Designated Training Engineer Job at JLL (Aurora)

Senior AI Infrastructure Engineer - Training Platform

As a Software Engineer on the Machine Learning Infrastructure team, you will bui...

Location

United States , San Francisco; Seattle; New York

Salary:

216000.00 - 270000.00 USD / Year

Scale

Expiration Date

Until further notice

Requirements

5+ years of experience in backend or infrastructure engineering, with at least 2 years focused on orchestrating ML workloads at scale (100+ GPU nodes)
Strong programming skills in one or more languages (e.g. Python, Go, Rust, C++)
Experience with complex compute management systems that cover queueing, quotas, preemption, and gang scheduling
Experience with distributed training infrastructure, such as EFA, Infiniband, and topology-aware scheduling
Experience with distributed storage systems (e.g. Lustre, S3) as they relate to training throughput
Expert-level knowledge of Kubernetes internals (Custom Resources, Operators, Admission Controllers) and how they interact with device plugins for specialized hardware
Familiarity with cloud infrastructure (AWS, GCP) and infrastructure as code (e.g., Terraform)
Proven ability to solve complex problems and work independently in fast-moving environments

Job Responsibility

Architect and scale a multi-tenant orchestration layer that abstracts away the complexity of GPU clusters, ensuring high utilization and seamless job recovery
Design and implement scheduling primitives to optimize the lifecycle of training jobs
Develop deep observability and automated health-checking into the training stack to proactively identify and isolate hardware failures
Evaluate and integrate emerging technologies in the CNCF and AI ecosystem (e.g. Ray, Kueue), making data-driven build vs. buy decisions that balance velocity with long-term maintainability
Work closely with Finance and Procurement teams to drive our capacity planning process
Participate in our team's on call process to ensure the availability of our services
Own projects end-to-end, from requirements, scoping, design, to implementation, in a highly collaborative and cross-functional environment

What we offer

Comprehensive health, dental and vision coverage
retirement benefits
a learning and development stipend
generous PTO
commuter stipend (may be eligible)

Fulltime

Training Engineer

Unox, a market leader in the production of high-end ovens and certified as a Gre...

Location

Italy , Cadoneghe

Salary:

Not provided

UNOX

Expiration Date

Until further notice

Requirements

Bachelor’s or Master’s degree in Engineering
Excellent proficiency in English, and French or German
Willingness to travel internationally to visit subsidiaries and support partners, at least for one week per month
Entry-Level (<2 years)

Job Responsibility

Deliver continuous technical training, both remotely and in-person, to the network of technical support partners
Promote and maintain best practices related to the Service Academy
Oversee the training of Unox SpA internal and branch personnel, ensuring alignment with corporate standards
Create technical documentation and training materials for Unox products
Collaborate with design teams during product development, identifying key issues and proposing innovative solutions

What we offer

Flexible Working Hours
Work-Life balance initiatives
Paid time off & overtime
Company canteen
Personal and family welfare
Health insurance & welfare programs
Pension & retirement plans
Mentorship & coaching
Career growth & training programs
Diversity & inclusion policies

Fulltime

ML Engineer, Training Infrastructure

You’ll take on challenging engineering tasks crucial to the development of tabul...

Location

Germany; United States , Berlin; Freiburg; New York; San Francisco

Salary:

Not provided

Prior Labs

Expiration Date

Until further notice

Requirements

Exceptional software engineering fundamentals and expert-level Python proficiency, with 5+ years of hands-on industry experience building and operating production systems
Proven track record of designing and building complex, scalable software, preferably for data processing or distributed systems
Deep, practical knowledge of the modern ML ecosystem (PyTorch, scikit-learn, etc.) and a genuine interest in applying systems thinking to solve hard problems in AI
Core MLOps Concepts: Strong understanding of the entire machine learning lifecycle (MLLC) from data ingestion and preparation to model deployment, monitoring, and retraining. Familiarity with MLOps principles and best practices (e.g., reproducibility, versioning, automation, continuous integration/delivery for ML)

Job Responsibility

Training & research compute infrastructure: Own our cloud GPU cluster (operations, reliability, and cost/performance) currently based on Slurm. Design and implement future versions as our compute needs scale and we expand across multiple cloud/HPC providers
Training & inference performance: Work closely with researchers to identify and resolve performance bottlenecks in distributed training and inference. Support high hardware utilization and efficient memory usage through systems-level debugging, profiling, and infrastructure improvements
Developer productivity: Manage our internal repositories on GitHub and keep their CI and other pipelines speedy. Ensure our experiment tracking, model registry, data processing pipelines are working smoothly
Try out your own ideas! We operate an open environment. If you’ve got the next SOTA tabular architecture up your sleeve, go ahead and train it

What we offer

Competitive compensation package with meaningful equity
30 days of paid vacation + public holidays
Comprehensive benefits including healthcare, transportation, and fitness
Work with state-of-the-art ML architecture, substantial compute resources and with a world-class team

Fulltime

Member of Technical Staff - Distributed Training Engineer

Our Training Infrastructure team is building the distributed systems that power ...

Location

United States , San Francisco; Boston

Salary:

Not provided

Liquid AI

Expiration Date

Until further notice

Requirements

Hands-on experience building distributed training infrastructure (PyTorch Distributed DDP/FSDP, DeepSpeed ZeRO, Megatron-LM TP/PP)
Experience diagnosing performance bottlenecks and failure modes (profiling, NCCL/collectives issues, hangs, OOMs, stragglers)
Understanding of hardware accelerators and networking topologies
Experience optimizing data pipelines for ML workloads

Job Responsibility

Design and build core systems that make large training runs fast and reliable
Build scalable distributed training infrastructure for GPU clusters
Implement and tune parallelism/sharding strategies for evolving architectures
Optimize distributed efficiency (topology-aware collectives, comm/compute overlap, straggler mitigation)
Build data loading systems that eliminate I/O bottlenecks for multimodal datasets
Develop checkpointing mechanisms balancing memory constraints with recovery needs
Create monitoring, profiling, and debugging tools for training stability and performance

What we offer

Competitive base salary with equity in a unicorn-stage company
We pay 100% of medical, dental, and vision premiums for employees and dependents
401(k) matching up to 4% of base pay
Unlimited PTO plus company-wide Refill Days throughout the year

Fulltime

Training engineer

Designated Training Engineers (DTE) are the professionals who train the engineer...

Location

United States , Carlstadt

Salary:

105000.00 - 140000.00 USD / Year

JLL

Expiration Date

Until further notice

Requirements

Must have hands-on experience in a data center/critical facility, including UPS Systems, emergency generators, and switch-gear
High School diploma or GED equivalent
Operating Engineers license (SMA) or equivalent
Proficiency with computer applications including Microsoft Word, PowerPoint and Excel.
Demonstrated excellent verbal and written communication skills with prior instructor experience preferred.
Proven record of excellent internal and external customer service as well as leadership ability, among engineering peers.
Candidates must be authorized to work in the United States without sponsorship.

Job Responsibility

Designated Training Engineers (DTE) are the professionals who train the engineering team on equipment and operation in the facility.
DTE’s are responsible for assisting, reviewing and developing a format which will educate the engineering personnel.
DTE’s are responsible for maintaining complete and meticulous training records of all engineers.
The DTE is expected to provide skilled leadership and technical expertise in support of the Chief Engineer for all training related issues, writing and/or editing Method of Procedures (MOPs) and Standard & Emergency Operating Procedures (SOP / EOP), as well as incident investigations.
Performing as required: Installation, repair, and maintenance of electrical, mechanical, and plumbing/piping equipment, machinery and controls located in the interior and exterior of building.
Monitors operations and conducts a routine and on-going assessment of the building systems operations and performance.
Performs tests, rounds and analyzes data to ensure the proper functioning of departmental equipment.
Performing as required at the direction of supervisor, maintaining, monitoring, and performing preventive maintenance and continuous operation of all building systems including: fire/life safety, mechanical (HVAC, plumbing, controls) electrical (lighting, UPS, PDU, generators, primary switch gear), emergency backup systems and hot water systems
monitors operation, adjusts, and maintains refrigeration, chilled water, and air conditioning equipment
boilers, and ventilating and hot water heaters

What we offer

401(k) plan with matching company contributions
Comprehensive Medical, Dental & Vision Care
Paid parental leave at 100% of salary
Paid Time Off and Company Holidays
Early access to earned wages through Daily Pay

Fulltime

Advanced Training Engineer – APIs & Industrial Interfaces

In the Customer Success field, you're the bridge between technology and people. ...

Location

Germany , Metzingen

Salary:

Not provided

Neura Robotics GmbH

Expiration Date

Until further notice

Requirements

Completed studies in Engineering, Computer Science, Automation, or related fields
Solid knowledge of industrial communication protocols, such as Modbus TCP, Profinet, OPCUA, Ethernet/IP, and EtherCAT
Strong programming experience in Python, C++
Practical experience with API development, integration, or system communication
Understanding of network communication, diagnostics, and troubleshooting
Ability to explain complex technical topics clearly and logically
Strong presentation skills and confidence in delivering interactive and engaging sessions
A structured, solution-oriented mindset with a passion for supporting learners during hands-on sessions
Fluent in English and German

Job Responsibility

Preparing and delivering advanced training sessions on API usage, software interfaces, and system communication workflows
Creating hands-on use cases, exercises, and training documentation for industrial communication interfaces such as Modbus TCP, Profinet, OPCUA, Ethernet/IP, and TCP/UDP
Designing, developing, and maintaining advanced demo applications using our APIs (Python, C++) and PLCs
Ensuring seamless robot integration into industrial environments through testing, validation, and communication troubleshooting
Collaborating closely with Development and Software teams to stay aligned with new features and system updates
Translating complex technical concepts into clear, structured, and engaging explanations for customers and internal teams
Developing presentations, documents, and course materials according to Academy standards

What we offer

Dynamic, self-reliant work culture with flat hierarchies
Flexible hours
30 vacation days
Competitive salary package
Exclusive employee discounts
Team events (e.g., summer party, company town hall meetings)
Support for personal and professional development

Research Scientist / Engineer – Training Infrastructure

Luma’s mission is to build multimodal AI to expand human imagination and capabil...

Location

United States , Palo Alto

Salary:

187500.00 - 395000.00 USD / Year

Luma AI

Expiration Date

Until further notice

Requirements

Extensive experience with distributed PyTorch training and parallelisms in foundation model training
Deep understanding of GPU clusters, networking, and storage systems
Familiarity with communication libraries (NCCL, MPI) and distributed system optimization

Job Responsibility

Design, implement, and optimize efficient distributed training systems for models with thousands of GPUs
Research and implement advanced parallelization techniques (FSDP, Tensor Parallel, Pipeline Parallel, Expert Parallel)
Build monitoring, visualization, and debugging tools for large-scale training runs
Optimize training stability, convergence, and resource utilization across massive clusters

Fulltime

Staff Machine Learning Engineer - ML Training Infrastructure

The Role:   We are seeking an experienced, technically strong, impact-driven ex...

Location

United States , Austin; Mountain View

Salary:

185000.00 - 335300.00 USD / Year

General Motors

Expiration Date

Until further notice

Requirements

Bachelor's degree or higher in Computer Science or a related field, or equivalent practical experience
8+ years of professional software engineering experience
5+ years of specialized experience in AI/ML infrastructure, such as enabling distributed training for large-scale ML models
Strong programming skills in Python, with deep proficiency in frameworks such as PyTorch (preferred), TensorFlow, or similar ML systems
Proven experience designing and operating distributed systems for ML training, including distributed computing, GPU computing, and cloud environments (AWS, GCP, Azure)
Demonstrated track record of leading technically ambiguous, cross-team infrastructure initiatives and driving them to measurable impact
Strong architectural judgment and ability to make sound technical tradeoffs across performance, reliability, usability, and cost
Willingness to travel to Sunnyvale, CA as needed
Comfortable operating in highly ambiguous and dynamic environments

Job Responsibility

Define and drive the architecture, design, and development of scalable, reliable, and high-performance ML frameworks and platform capabilities to support model training at scale
Lead model training performance analysis and optimization efforts across distributed training workflows, improving scalability, efficiency, and cost across heterogeneous hardware environments
Raise the bar on system observability, debuggability, operational excellence, and developer experience across the ML training stack
Own large, ambiguous, cross-functional technical initiatives from strategy through execution, including technical roadmap definition, tradeoff analysis, and delivery
Influence platform direction by identifying long-term infrastructure investments, setting engineering standards, and driving adoption of best practices across teams
Collaborate across organizational boundaries to align requirements, resolve technical disagreements, and integrate new capabilities into the platform ecosystem
Mentor engineers through design reviews, technical guidance, and hands-on partnership, while elevating engineering quality across the team

What we offer

medical
dental
vision
Health Savings Account
Flexible Spending Accounts
retirement savings plan
sickness and accident benefits
life insurance
paid vacation & holidays
tuition assistance programs

Fulltime

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Designated Training Engineer

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