Production Line Management Engineer Jobs

The following description is not intended as an exhaustive list of all responsibilities, duties and skills required of personnel so classified. Management retains the discretion of adding or changing the duties of the position at any time. About the Role We’re looking for a Mechanical Engineer who brings a strong foundation in mechanical or manufacturing engineering and thrives in a customer-facing, product-driven role. This is a unique opportunity for someone who understands how things are made—but is equally comfortable engaging with clients, coordinating across departments, and driving products from idea to mass production. Key Responsibilities Own the end-to-end mechanical component lifecycle —from concept validation through to mass production—focused on enclosures and structural parts. Act as a technical liaison between internal teams (design, procurement, sales) and external stakeholders (customers, suppliers, factories). Collaborate with clients to define product requirements, ensuring feasibility across design, cost, and manufacturing capabilities. Support business development teams by offering technical insights during customer meetings, RFQ responses, and project scoping. Translate technical needs into action plans , guiding suppliers and contract manufacturers to align with quality, cost, and timeline expectations. Perform mechanical feasibility assessments including Design for Manufacturability (DFM) and Design for Assembly (DFA) reviews. Oversee supplier coordination , particularly for processes such as CNC machining, metal forming, die-casting, and surface finishing. Contribute to pricing strategies by analyzing material costs, process efficiencies, and competitive benchmarks. Lead or support new product introduction (NPI) activities, ramp-up phases, and factory readiness initiatives. Stay up to date on manufacturing trends , technologies, and customer needs across consumer electronics and related sectors. Qualifications Bachelor’s degree in Mechanical

As a Research Engineer on our team, you will partner with Research Scientists to turn research ideas into working systems, building the data, tooling, and infrastructure that enable rapid iteration, trustworthy evaluation, and a smooth path from prototype to production. Building on our track record of AI-powered solutions (e.g., Bits AI , Bits Evolve , and our time series foundation model ), Datadog AI Research tackles high-risk, high-reward problems grounded in real-world challenges in cloud observability and security. We are focused on two research areas: World Models for Observability -- Training multimodal foundation models that learn the joint dynamics of distributed systems across metrics, traces, logs, topology, and events. These models power advanced forecasting, anomaly detection, root cause analysis, counterfactual simulation ("what if?"), and provide a learned planning backbone for our autonomous agents. Trained Agents for Observability -- Post-training models to operate autonomously across Datadog's domain. SRE incident response is our first target, with a clear path to code repair, security response, and infrastructure optimization. We build the simulation environments, RL training loops, and evaluation infrastructure needed to train agents that match or surpass frontier models at a fraction of the cost. What You'll Do: Build and operate multimodal data pipelines, training and evaluation infrastructure, benchmarks, and internal tooling Implement models, run experiments at scale, and profile for reliability, performance, and cost Build simulation environments and replay infrastructure for agent training and evaluation Orchestrate distributed training and distributed RL with Ray, including scheduling, scaling, and failure recovery Establish rigorous automated benchmarks and regression tests for world model predictions, agent performance, and simulation fidelity Collaborate with Research Scientists, Product, and Engineeri

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 AI Native is our segment for companies whose core product is AI, from their first model in production through serious scale. You'll be the first person at Baseten to reach many of these founders, and you'll win them early. This is a high-velocity, high-intensity seat. You're running many early-stage opportunities at once, moving fast with founders who move fast, and going deep enough technically to be useful on day one. If you want a front-row seat to the frontier of AI and the ambition to grow into our largest accounts, this is the seat. RESPONSIBILITIES Source, close, and grow new business with early-stage AI companies. You own pipeline generation, not just what's handed to you Run fast, technical sales cycles with founders and early engineering teams, from first call to first production workload Prioritize ruthlessly across a high volume of opportunities and drive each one forward without dropping the thread Pull in applied research and engineering when a deal needs depth, and keep everyone moving on your timeline Bring the field back to product. You see what early AI teams need before the rest of the market does REQUIREMENTS 2+ years of closing sales experience in a SaaS or infrastructure business, with a record of closing Genuine curiosity about open-source models and AI infrastructure. You follow model releases and can hold a real conversation with engineers Strong prioritization and project management ins

About the Role Together AI is building the Inference Platform that brings the most advanced generative AI models to the world. Our platform powers multi-tenant serverless workloads and dedicated endpoints, enabling developers, enterprises, and researchers to harness the latest LLMs, multimodal models, image, audio, video, and speech models at scale. If you get a thrill from optimizing latency down to the last millisecond, this is your playground. You’ll work hands-on with tens of thousands of GPUs (H100s, H200s, GB200s, and beyond), figuring out how to fully utilize every FLOP and every gigabyte of memory. You’ll collaborate directly with research teams to bring frontier models into production, making breakthroughs usable in the real world. Our team also works closely with the open source community, contributing to and leveraging projects like SGLang, vLLM, and NVIDIA Dynamo to push the boundaries of inference performance and efficiency. Shape the core inference backbone that powers Together AI’s frontier models. Solve performance-critical challenges in global request routing, load balancing, and large-scale resource allocation. Work with state-of-the-art accelerators (H100s, H200s, GB200s) at global scale. Partner with world-class researchers to bring new model architectures into production. Collaborate with and contribute to the open source community, shaping the tools that advance the industry. A culture of deep technical ownership and high impact — where your work makes models faster, cheaper, and more accessible. Competitive compensation, equity, and benefits. Responsibilities Build and optimize global and local request routing, ensuring low-latency load balancing across data centers and model engine pods. Develop auto-scaling systems to dynamically allocate resources and meet strict SLOs across dozens of data centers. Design systems for multi-tenant traffic shaping, tuning both resource allocation and request handling — including smart rate limiting and

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 looking for strong engineers with experience building software that developers love to work with. Our ideal candidate is someone with a demonstrated drive to build beautiful abstractions that enhance developer productivity. Requirements: 5+ years of experience developing high-quality Python, JS or Go applications or libraries where the code is used or interacted with by other developers A strong code-as-product sense that manifests as a focus on developer ergonomics and productivity. Knowledge of async programming and concurrency management/pitfalls A high level of customer empathy, good communication skills, and an openness to working directly with our users to help solve their problems. Ability to participate in on-call rotation and respond to production incidents. Ability to work in-person in our New York or Stockholm office. Any of the following would be a plus: Having built developer to

Software is eating the world, but AI is eating software. We live in unprecedented times – AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products. To make them safe, aligned and actually useful, these models need human eval and reinforcement learning through human feedback (RLHF) during pre-training, fine-tuning, and production evaluations. This is the main innovation that’s enabled ChatGPT to get such a large headstart among competition. At Scale, our products include the Generative AI Data Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI. At the foundation of these products is the Platform Engineering team. In this role, you will support the design and development of shared platforms used across Scale. This includes designing our foundational data platforms and lifecycle, architecting Scale’s core cloud infrastructure and orchestration stack, and redefining how engineers develop, build, test, and deploy software at Scale. You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies. You will: Drive the design, and implementation of our foundational platforms and systems, working closely with stakeholders and internal customers to understand and refine requirements. Collaborating with cross-functional teams to define, design, and deliver new features. Proactively identifying opportunities for, and driving improvements to, current p

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 The largest, most demanding enterprises are starting to run on Baseten, and they arrive with a range of security, compliance, and procurement requirements. As an Engineer on Baseten's enterprise engineering team, you'll build the capabilities that enable large organizations like Writer, HubSpot, and Notion to succeed on Baseten. Enterprise engineering authors the core building blocks, APIs, and user experiences powering the Baseten platform: identity and access management, billing, regional isolation, and self-hosted and single-tenant deployment options. This is deep product and systems work across the full stack, from designing authentication and authorization systems using standards like OAuth and OIDC to shipping the admin experiences enterprise IT teams use to manage their organization. EXAMPLE INITIATIVES Recent and upcoming work on the team: Fine-grained authorization for users, service accounts, and agentic workloads SSO and SCIM support, allowing customers to centralize and automate access to Baseten Expanding the billing platform to support evolving pricing models, advanced data exports, and controls to manage spend In-product management and enforcement of customer compliance requirements like data residency and HIPAA Securing network paths in and out of a customer's models with private connectivity and ingress and egress restrictions Allowing customers to run Baseten inside their own VPC, on-prem, or a

About the Team The AI Architect team partners with organizations to turn OpenAI's most capable models into meaningful, real-world impact. We work with customers across industries and digital-native businesses to identify where AI can create value, design secure and scalable solutions, and help those solutions move from early exploration into sustained production adoption. The team brings together technical strategy, customer partnership, and practical deployment expertise, working closely with Sales, Product, Engineering, Research, and specialist delivery teams. About the Role As an AI Architect, you will be the senior technical owner for a named portfolio of customers and the primary technical counterpart to their leadership teams. You will act as the “CTO of your book of business”, shaping each customer's AI strategy and guiding their journey from pre-sales discovery and solution evaluation through deployment, adoption, and measurable business impact. You will own the technical account plan across ChatGPT Enterprise, the OpenAI API, Codex, and other agentic AI solutions. In partnership with the Account Director, you will translate business priorities into a focused use-case portfolio, an actionable adoption roadmap, and a clear path to durable customer value and growth. The Account Director owns commercial strategy; you own the technical strategy, customer journey, and path to production value. You will remain accountable for the technical outcome while bringing in the right specialists across deployment, implementation, enablement, security, product, and partners to provide deeper expertise and execute work where needed. This role calls for strong industry fluency, sound architectural judgment, and the ability to move confidently between executive strategy and hands-on technical conversations. In this role, you will: Serve as the primary technical advisor and long-term technical relationship owner for a named portfolio of existing customers and pre-sales prospect

P-1439 As Applied ML/AI Engineer at Databricks, you will define and create the Agentic Machine Learning revolution. You will help world’s largest companies build and deploy massive classical machine learning solutions (such as personalized recommendations, fraud detection, dynamic pricing, forecasting) fully using Databricks’ agents and harnesses. After 30 years of painfully slow progress, expensive knowledge acquisition and tedious processes in classical ML, the agentic era has ushered innovation, scale and visibility for all: from the most junior data scientists and machine learning engineers to the world class experts. You will work on Databricks’ Genie Code, an agent and an ML “exoskeleton” that is authoring ML, training and deploying models, monitoring and self-healing production ML, all at the top-expert level. Additionally, you will develop ML solutions that under the hood address the most pressing questions non-technical business people have today: predictive and what-if questions. Your work is a top priority for Databricks and you will report to a Principal Software Engineer (a Director level position). The impact you will have: Build agentic end-to-end systems in a small, highly international team of experienced engineers in a flat and agile organization. Build solutions for people like you: software engineers, ML engineers, data engineers, data scientists and MLOps engineers. Own our applied ML investment by engaging with engineering and product teams across the company. Drive the development and deployment of state-of-the-art ML/AI models and systems that directly impact the capabilities and performance of Databricks’ products, infrastructure, and services. Architect and implement robust, scalable ML infrastructure, including model training and serving components to support seamless integration of AI/ML models into production environments. Work on novel forecasting techniques. Possibilities to contribute to the broader AI community by presenting a

As a Firmware Validation Engineer, you will validate firmware functionality at the component, subsystem and system level, ensuring features operate reliably within the broader vehicle platform. This includes testing embedded applications, control logic, and feature integrations across hardware interfaces, sensors, and actuators to confirm they meet functional, performance, and safety requirements. Your work directly impacts the quality and readiness of customer-facing features by catching issues early, improving integration stability, and ensuring smooth delivery of these features to internal customers. Through close collaboration with firmware developers, systems engineers and cross-functional teams, you will help deliver robust and reliable features to production. In this role, you will: Define and develop comprehensive test plans based on requirements, trace testcases to requirements, set pass/fail criteria and refine requirements based on test outcomes Develop and implement test plans on multiple test layers (HiL, Dyno, Vehicle) Define tooling needs to execute tests and evaluate results efficiently Collaborate with system, firmware & hardware engineers to ensureimplementations meet requirements and desired functionality in accordance withproduct requirements. Investigate firmware issues through data analysis and issue reproduction Qualifications BS degree in Electrical, Mechanical, Computer or Systems Engineering 4+ years of experience in developing or testing embedded software Test automation with Python or other scripting languages Experience writing code with source control (Git) Hands-on technical experience debugging complex systems involving networked microprocessors and software-controlled electrical or electromechanical devices Experience parsing and analyzing log data/source code and identifying rootcause. Positive attitude, team player, and abil

A World-Changing Company Palantir builds the world’s leading software for data-driven decisions and operations. By bringing the right data to the people who need it, our platforms empower our partners to develop lifesaving drugs, forecast supply chain disruptions, locate missing children, and more. The Role Substrate is the team responsible for Palantir’s core production infrastructure — 100s of K8s clusters — from on-prem to the major cloud hyperscalers, whether they are internet-connected or air-gapped, small hardware footprint or large. As a Senior Software Engineer on Substrate, you will design and build Palantir’s managed Kubernetes product offerings across all these environments. You and your team will be responsible for bootstrapping and operating the entire fleet of K8s clusters with zero manual steps by building industry leading tooling and contributing to core CNCF components. You will also be responsible for ensuring scale, stability and security across a matrix of compliance regimes and hosting infrastructure types. Your team culture emphasizes engineering rigor and operational excellence at scale. This means issues in production should be pre-empted and deeply root-caused, and investments in automation and self-healing systems are key. If you’re excited about infrastructure at scale and working with Kubernetes, this is the right role for you. Core Responsibilities Deliver a container runtime to challenging new environment types - new clouds, on premise, edge devices Build automation and establish standards for operating K8s securely at scale with zero manual ops overhead Drive innovation through adoption of novel K8s features and CNCF tools, making upstream contributions as needed Design the next generation of Palantir’s infrastructure through a deep understanding of internal systems and CNCF standards What We Value Systems programming experience with strong proficiency in golang, C/C++ or equivalent</

A World-Changing Company Palantir builds the world’s leading software for data-driven decisions and operations. By bringing the right data to the people who need it, our platforms empower our partners to develop lifesaving drugs, forecast supply chain disruptions, locate missing children, and more. The Role Software Engineers at Palantir build software at scale to transform how organizations use data. Our Software Engineers are involved throughout the product lifecycle, from idea generation, design, prototyping, and production delivery. You will collaborate closely with technical and non-technical teammates to understand our customers' problems and build products that solve them. We encourage movement across teams to share context, skills, and experience, so you'll learn about many different technologies and aspects of each product. Engineers work autonomously and make decisions independently, within a community that will support and challenge you as you grow and develop, becoming a strong technical contributor and engineering leader. Our Product Development organization is made up of small teams of Software Engineers. Each team focuses on a specific aspect of a product. Our infrastructure teams are responsible for the lowest layers of our software stack, often focused on database technologies, distributed systems, large scale data systems, security, and application infrastructure. As a Software Engineer on infrastructure working on our Foundry platform, you'll contribute high-quality code to underpin Palantir Foundry and Gotham with performant, secure, and scalable building blocks, enabling products deployed to the most important institutions in the public and private sector. You'll build the foundational capabilities that power our products used by research scientists, aerospace engineers, intelligence analysts, and economic forecasters, in countries around the world. We’re hiring engineers who are passionate about solving real-world problems and empower

About the Team The Applied Engineering team works across research, engineering, product, and design to bring OpenAI’s technology to consumers and businesses. You’ll join the team responsible for running the core infrastructure that supports products like ChatGPT and the API. The systems we support include our kubernetes clusters, infrastructure deployment, our networking stack, cloud abstractions, and more. We seek to learn from deployment and distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. Safety is more important to us than unfettered growth. About the Role The cloud infrastructure team builds and maintains infrastructure abstractions allowing OpenAI to ship products quickly and scalably. This role is based in San Francisco, CA. In this role, you will: Design and build the development and production platforms that power our products, enabling reliability and security at scale Ensure our infrastructure can scale to the next order of magnitude Help create a diverse, equitable, and inclusive culture that makes all feel welcome while enabling radical candor and the challenging of group think Like all other teams, we are responsible for the reliability of the systems we build. This includes an on-call rotation to respond to critical incidents as needed. You might thrive in this role if you: Have 5+ years building core infrastructure Have experience operating orchestration systems such as Kubernetes at scale Have experience building abstractions over cloud platforms Take pride in building and operating scalable, reliable, secure systems Are comfortable with ambiguity and rapid change This role is exclusively based in our San Francisco HQ. We offer relocation assistance to new employees. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely depl

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 Data Platform team builds and operates the infrastructure responsible for all large-scale data transport and processing across the company. We own and manage core systems including Apache Kafka, HDFS, Spark, Flink, and Trino, enabling real-time ML pipelines, feed ranking, experimentation, analytics, and observability at petabyte scale. Our team deals with latency-critical workloads, high-throughput streaming, and distributed compute systems that require fault tolerance, performance, and absolute reliability. As a software engineer on the Data Platform team, you will design, build, and operate the distributed systems powering SpaceXSI's data movement and compute. You will take ownership of infrastructure components that process trillions of events daily, driving the scalability, performance, and reliability of the systems that power product and ML workloads across the company. RESPONSIBILITIES: Design and implement high-throughput, low-latency data ingestion and transport systems. Scale and optimize multi-tenant Kafka infrastructure supporting real-time workloads. Extend and tune Spark, Flink, and Trino for demanding production pipelines. Build interfaces, API

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 We’re seeking a GPU Kernel Engineer to join our team at the cutting edge of AI acceleration, where your code directly impacts the performance of state-of-the-art machine learning models. As a GPU Kernel Engineer, you'll craft the foundation that powers modern AI workloads, optimizing every microsecond of computation to enable breakthrough applications. You'll work in a fast-paced, intellectually stimulating environment where technical excellence is paramount and your contributions directly influence production systems serving millions of users across numerous products. This role offers exceptional growth potential for engineers passionate about low-level optimization and high-impact systems work. EXAMPLE INITIATIVES You'll get to work on these types of projects as part of our Model Performance team: Baseten Embeddings Inference: The fastest embeddings solution available The Baseten Inference Stack Driving model performance optimization RESPONSIBILITIES Core Engineering Responsibilities Design and implement high-performance GPU kernels for key ML operations, including matrix multiplications, attention mechanisms, and mixture-of-experts routing Write and optimize code using CUDA, PTX assembly, and architecture-specific techniques Apply advanced performance optimization methods such as memory coalescing, warp-level programming, tensor core acceleration, and compute/memory overlap Performance & Innovation Implem