensuring configuration integrity, access governance, and compliance with defined control requirements. Own onboard

P-1651 At Databricks, we’re passionate about enabling data teams to solve the world’s toughest problems — from advancing the future of transportation to accelerating medical breakthroughs. We do this by building and operating the world’s best data and AI infrastructure platform so our customers can turn deep data insights into business impact. Founded by engineers and driven by customer obsession, Databricks takes pride in tackling hard technical challenges — from designing next-generation UI/UX for working with data, to scaling our services and infrastructure across millions of virtual machines. And we’re only getting started. As a Sr. Software Engineer for Customer Experience Intelligence, you will architect and deliver Databricks' AI-native vertical workflow platform. CXI is building intelligent systems that orchestrate AI agents, humans, and enterprise tools into end-to-end operational workflows. Support is our first production domain and the platform is designed to expand across multiple domains such as IT, Security, Legal, Marketing, and other knowledge-worker workflows, with a roadmap toward broader productization. The Impact You Will Have: Architect the Agentic Ecosystem: Contribute to the technical vision, core infrastructure, and backend architecture for Databricks’ next-generation Enterprise Agentic Framework. Scale across multiple domains: Build a vertical modular, multi-tenant agent platform initially optimized for Customer Support, but natively designed to expand into other domains such as IT, Security, Compliance, Marketing, HR, Legal and all ticket based workflows across the company. Engineered Reliability: Drive rapid, iterative backend development while upholding strict quality, safety, throughput, and reliability standards for agentic-based systems. Orchestrate Complex Workflows: Design state-machine and agentic workflows that seamlessly evolve from human-in-the-loop validation to fully automated execution. Enterprise-Grade Observability: Imp

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products. THE ROLE Baseten is building for talent density. We believe attracting and retaining exceptional people, and ensuring they feel recognized and valued for their impact, is core to becoming the best place to work. Compensation is a critical lever in that mission. As our Compensation Manager, you will own compensation programs company-wide. You’ll be a trusted advisor to senior leaders, shaping our compensation philosophy, leveling framework, and equity programs to ensure we remain competitive, principled, and performance-oriented as we scale. This role blends strategy and execution: designing clear, fair systems while moving quickly in a high-growth environment. RESPONSIBILITIES Own and evolve Baseten’s company-wide compensation strategy, philosophy, and programs. Collaborate with leadership and HRBP to create and evolve job architecture and leveling frameworks. Build and maintain compensation bands. Conduct regular market benchmarking to ensure comp bands and strategy remain competitive in a fast moving industry. Partner closely with Talent to design and approve competitive new hire offers, advising on negotiation strategy within our compensation principles. Lead bi-annual leveling and compensation review cycles to ensure market competitiveness and reward high performance across teams. Manage new hire equity grants in partnership with Finance and Legal. Design and administer a thoughtful equity refresher program for ten

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We're looking for Forward Deployed ML Engineers who want to work at the intersection of deep technical work and direct customer impact. As an ML FDE, you'll partner with leading AI companies and foundation model labs to help them achieve state-of-the-art performance on their most demanding workloads — LLM serving, model training (SFT, RLHF), audio pipelines, scientific computing, and more. You're helping teams reach outcomes most engineers can't on their own. The FDE team today includes world-class software engineers, computational scientists, ML engineers, and former founders. We're looking for people with strong engineering fundamentals, deep curiosity across the AI stack, and energy for working directly with customers on hard problems. You will: Work hands-on with companies like Suno, Lovable, Cognition, and Meta to architect and optimize production AI workloads

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 the Milwaukee, WI area and requires close collaboration across software, hardware, operations, and product engineering teams. We welcome applicants from outside Milwaukee who are willing to relocate. Relocation assistance/bonus will be a part of compensation package. 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

About the Team OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform. About the Role You will develop and evolve the tooling ecosystem that hardware engineers rely on every day — from hardware compilers and IR transformations to simulation, debugging, and automation infrastructure. The work spans software engineering, compiler concepts, and practical hardware workflows, with direct impact on how quickly and effectively we design next-generation AI systems. You’ll collaborate closely with architects, RTL designers, and verification engineers to translate real engineering friction into durable, scalable tooling solutions. In this role you will: Build and improve the software tooling that makes hardware teams faster: compilation, IR transforms, RTL generation, simulation, debug, and automation. Extend and integrate hardware compiler stacks (frontends, IR passes, lowering, scheduling, codegen to Verilog/SystemVerilog) and connect them to real design workflows. Improve developer experience and reliability: reproducible builds, better error messages, faster iteration loops, and dependable CI and regression infrastructure. Work closely with designers and verification engineers to turn real pain points into durable tools. Dive into RTL when needed: read and reason about Verilog/SystemVerilog to debug issues, validate tool output, and improve debuggability. Be willing to go all the way down the stack when necessary, including gate-level views, synthesis results, and implementation artifacts. Help enable PPA optimization loops by building analysis and au

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE As a Software Engineer at Baseten, you will own one of the most critical surfaces of our business: pricing, billing, and revenue infrastructure. As we launch more and more products— billing is no longer just operational plumbing. It is a strategic lever for growth. This role will establish clear ownership of billing as a function and create leverage for Finance, Sales, and GTM teams while maintaining a seamless customer experience. RESPONSIBILITIES Own Baseten’s end-to-end billing and revenue infrastructure, including pricing, invoicing, metering, and reporting foundations. Build and evolve our billing platform and integrations (including Orb), ensuring correctness, auditability, and a high-trust experience for customers and internal teams. Partner closely with Finance, Sales, GTM, and Forward Deployed Engineering to turn real-world workflows into reliable internal tooling and automation (quoting, approvals, renewals, usage reconciliation, revenue reporting). Design systems that scale with new products, packaging, and go-to-market motions, making billing a strategic lever for growth. Drive reliability and operational excellence for revenue-critical workflows: monitoring, alerting, incident response, backfills, and clear runbooks. Lead from the front on high-impact projects: clarify requirements, propose crisp technical approaches, ship iteratively, and raise the bar on quality and velocity. Debug and resolve pro

DGM - Mine Operations encompasses overseeing all aspects of mining operations, from planning and execution to resource management and quality control. Responsible for ensuring adherence to approved plans and safety protocols, the Manager directs drilling, blasting, and coal seam removal activities, guiding shift leaders to meet production targets. Collaborating closely with colliery engineers, they facilitate continuous improvement initiatives and preparatory works, while also managing equipment maintenance and contractor relations. The Manager plays a pivotal role in driving productivity, cost reduction, and safety enhancement measures, ensuring compliance with regulatory guidelines and DGMS standards. Source: Adani Group | Job ID: 47496

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE As a Solutions Architect at Baseten you will partner closely with Sales and customers to translate business needs into technical solutions, run technical discovery, and guide repeatable deployments and proofs of value for customers. This role is a great fit for entrepreneurial, customer-facing technical professionals who want a front-row view into how modern companies adopt AI at scale, and who enjoy working across technical discovery, solution design, demos, deployment scoping, and hands-on customer implementations, in close partnership with Sales and Engineering. RESPONSIBILITIES Partner with Sales on customer discovery calls (most often second calls, occasionally first calls for large accounts). Lead demos and technical scoping to align on success criteria, architecture, and deployment approach. Own benchmarking and repeatable deployments , including: Handling standard deployment patterns and configurations across many modalities – LLMs, embeddings, image and video generation, Voice AI, etc. Advising on tradeoffs like H100s vs B200s and latency-optimized vs throughput-optimized setups. Driving consistent “playbook” style deployments for common models and use cases. Become a power user of different runtimes such as vLLM, SGLang, and TRT-LLM and all the common configurations and tradeoffs between them Drive POC and project execution , including: Scoping POCs and keeping stakeholders aligned on timeline, deliver