Design and optimize distributed evaluation execution engines to orchestrate large volumes of inference steps across TPU and GCU pools with high throughput and low latency.
Build foundational abstractions for evaluating complex LLM agent loops, tool use, and automated LLM-as-a-judge rating systems.
Design robust error classification, automated retry policies, and observability dashboards to maintain strict SLOs for evaluation pipeline success rates.
Partner closely with GDM research scientists and data science teams to anticipate frontier model evaluation requirements and translate them into scalable infrastructure solutions.
Mentor fellow engineers, set high standards for code quality (Python in Google3), and advocate rigorous testing and system design practices.
Requirements
Bachelor's degree in Computer Science, Software Engineering, Mathematics, or a related STEM field
Nice to have: Master's degree or PhD in Computer Science, Artificial Intelligence, Robotics, or a related technical field
Design, architect, and implement high-performance, reliable network communication transports across multiple generations of SmartNICs and hardware platforms to support demanding HPC and ML workloads.
Profile, tune, and optimize network performance end-to-end—from bare-metal hardware up to the application layer—and scale these solutions across business-critical production workloads.
Partner with cross-functional engineering teams to drive technical alignment, foster a culture of shared innovation, and deliver seamless system integrations.
Lead, mentor, and scale a high-performing engineering team, advocating career growth and fostering a positive culture where technical perspectives thrive.
Define and drive the mid-to-long-term technical roadmap for your team, translating high-level business objectives into clear execution plans while balancing technical debt with product velocity.
Requirements
Bachelor’s degree
Nice to have: Master's degree or PhD in Computer Science
Nice to have: experience in complex matrixed organization
Lead the engineering organization responsible for defining, building, and delivering complex data and AI infrastructure software.
Compensation
The target salary range for this position is 266,050 - 396,000 USD.
Responsibilities
Own end-to-end engineering delivery, from design through implementation, testing, and production reliability.
Provide deep technical leadership, design reviews, and guidance on performance, scalability, security, and system tradeoffs, including accelerated computing where relevant; partner with senior architects to turn technical direction into robust products.
Translate product priorities and customer commitments into realistic engineering plans with clear owners, milestones, dependencies, quality gates, and measurable outcomes.
Build a disciplined execution culture with high engineering velocity, transparent progress, timely decisions, and accountability for commitments.
Recruit, coach, and retain exceptional engineers and engineering leaders; define team structures, clarify decision rights, develop successors, and raise the technical bar.
Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability.
Locations (4)
McLean, Virginia, United States
Cambridge, Massachusetts, United States
New York, New York, United States
San Jose, California, United States
Compensation
Cambridge, MA: $197,300 - $225,100 for AI Engineer 4
McLean, VA: $197,300 - $225,100 for AI Engineer 4
New York, NY: $215,200 - $245,600 for AI Engineer 4
San Jose, CA: $215,200 - $245,600 for AI Engineer 4
PhD-level internship focused on generative world models, controllable simulation, and multimodal conditioning for autonomous driving technology.
Compensation
Hourly PhD Pay: $85—$85 USD
Responsibilities
Design, implement, and scale controllable generation and test-time compute algorithms, multimodal conditioning, and critic-guided flow/diffusion steering—for foundation world models.
Investigate multimodal sensor + semantic latent conditioning, and representation alignment to advance toward holistic world simulation.
Leverage learned realism critics and agentic autoresearch workflows on large-scale TPU clusters to evaluate closed-loop interactive realism, long-tail scenario synthesis, and multimodal consistency.
Write clean, modular, and well-tested JAX code in core simulation and world-modeling codebases, collaborating closely with researchers across Sim Realism, Foundation Models, and Closed-Loop Training teams.
Requirements
PhD in Computer Science
Machine Learning
Robotics
related technical field
Nice to have: First-author publications at top-tier venues (NeurIPS, ICML, ICLR, CVPR, ECCV, CoRL, RSS, ICRA)
Lead the engineering organization responsible for defining, building, and delivering complex data and AI infrastructure software.
Compensation
The target salary range for this position is 266,050 - 396,000 USD.
Responsibilities
Own end-to-end engineering delivery, from design through implementation, testing, and production reliability.
Provide deep technical leadership, design reviews, and guidance on performance, scalability, security, and system tradeoffs.
Translate product priorities and customer commitments into realistic engineering plans with clear owners, milestones, dependencies, quality gates, and measurable outcomes.
Build a disciplined execution culture with high engineering velocity, transparent progress, timely decisions, and accountability for commitments.
Recruit, coach, and retain exceptional engineers and engineering leaders; define team structures, clarify decision rights, develop successors, and raise the technical bar.
Conduct research and development in model-based haptic sensing and haptic SLAM for soft robotic systems.
Responsibilities
Conduct research and develop model-based haptic sensing and state-estimation methods for cable- or tendon-driven soft robotic systems.
Develop analytical and numerical models of soft-robot deformation, cable/tendon transmission, actuator behaviour, and robot-environment interaction.
Develop methods to infer external contact forces and interaction states from motor-side proprioceptive measurements.
Implement and evaluate soft-robot models, sensing algorithms and estimation methods using SoRoSim, MATLAB and related numerical or simulation environments.
Design, fabricate, assemble and program multi-actuator cable/tendon-driven soft robotic prototypes, including the soft robot body, cable-transmission mechanisms, HEBI Robotics actuators, sensors and control electronics.
Requirements
Bachelor's degree in Mechanical Engineering, Robotics, Mechatronics, or a related field
You will define how Crux runs its TPU fleet and build it so that AI agents, not people, do most of the operating. You will own telemetry across facilities/clusters/network, incident/change processes, and autonomous systems.
Compensation
The annual salary range for this position has been estimated based on market data and other factors. However, a salary higher or lower than this range may be appropriate for a candidate whose qualifications differ meaningfully from those listed in the job description.
Responsibilities
Own one telemetry and event pipeline across power, cooling, TPU hosts, interconnect, and the control plane
Build AI agents that triage alerts, run runbooks, drain and requeue workloads, and initiate RMAs with Google
Set SLOs and error budgets for every Crux service
Stand up 24/7 fleet operations where agents handle repeat failures and people handle novel ones
Hire and develop SRE, fleet operations, and AI tooling leaders
Requirements
Nice to have: SRE or fleet operations leadership at a hyperscaler or neocloud
Nice to have: Global NOC or data center interconnect operations across 100+ sites
Nice to have: Operating TPU or GPU clusters for large training and inference workloads
Nice to have: Patents or publications in AIOps, autonomous operations, or network automation
Lead the design and development of ML infrastructure that takes DUE models from data to training to production serving, including event detection models, triage foundation models, and agents.
Locations (3)
Mountain View, California, United States
San Francisco, California, United States
New York, New York, United States
Compensation
The expected base salary range for this full-time position across US locations is listed below... $251,000—$310,000 USD
Responsibilities
Lead the design and development of ML infrastructure that takes DUE models from data to training to production serving, including event detection models, triage foundation models, and agents.
Design and scale distributed systems for large-scale data generation, model training, and evaluation.
Position Title: Mechanical Engineer
Location: Virginia Beach, Virginia
Clearance Requirement: SECRET Clearance – TS/SCI Eligible
Status: This position is contingent upon award
Endurion is seeking a Mechanical Engineer that can integrate systems, model and create technical solutions to assist with launch and recovery of unmanned systems, and integrate operational systems and technology on to unmanned systems.
Education/Experience requirements:
B.S. in Mechanical/Robotics/Aeronautical Engineering; or applicable engineering or science field.
Minimum of 3 years of hands-on professional experience.
Extensive knowledge of aviation principles and unmanned systems (UxS). - 3 years. Extensive knowledge in electric propulsion and combustible power systems - 3 years.
Understanding of material properties (strength, weight, durability, thermal conductivity) and their impact on Unmanned Systems (UxS) performance.
Proven ability to select appropriate materials and designs structures that meet competing requirements for load-bearing capacity, vibration resistance, and environmental robustness.
Experience designing and developing launch and recovery mechanisms for manned or unmanned systems, considering factors like weight, stability, and environmental conditions.
Expertise in using computer aided design (CAD) software (SolidWorks, AutoCAD, Rhino) to model, analyze, and create technical solutions for UxS components and subsystems.
Hands-on experience designing and fabricating enclosure solutions, mechanical and electrical housings, and custom mounting brackets for UxS components.
Engineer must be comfortable working in a shop environment with loud noises and industrial power tools. May be required to lift 50 lbs.
Hands-on experience manufacturing with a CNC machine.
Proven ability to incorporate analytical considerations for thermal management, shock absorption, stress, and vibration mitigation into designs.
Proven ability to analyze complex UxS design problems, such as optimizing weight distribution for improved performance or developing innovative solutions for integrating sensitive payloads within tight space constraints.
Experience in designing and installing antenna systems for UxS, considering optimal placement, signal strength, and interference mitigation.
Understanding of electromagnetic principles and the potential impact of lightning strikes and RF interference on UxS electronics. Ability to implement design strategies (e.g.,grounding techniques, shielding) to protect sensitive components and ensure safe operation.
Hands on experience using various 3d printing technologies, such as FDM, SLS, SLA and strong understanding in selecting materiel e.g., PLA, PETG/ABS, and TPU.
This job description is intended to describe the general nature and level of work performed by employees in this position. It is not intended to be an exhaustive list of all responsibilities, duties, and skills required. Management retains the discretion to add to or modify the duties of the position at any time. Employment with Endurion is at-will, meaning that either the employee or the employer may terminate the employment relationship at any time, with or without cause or advance notice, provided it does not violate applicable law.
Endurion complies with all Equal Employment Opportunity (EEO) requirements. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other legally protected characteristic. Endurion will provide reasonable accommodations to qualified individuals with disabilities in accordance with the Americans with Disabilities Act (ADA). If you need assistance or an accommodation due to a disability, please contact us at recruiting@endurion.com.
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