Working hands-on with MEP systems, you'll tackle maintenance, operations, and repairs, ensuring peak performance and reliability.

Expect to troubleshoot complex issues, streamline processes, and collaborate with teams to keep our infrastructure running smoothly, directly supporting xAI's mission to accelerate human scientific discovery through AI.

Key responsibilities include:

• Independently operating and maintaining critical mechanical, electrical, and plumbing (MEP) systems in supercomputing data centers
• Performing advanced maintenance and troubleshooting of critical data center systems like HVAC, power, and environmental controls
• Overseeing the maintenance and optimization of critical data center infrastructure, including power, cooling, and environmental systems
• Ensuring MEP Infrastructure site safety and environmental compliance
• Providing operational expertise for Mechanical, Electrical, and Plumbing (MEP) systems at the datacenter facility

Requirements include:

• Bachelor's Degree in Mechanical or Electrical or 6+ years of hands-on operations/facilities work experience in lieu of degree
• Knowledge of mechanical or electrical engineering principles and systems
• Experience and knowledge of all critical systems documentation including Plans, Procedures, and Operations Manuals
• Strong troubleshooting skills
• Experience with PLC-based control systems and/or with Building Management Systems (Client)

Physical Requirements:

• Ability to lift up to 50 lbs.
• Ability to utilize hand tools and power tools as needed
• Work is often performed in tight quarters, and physical dexterity is necessary to perform job functions
• Ability to lift up to 35 lbs. unassisted
• Comfortable working at elevated heights (up to 100 feet) with appropriate safety gear
• Comfortable working in extreme outdoor environments,heat, cold, rain, etc.
• Comfortable working in an environment requiring exposure to fumes, odors, and noise

XML job scraping automation by YubHub

Your work will touch the full GenAI inference stack , from kernels and runtimes to orchestration and memory management. You will contribute to the design and implementation of the inference engine, and collaborate on model-serving stack optimized for large-scale LLMs inference.

Key responsibilities include:

• Collaborating with researchers to bring new model architectures or features (sparsity, activation compression, mixture-of-experts) into the engine
• Optimizing for latency, throughput, memory efficiency, and hardware utilization across GPUs, and accelerators
• Building and maintaining instrumentation, profiling, and tracing tooling to uncover bottlenecks and guide optimizations
• Developing and enhancing scalable routing, batching, scheduling, memory management, and dynamic loading mechanisms for inference workloads
• Supporting reliability, reproducibility, and fault tolerance in the inference pipelines, including A/B launches, rollback, and model versioning
• Integrating with federated, distributed inference infrastructure – orchestrate across nodes, balance load, handle communication overhead
• Collaborating cross-functionally: with platform engineers, cloud infrastructure, and security/compliance teams
• Documenting and sharing learnings, contributing to internal best practices and open-source efforts when possible

Requirements include:

• BS/MS/PhD in Computer Science, or a related field
• Strong software engineering background (3+ years or equivalent) in performance-critical systems
• Solid understanding of ML inference internals: attention, MLPs, recurrent modules, quantization, sparse operations, etc.
• Hands-on experience with CUDA, GPU programming, and key libraries (cuBLAS, cuDNN, NCCL, etc.)
• Comfortable designing and operating distributed systems, including RPC frameworks, queuing, RPC batching, sharding, memory partitioning
• Demonstrated ability to uncover and solve performance bottlenecks across layers (kernel, memory, networking, scheduler)
• Experience building instrumentation, tracing, and profiling tools for ML models
• Ability to work closely with ML researchers, translate novel model ideas into production systems
• Ownership mindset and eagerness to dive deep into complex system challenges
• Bonus: published research or open-source contributions in ML systems, inference optimization, or model serving

XML job scraping automation by YubHub

As a Sr. Facilities Operations Technician at xAI, you'll dive in, operating and maintaining the critical facility systems that power our supercomputing data centers.

Working hands-on with MEP systems, you’ll tackle maintenance, operations, and repairs, ensuring peak performance and reliability. Expect to troubleshoot complex issues, streamline processes, and collaborate with teams to keep our infrastructure running smoothly, directly supporting xAI’s mission to accelerate human scientific discovery through AI.

Responsibilities

• Independently operate and maintain critical mechanical, electrical, and plumbing (MEP) systems in supercomputing data centers, ensuring high reliability and performance through hands-on maintenance, troubleshooting, and process optimization.

• Perform advanced maintenance and troubleshooting of critical data center systems like HVAC, power, and environmental controls, while mentoring junior technicians to ensure operational reliability.

• Oversee the maintenance and optimization of critical data center infrastructure, including power, cooling, and environmental systems, while leading a team of technicians to ensure operational reliability and efficiency.

• Responsible for MEP Infrastructure site safety and environmental compliance, ensuring the sites align with all local and regional health and safety requirements.

• Provide operational expertise for Mechanical, Electrical, and Plumbing (MEP) systems at the datacenter facility. The systems and equipment can include pumps, piping, chillers, cooling towers, CRAH units, wiring, lighting systems, generators, motors, water supply, UPS and switchgear, etc.

• Routinely inspect all areas to ensure performance measures are being maintained and proactively self-report the problems of facilities.

• Experience with writing and executing MOPs, SOPs, EOPs.

• Perform daily inspections of critical systems.

• Identify and maintain spare parts inventory to minimize downtime.

• Coordinate and supervise scheduled system shutdowns.

• Develop and implement energy monitoring metrics.

• Support commissioning efforts by witnessing equipment startup, assisting with functional testing, and monitoring construction progress.

Basic Qualifications

• Bachelor’s Degree in Mechanical or Electrical or 6+ years of hands-on operations/facilities work experience in lieu of degree (data center experience preferred).

• Knowledge of mechanical or electrical engineering principles and systems (both would be a huge plus).

• Experience and knowledge of all critical systems documentation including Plans, Procedures, and Operations Manuals.

• Experience and knowledge of Building and Electrical Power Monitoring Systems and Operations.

• Strong troubleshooting skills.

• Experience with PLC-based control systems and/or with Building Management Systems (Client).

• Excellent written and verbal communication and technical writing skills in English.

Physical Requirements

• Ability to lift up to 50 lbs.

• Ability to utilize hand tools and power tools as needed.

• Work is often performed in tight quarters, and physical dexterity is necessary to perform job functions.

• Ability to lift up to 35 lbs. unassisted.

• Comfortable working at elevated heights (up to 100 feet) with appropriate safety gear.

• Comfortable working in extreme outdoor environments,heat, cold, rain, etc.

• Comfortable working in an environment requiring exposure to fumes, odors, and noise.

• Available to work flexible shifts providing 24x7 coverage as needed, including evenings, weekends, and holidays.

• Position is subject to pre-employment drug and random drug and alcohol testing.

• Position is subject to pre-employment and annual post-employment background checks.

• Willing to travel as needed (up to 10%).

• Valid driver’s license.

XML job scraping automation by YubHub

As a senior individual contributor, you'll be accountable for the technical decisions that ripple across the team and beyond. You'll architect the systems, tooling, and evaluation infrastructure that determine how quickly our research can move.

Responsibilities:

• Set technical direction for evaluation systems, research infrastructure, and internal tooling across the Claude Code team

• Architect eval frameworks that measure model capabilities across diverse coding tasks and scale with our research roadmap

• Lead the design of infrastructure that enables researchers to run experiments at scale, and make the foundational tradeoffs that shape how the team operates for years

• Identify the highest-leverage engineering investments,often before anyone has asked for them,and drive them to completion

• Serve as a senior technical bridge between product and research, using strong product intuition to influence which capabilities we prioritize and how we measure progress against them

• Mentor and raise the bar for other engineers on the team; review designs, unblock peers, and model the engineering standards we want to scale

• Partner with research leads to translate ambiguous research questions into durable engineering solutions

• Own critical systems end-to-end, from architecture through production reliability, and take responsibility for their long-term health

If you have 10+ years of software engineering experience, with a track record of operating as a Staff or Principal engineer (or equivalent) at a high-caliber organization, you may be a good fit for this role.

Strong candidates may also have experience with designing or scaling eval/evaluation frameworks for ML systems, reinforcement learning infrastructure or training systems, leading technical initiatives in high-performance, demanding environments, research computing, scientific infrastructure, or developer platforms at scale, a strong quantitative foundation (math, physics, or related fields), and expertise in Python and TypeScript.

The annual compensation range for this role is $405,000-$485,000 USD.

XML job scraping automation by YubHub

This role sits at the intersection of AI/ML, autonomy, model lifecycle, infrastructure, and product strategy. The PM partners closely with engineering, AI research, Hivemind Solutions, and field teams to deliver the tooling that enables sovereign autonomy, AI Factories at the edge, and continuous learning,capabilities that are central to Shield AI's strategic direction.

This is a high-impact role for an experienced product leader excited to define how foundation models are trained, validated, governed, and deployed across thousands of autonomous systems in highly contested environments.

Responsibilities:

• AI Model Development & Training Platform

Own the roadmap for foundation model training workflows, including dataset ingestion, curation, labeling, synthetic data generation, domain model training, and distillation pipelines. Define requirements for world models, robotics models, and VLA-based training, evaluation, and specialization. Lead the evolution of MLOps capabilities in Forge, including data lineage, experiment tracking, model versioning, and scalable evaluation suites.

• Data, Simulation & Synthetic Data Factory

Define product requirements for synthetic data generation, simulation-integrated data flywheels, and automated scenario generation. Partner with Digital Twin, Simulation, and autonomy teams to convert natural-language mission inputs into data needs, training procedures, and model variants.

• Safe Deployment & Model Governance

Lead the development of model governance and auditability tooling, including model cards, dataset rights, lineage tracking, safety gates, and compliance evidence. Build guardrails and workflows to safely deploy models onto edge hardware in disconnected, GPS- or comms-denied environments. Partner with Safety, Certification, Cyber, and Engineering teams to ensure traceability and evaluation pipelines meet operational and accreditation requirements.

• Edge Deployment & AI Factory Integration

Partner with Pilot, EdgeOS, and hardware teams to integrate foundation-model-based perception and reasoning into autonomy behaviors. Define requirements for distillation, quantization, and inference tooling as part of the “three-computer” development and deployment model. Ensure closed-loop workflows between cloud model training and edge-native execution.

• Cross-Functional Leadership

Collaborate with Engineering, Research, Product, Customer Engagement, and Solutions teams to ensure model outputs meet mission and platform constraints. Translate advanced AI capabilities into intuitive workflows that platform OEMs and partner nations can use to build sovereign AI factories. Sequence foundational capabilities that unblock autonomy, simulation, and customer-facing product teams.

• User & Customer Impact

Develop deep empathy for ML engineers, autonomy developers, and Solutions engineers who rely on the platform. Capture operational data gaps, mission-driven model needs, and domain-specific specialization requirements. Lead demos and onboarding for model-development capabilities across internal and external teams.

XML job scraping automation by YubHub

[2026] Senior Machine Learning Engineer, Engine Optimization - PhD Early Career

San Mateo, CA, United StatesEarly CareerID: 5626

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators.

At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device.We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there.

A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone.

Our engine’s resource management and streaming systems are critical to delivering a smooth, stable, and responsive experience for Roblox users across a huge range of devices and network conditions. These systems work together to intelligently allocate compute, memory, bandwidth, and rendering quality while dynamically delivering world content in real time as players move, explore, and interact. The challenges span highly dynamic environments, unpredictable user behavior, and opaque signals from device and OS constraints.

This role offers a rare opportunity to pioneer the application of machine learning in real-time engine optimization. You will establish the ML framework for predictive resource allocation and content fetching, replacing heuristic-based logic with adaptive, data-driven decision-making. Your work will directly shape stability, visual quality, responsiveness, and content delivery across billions of global play sessions.

You Will

• Analyze massive-scale engine performance, streaming patterns, and user behavior telemetry to uncover optimization opportunities and guide the long-term ML roadmap.
• Design ML models that infer player and interaction patterns for predictive resource management and content delivery.
• Build adaptive control systems that translate ML outputs into real-time adjustments of fidelity and system decisions, ensuring high-quality experiences without compromising stability or latency.
• Collaborate with core engine and performance engineering teams to integrate ML solutions directly into the critical path of gameplay across multiple platforms.
• Define the architectural strategy for deploying and scaling ML across resource management and streaming components at massive global scale.

You Have

• Strong expertise in applied ML—such as reinforcement learning for control, predictive modeling (especially time-series and intent inference), trajectory prediction, or real-time optimization.
• Proficiency in C++, Python, Go, Java, or similar languages, with experience deploying ML models in performance-critical systems.
• A solid understanding of systems-level concepts (memory management, threading, OS signals) or a deep interest in learning them.
• A track record of solving complex optimization problems or integrating ML into real-time systems, ideally in gaming, simulation, robotics, or mobile environments

Benefits

As a full-time employee at Roblox, you will be eligible for equity compensation and benefits as described on this page.

Salary

The starting base pay for this position is as shown below. The actual base pay is dependent upon a variety of job-related factors such as professional background, training, work experience, location, business needs and market demand. Therefore, in some circumstances, the actual salary could fall outside of this expected range. This pay range is subject to change and may be modified in the future.

Annual Salary Range

$195,780—$242,100 USD

Work Schedule

Roles that are based in an office are onsite Tuesday, Wednesday, and Thursday, with optional presence on Monday and Friday (unless otherwise noted).

XML job scraping automation by YubHub