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Slam Operator Jobs (NOW HIRING)

AEVEX

Robotics Engineering Co-op

Tampa, FL

... operating in complex, GPS-degraded, and GPS-denied environments. We are seeking a highly motivated ... Develop and implement computer vision-based localization, SLAM, or deep learning models for real ...

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Slam Operator information

What does slam mean at Amazon?

At Amazon, a slam refers to a performance metric used in warehouse operations to measure the speed and efficiency of order picking and packing. It often relates to meeting or exceeding productivity targets within a set time frame, and employees may be monitored using handheld devices or scanners to track their progress.

What is the difference between Slam Operator vs Crane Operator?

AspectSlam OperatorCrane Operator
CertificationsOSHA certification, specialized trainingOSHA certification, crane operation license
Work EnvironmentConstruction sites, industrial facilitiesConstruction sites, shipping yards, industrial plants
Industry UsageMaterial handling, demolition, constructionHeavy lifting, lifting equipment operation
Job FocusOperating slam hammers or compactorsOperating cranes for lifting and moving heavy loads

While both Slam Operators and Crane Operators work in construction and industrial environments, Slam Operators primarily handle equipment like slam hammers and compactors, focusing on material compaction. Crane Operators specialize in operating cranes for lifting and moving heavy materials. Both roles require OSHA certification, but their equipment and specific tasks differ significantly.

What is the highest paying position at Amazon warehouse?

At Amazon warehouses, the highest paying positions are typically managerial roles such as Area Manager or Operations Manager, which can earn significantly higher salaries than entry-level roles like Slam Operator. These positions often require leadership skills, experience, and sometimes specialized certifications, and they oversee warehouse operations and staff management.

What's the hardest job at Amazon?

The hardest job at Amazon often involves roles like warehouse associate or fulfillment center worker, which require physical stamina, repetitive tasks, and working in fast-paced environments. These positions can be physically demanding and may involve shift work, including nights and weekends.

What are Slam Operators and what do they do?

Slam Operators are professionals responsible for operating machines or systems that move, sort, or process packages in warehouses or distribution centers. Their main duties include monitoring automated equipment, ensuring packages are correctly labeled and routed, troubleshooting minor machine issues, and maintaining a safe work environment. They play a crucial role in the efficiency of logistics operations, helping to ensure that goods reach their destinations quickly and accurately. Attention to detail and adherence to safety protocols are important in this role.

What are the key skills and qualifications needed to thrive as a Slam Operator, and why are they important?

To thrive as a Slam Operator, you need a solid understanding of warehouse logistics, equipment operation, and inventory control, often requiring a high school diploma or equivalent. Familiarity with warehouse management systems (WMS), barcode scanners, and material handling tools is typically necessary. Attention to detail, reliability, and strong teamwork skills help ensure efficient and accurate operations. These abilities are crucial for maintaining smooth workflow, minimizing errors, and supporting overall warehouse productivity.

Does Amazon pay $20 an hour?

Slam operators at Amazon, such as those working in fulfillment centers, typically earn around the minimum wage or slightly above, with pay rates varying by location and experience. As of recent data, starting wages are often between $15 and $18 per hour, with some roles offering higher pay for experienced workers or those with specialized skills. Earning $20 an hour may be possible with overtime, bonuses, or in certain regions where wages are higher.

What are some common challenges faced by Slam Operators, and how can they be addressed in the workplace?

Slam Operators often encounter challenges such as managing repetitive tasks, adhering to strict safety protocols, and handling the physical demands of the job. To address these, many workplaces provide ergonomic training, rotate tasks to reduce fatigue, and foster a strong safety culture through regular briefings. Collaboration with supervisors and maintenance teams is also crucial to ensure that equipment runs smoothly and any issues are quickly resolved, helping to maintain both productivity and safety on the floor.
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Slam Operator jobs near you
System Software Engineer - GPU & Accelerated Compute

System Software Engineer - GPU & Accelerated Compute

Sunday Inc

Redwood City, CA • On-site

$211K - $251K/yr

Full-time

Posted 21 days ago

Job description

Join Us in Building the Future of Home Robotics
At Sunday, we're developing personal robots to reclaim the hours lost to repetitive tasks. We're focused on an ambitious goal to make generalized robots broadly accessible, enabling households to take back quality time.
We have spent the last 18 months building a talented team, securing capital, and validating our technology. We are now seeking passionate individuals to join us in the next phase of our growth. If you are ready to apply your skills to the forefront of robotics innovation, we'd love to hear from you.
What to Expect
The ML & Robotics Infra team builds the foundational systems that every part of our robot perception, ML, controls and behavior runs on, and the developer infrastructure that lets us build, ship, and update that software quickly and safely on every robot in the fleet.
As a System Software Engineer on ML & Robotics Infra focused on GPU and accelerated compute, you'll own how every accelerated workload on the robot from model inference, SLAM/perception, and more gets data, gets scheduled and runs efficiently on shared compute. You'll work alongside teammates who own the runtime and our build and delivery infrastructure, and you'll partner cross-functionally with ML, SLAM/Perception, Controls and Hardware teams to ensure the GPU is a first-class, well-utilized resource that meets the latency and throughput requirements of a real-time robotic system operating in the home.
What You'll Do
You'll own and contribute to the accelerated compute layer of the ML & Robotics Infra, including:
  • Efficient model execution and switching: Reduce gpu kernel launch overheads and make swapping between models on the same device fast and predictable
  • GPU scheduling and time-slicing: Arbitrate GPU access across concurrent users (model inference, SLAM, and other robotics applications) with predictable latency
  • Camera pipeline: Drive low-latency transfer of camera frames into GPU memory, integrating with HW accelerate encode/decode (NVDEC/NVENC) where appropriate
  • CPU ↔ GPU data transfer: Build efficient, low-overhead data movement between host and device, including pinned memory, zero-copy paths, and asynchronous transfer patterns
  • CPU/GPU synchronization: Design synchronization primitives and patterns that minimize stalls and keep inference pipelines full

What You'll Bring
  • 2+ years of experience developing gpu systems software
  • Strong proficiency in CUDA and a systems language such as C++, C, or Rust
  • Solid understanding of GPU architecture, GPU workloads, and the tradeoffs involved in time-slicing and sharing the device across users
  • Hands-on experience with the CUDA ecosystem: CUDA runtime API, CUDA Graphs, and CUDA IPC
  • Familiarity with GPU sharing mechanisms such as MPS and MIG
  • Experience with GPU profiling tools such as Nsight Systems and Nsight Compute
  • Solid Linux fundamentals: scheduling, IPC, memory management, and performance tuning

Nice to Have
  • Contributions to CUDA libraries or other GPU programming libraries
  • Experience with camera pipeline integration and NVDEC/NVENC
  • Experience optimizing model inference on embedded GPU platforms (e.g., Jetson)
  • Experience with observability and tracing for GPU-accelerated workloads

At Sunday Robotics, we're building technology shaped by real people - curious, creative, and diverse. We're proud to be an equal opportunity employer and consider all qualified applicants regardless of race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.
Even if you don't meet every single requirement, we encourage you to apply. Studies show that women and underrepresented groups often hold back unless they meet 100% of the criteria - we don't want that to be the reason we miss out on great talent.

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