Production Line Management Engineer Jobs

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

About the Opportunity Enabling millions of distributed energy devices to deliver reliable and predictable grid services to the electricity industry requires state-of-the-art forecasting, control systems, optimization algorithms, and data science. As such, EnergyHub seeks to hire a Senior Forecasting and Optimization Engineer to join EnergyHub’s Data Science and Power Systems Intelligence team. As a Senior Forecasting and Optimization Engineer you will work closely with some of the brightest minds in the electricity industry to solve some of the most difficult problems in distributed energy. The algorithms and data systems that you contribute to will be key to enabling a carbon-free distributed energy future. Main Responsibilities: What you’ll do Develop and improve accurate and robust energy forecasting models Develop and improve control and optimization algorithms Design, write, test, and deploy production-grade code for mission-critical forecasting and optimization products and related algorithms Build and use tools and processes to monitor and assess the quality of operational forecasting and optimization models Translate data from one of the largest distributed energy datasets in the electricity industry into actionable insights for electric utilities and other energy industry stakeholders Provide guidance to other engineers and scientists regarding machine learning, forecasting and optimization methods Present results clearly to internal and external stakeholders Collaborate closely with stakeholders inside and outside of EnergyHub including Data Engineering, Client Success, Marketing, Sales, Product, and Market Development teams Other duties as assigned Required Skills and Experience: What you need Passion for enabling a carbon-free, distributed energy future At least five years of experience in machine learning, statistical analysis, data visualization, control systems engineering, and/or mathematical optimization Experience developing data pipelines using la

About the role The Model Shaping team at Together AI works on products and research focused on tailoring open foundation models to downstream applications. We build services that enable machine learning developers to choose the best models for their tasks and further improve these models using domain-specific data. In addition, we develop new methods for more efficient model training and evaluation, drawing inspiration from a broad range of ideas across machine learning, natural language processing, and ML systems. As a Research Engineer within Model Shaping, you will develop a platform that enables users to customize open-source models with their own data. Working across the training and inference stacks, you will build and improve our Fine-Tuning, Reinforcement Learning, and Evaluation services – from ensuring a seamless path from post-training to production serving, to optimizing the inference engine for RL training workloads. You will collaborate closely with our product, research, and engineering teams to keep the API reliable, performant, and well integrated into the company's technical infrastructure. Above all, you will help build the foundational layer of the open-source AI ecosystem, enabling developers around the world to efficiently create high-quality models tailored to their specific applications. Responsibilities Design and build Together’s systems for customizing open-source models Build integrations between the Model Shaping and Inference platforms to ensure a seamless path from post-training to serving production workloads Add features to inference engines for large-scale post-training experiments, including optimizations for RL workloads Make sure the service is stable and robust, participating in an on-call rotation and ensuring 24/7 availability of our platform Requirements Have 2+ years of experience building and deploying machine learning-based services in a production environment Have hands-on experience with modern inference engines, such as

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 Lead large-scale brand campaigns across digital, events, and out-of-home. Partner with engineering and product marketing on major product launches. Turn complex technical ideas into clear, compelling visual communication. Evolve the Baseten visual identity into a brand system that scales. Own projects end-to-end, from concept through launch, collaborating directly with marketing, product, engineering, and leadership. Shape our employer brand and help define how new hires experience Baseten. Raise the bar for craft across every customer touchpoint. REQUIREMENTS You have a portfolio of exceptional work with outstanding visual craft and attention to detail. You care deeply about quality and sweat the details. You communicate ideas clearly and thrive in collaborative environments. You know when to build systems, not just execute on assets. You default to ownership and are comfortable leading highly cross-functional projects from concept through launch. You're excited by technical products and know how to make complex ideas feel consumable without oversimplifying them. You thrive in a fast-moving environment with a high bar for quality. You have strong opinions about design and can articulate why something works - and why it doesn't. NICE TO HAVE Motion design and animation experience Experience designing for developers or highly technical audiences. BENEFITS Competitive compensation, including meaningful equity (U.S

Here's a summary of the role: Do you love building scalable cloud platforms and solving complex engineering problems with modern technologies? As a Senior Software Engineer at Diligent, you'll design and deliver high-performing , serverless applications that power our global SaaS platform. You'll work extensively with TypeScript, Node.js, AWS, and event-driven microservices, owning services from design to deployment and production monitoring. This is an opportunity to influence technical decisions, mentor engineers, and explore how AI can transform software development and engineering productivity. If you're passionate about cloud-native architectures, distributed systems, and building software that scales to millions of users, we'd love to meet you. Here's a breakdown of what you'll do (not all of it, just the important stuff): Design and build scalable backend services and event-driven microservices using TypeScript and AWS. Develop secure APIs and integrations that power reporting, analytics, and dashboard experiences. Build and maintain serverless solutions using AWS services such as Lambda, EventBridge , SQS, and DynamoDB. Drive engineering excellence through testing, observability, automation, and production readiness practices. Contribute to infrastructure-as-code and CI/CD pipelines using AWS CDK and modern DevOps practices. Mentor engineers, participate in architecture discussions, and champion the use of AI tools to improve development efficiency. These are the essentials you'll need to get an interview: 6-8 years of professional software engineering experience. Strong experience with TypeScript, Node.js, and modern backend development patterns. Hands-on experience building cloud-native applications on AWS. Strong understanding of serverless architectures and event-driven microserv

Mechanical Maintenance Engineer ensures smooth, safe, and efficient operation of all mechanical systems, equipment, and machinery in the precast factory through preventive and corrective maintenance, minimizing breakdowns, supporting continuous production operations, and ensuring compliance with safety and quality standards. Source: Adani Group | Job ID: 53487

Mechanical Maintenance Engineer ensures smooth, safe, and efficient operation of all mechanical systems, equipment, and machinery in the precast factory through preventive and corrective maintenance, minimizing breakdowns, supporting continuous production operations, and ensuring compliance with safety and quality standards. Source: Adani Group | Job ID: 53486

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 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've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. Our team includes creators of popular open-source projects (e.g., Seaborn , Luigi ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We're building a platform that covers the whole life of an LLM: training it, deploying it, and observing it in production. We already run multi-node training, elastic inference, sandboxes, and distributed volumes, and we control the infrastructure underneath. We’re looking for research depth in post-training to sit alongside our systems and product work. What You'll Do: We are looking for research scientists with a strong track record in reinforcement learning, machine learning, and foundation models, including large language and multimodal models, to join our research team. This role is well suited to candidates interested in improving existing methods and developing new techniques for large-scale model training, optimization, and inference, extending models to long-context and long-horizon tasks, and improving inference-time efficiency, reliability, and robustness in high-stakes real-world deplo

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 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've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. Our team includes creators of popular open-source projects (e.g., Seaborn , Luigi ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: Most of the value of owning a model shows up at serving time. We're building a platform that covers the whole life of an LLM -- train it, deploy it, observe it -- and inference is where teams feel the difference every day. We already run elastic inference, sandboxes, distributed volumes, and multi-node training, and we control the infrastructure underneath, so the serving stack is ours to shape rather than something we resell. You will do hands-on inference research at Modal, working with the research lead to pick high-impact bets and owning them end to end. The bets that matter most are the ones that move cost per token and tail latency on the workloads our customers actually run. What You'll Do: Own end-to-end inference research bets: speculative decoding, disaggregated prefill/decode, quantization (FP8, INT4), KV-cache and memory management, autoscaling for spiky serverless traffic, and whateve

Role Purpose: The Machine Learning Engineer IV will play a critical role in advancing Jumio's Fraud team's mission to develop and enhance state-of-the-art solutions for fraud detection for ID verification purposes. This role is essential for ensuring the highest standards of security and user verification through the application of advanced machine learning and deep learning techniques, ultimately contributing to Jumio's leadership in the online identity verification, eKYC, and AML solutions market Role Value: As a Machine Learning Engineer IV at Jumio, you will have the opportunity to significantly impact the security and user experience of our ID verification solutions. Your expertise in deep learning and computer vision will drive the development of innovative algorithms that keep Jumio at the forefront of the industry. By deploying and maintaining these models in production, you will ensure the robustness and reliability of our solutions, supporting our clients across diverse industries such as Financial Services, Travel, Sharing Economy, Fintech, and Gaming. Your contributions will be pivotal in maintaining Jumio's reputation as the leading provider of online identity verification solutions, helping to meet the growing demand for secure and seamless user verification globally. Example Responsibilities . Develop, maintain, and own key fraudulent CV models of Jumio, which shapes the whole fraud product offering of Jumio. Design and implement machine learning, deep learning, classical CV focused on fraud detection. Research to support the deployment of the advanced algorithms. Deploy models as AWS SageMaker endpoints or directly onto devices. Stay updated with the latest advancements in machine learning, deep learning, and computer vision by engaging with academic papers and attending industry conferences. Work collaboratively with other engineers and product managers in an Agile development environment. Experience and Qualifications Bach

About Ema Ema is building the world’s leading Agentic AI platform to transform enterprise productivity. We enable organizations to delegate repetitive tasks to Ema, the Universal AI Employee, delivering 10x gains in workforce efficiency, across functions. Founded by former executives from Google, Coinbase, Flipkart, and Okta, our team includes engineers from premier tech companies and graduates of Stanford, MIT, UC Berkeley, CMU, and IITs. We are backed by industry leading investors including Accel, Naspers/Prosus, Section32, and angels like Sheryl Sandberg and Dustin Moskovitz. Headquartered in Silicon Valley and with offices in London, Bangalore and Vancouver, Ema is at the frontier of what Agentic AI can do in production — we ship real systems that run real business processes at scale. What You'll Own As our Social Media & Founder Brand Manager, you'll sit at the intersection of content, brand, and experimentation. You'll shape how the world sees Ema and its founders — building a distinctive, high-reach presence across LinkedIn, X, YouTube, and beyond, in the fastest-moving category in tech: agentic AI. Social Media & Content Creation Scale Ema's LinkedIn from 130K → 200K+ with bold, creative storytelling and a strong lens on ICP Maintain a consistent 4-week rolling calendar across social media, blogs, and newsletter channels — while staying nimble enough for moment marketing: hopping on relevant tech trends and conversations in real time, especially for the founders Create compelling video content for both Ema and the founders — from short-form clips and talking-head videos to event and product moments — built natively for each platform Work with design to repurpose existing content — whitepapers, blogs, interviews, videos — into carousels, short videos, threads, and newsletters to achieve consistency + repetition as a brand Continuously experiment with and improve existing channels, and identify the right new distribution channels and formats to scale E

Location : Remote (U.S.) Other Considerations: U.S. Citizen or Permanent Resident required with the ability to obtain a Public Trust LTS is seeking a Cyber Security Analyst to support the Department of Veterans Affairs (VA) Health Portfolio. The Health PMO support contract provides IT program management, project management, technical management, financial management, functional planning, and documentation analysis in support of the Enterprise Program Management Office (EPMO) Enterprise Program Management Division (EPMD) Health Portfolio The VA Health Portfolio is focused on development and execution of quality IT projects that address the needs of Veterans and health care providers through management of health care information and sustainment of production software to keep the mission going. What You'll Do: This individual will support cybersecurity efforts across multiple projects within a portfolio setting and proactively monitor upcoming cyber priorities across the VA Health portfolio. Communicate and provide consultative support on the VA on matters related to system security certification & accreditation and Authority to Operate (ATO). Coordinate and lead security and privacy activities within project teams and develop security and privacy related artifacts. Review and identified system/applications security controls in accordance with NIST SP-800 53 Rev 4 guidance and VA Handbook 6500. Responsible for on time deliverables of assigned and related security and privacy artifacts. Must be able to identify and mitigate risks to the program. Demonstrated experience in a remote work environment. Ability to proactively communicate and coordinate with various internal and external project stakeholders, depending on needs. Identifying and communicate symptoms for process improvement. Ability to work independently with minimal guidance and supervision Support a team of other cyber security professionals Support Application development/maintenance and IT

Our vision is to transform how the world uses information to enrich life for all. Join an inclusive team passionate about one thing: using their expertise in the relentless pursuit of innovation for customers and partners. The solutions we build help make everything from virtual reality experiences to breakthroughs in neural networks possible. We do it all while committing to integrity, sustainability, and giving back to our communities. Because doing so can fuel the very innovation we are pursuing. Key Responsibilities Capacity Optimization & Advanced Analytics Develop optimization models to improve factory capacity utilization, throughput, cycle time, tool loading, and bottleneck management. Build mathematical models for capacity planning, production allocation, constraint identification, and investment prioritization. Apply operations research techniques such as linear programming, mixed-integer programming, constraint programming, stochastic optimization, and simulation-based optimization. Design algorithms to support factory maxout strategies and identify opportunities to unlock additional capacity without unnecessary capital investment. Semiconductor Manufacturing Problem Solving Partner with manufacturing, industrial engineering, planning, equipment, process, and business teams to understand capacity constraints and operational challenges. Analyze tool capability, process flows, product mix, WIP movement, cycle time, dispatching rules, and factory constraints to recommend optimization opportunities. Support scenario analysis for capacity expansion, product mix changes, technology transitions, and capital planning decisions. Develop data-driven recommendations that improve decision quality

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Role Overview The ASIC Test Engineer is responsible for test program development, silicon validation, yield analysis, and production test optimization for advanced ASIC/SSD controller products. This role supports both NPI and HVM phases, driving fast ramp, robust quality, and cost-effective test solutions across wafer sort and final test. Key Responsibilities Develop and debug ATE test programs for wafer sort and final test (probe to package) to support silicon bring-up and production ramp. Drive yield analysis, failure characterization, and root cause investigation to accelerate yield improvement and ensure product quality. Collaborate with design, product engineering, reliability, and OSAT teams to resolve test and silicon issues across the product lifecycle. Optimize test coverage, test time (TTR), and cost through test content development, guardband tuning, and screening strategy improvements. Support hardware bring-up including probe cards, load boards, and tester configurations to ensure stable manufacturing operations. Enable efficient NPI execution by developing scalable test solutions and improving cycle time from bring-up to HVM. AI/Advanced Data Capability Apply AI/ML and data-driven methodologies to enhance yield analysis, anomaly detection, and failure classification. Leverage AI-assisted tools (e.g., code generation, debug automation, data analytics platforms) to improve engineering productivity and debug cycle time.<br

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, leading the design and architecture of our open-weights model platform spanning inference and fine-tuning: real-time GPU serving, high-throughput batch inference, and model fine-tuning. You’ll set technical direction across model serving and inference engines, fine-tuning and training pipelines, GPU autoscaling and utilization, batch pipelines, backend services, and observability, and mentor engineers as you go. This role is ideal for a senior engineer who enjoys owning ambiguous, high-impact systems and 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… Lead the design of infrastructure that helps DoorDash teams move GenAI ideas from prototype to production, increasing the velocity of business impact from AI across the company. Own and evolve our open-weights serving stack — real-time GPU endpoints, high-thr