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Remote Spatial Analysis Jobs in California (NOW HIRING)

The Perception team builds the system which learns the spatial-temporal representation and their ... analyze real-world behavior and develop systems for handling the complexities of interacting with ...

The Perception team builds the system which learns the spatial-temporal representation and their ... analyze real-world behavior and develop systems for handling the complexities of interacting with ...

The Perception team builds the system which learns the spatial-temporal representation and their ... analyze real-world behavior and develop systems for handling the complexities of interacting with ...

The Perception team builds the system which learns the spatial-temporal representation and their ... analyze real-world behavior and develop systems for handling the complexities of interacting with ...

Lead Engineer

San Francisco, CA ยท On-site +1

$120K - $159K/yr

Lead Engineer AI Infrastructure / Backend Engineering | USA Remote US-based candidates only|Visa ... Create data infrastructure that can be queried by AI agents for risk analysis and business ...

... the high spatial resolution and near-daily revisit of PlanetScope data. Impact You'll Own ... PhD and current Faculty/Professor status in Geospatial Analytics, Computer Science, Remote Sensing ...

Senior Software Engineer

Berkeley, CA ยท On-site +1

$150K - $250K/yr

Computational geometry and spatial data structures * Constraint solving and optimization Simulation ... Architected to support headless and remote. $150,000 - $250,000 a year We may use artificial ...

Senior Software Engineer

Berkeley, CA ยท On-site +1

$150K - $250K/yr

... and spatial data structures - Constraint solving and optimization Simulation Integration ... Architected to support headless and remote. $150,000 - $250,000 a year We may use artificial ...

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Remote Spatial Analysis information

What are the key skills and qualifications needed to thrive as a Remote Spatial Analyst, and why are they important?

To thrive as a Remote Spatial Analyst, you need a strong background in geography, GIS, remote sensing, and data analysis, often supported by a relevant degree. Proficiency with GIS software (like ArcGIS or QGIS), remote sensing platforms, and scripting languages such as Python or R is typically required. Analytical thinking, attention to detail, and effective communication are essential soft skills that set top performers apart. These competencies are critical for accurately interpreting spatial data, delivering actionable insights, and collaborating effectively with multidisciplinary teams.

What are some common challenges faced by professionals in remote spatial analysis roles, and how can they be addressed?

Remote spatial analysts often face challenges related to data accessibility, communication across distributed teams, and ensuring data security. Working with large geospatial datasets remotely can require advanced data management tools and reliable internet connections. Effective collaboration with colleagues in different locations is crucial, so leveraging cloud-based GIS platforms and regular virtual meetings can help maintain project momentum. Staying up to date with the latest remote sensing technologies and best practices also helps overcome technical obstacles and enhances productivity.

What is remote spatial analysis?

Remote spatial analysis refers to the process of examining and interpreting spatial data collected from a distance, often using technologies such as satellite imagery, aerial photography, and geographic information systems (GIS). Professionals in this field use specialized software to analyze patterns, changes, and relationships in the data to support decision-making in fields such as environmental science, urban planning, agriculture, and disaster management. Remote spatial analysis enables organizations to monitor large or inaccessible areas, identify trends, and make data-driven decisions without being physically present at the location of interest.

What is the difference between Remote Spatial Analysis vs Remote GIS Specialist?

AspectRemote Spatial AnalysisRemote GIS Specialist
CredentialsDegree in Geography, GIS, or related field; certifications like GISPSimilar credentials; often holds GIS certifications
Work EnvironmentData analysis, modeling, and interpretation primarily using GIS softwareData management, map creation, and spatial data handling
Industry UsageUsed across urban planning, environmental science, transportationCommon in government agencies, environmental firms, utilities
Search & Comparison IntentUnderstanding analysis techniques and data interpretationFocus on map creation and spatial data management

Remote Spatial Analysis involves analyzing spatial data to derive insights, often focusing on modeling and data interpretation. Remote GIS Specialist emphasizes managing spatial data, creating maps, and maintaining GIS databases. While both roles require similar credentials and work environments, their core tasks differ: analysis versus data management. Understanding these distinctions helps job seekers target the right roles in the GIS industry.

What are the most commonly searched types of Spatial Analysis jobs in California? The most popular types of Spatial Analysis jobs in California are:
What cities in California are hiring for Remote Spatial Analysis jobs? Cities in California with the most Remote Spatial Analysis job openings:
Machine Learning Engineer, Model Optimization

Machine Learning Engineer, Model Optimization

Waymo

Mountain View, CA โ€ข On-site, Remote

$170K - $216K/yr

Other

Posted 8 days ago


Job description

Machine Learning Engineer, Model Optimization

Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driverโ€”The World's Most Experienced Driverโ„ขโ€”to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states.

The Perception team builds the system which learns the spatial-temporal representation and their semantic meanings of the surrounding environment of the autonomously driving vehicle (ADV), i.e., the system that "perceives" the world around the car. We work jointly with downstream teams on the optimization and integration into the Waymo Driver. We conduct our own research to address real-world problems and collaborate with research teams at Alphabet. We have access to millions of miles of driving data from a diverse set of sensors, enabling engineers like you to (1) develop methods for efficiently and continuously learning from large scale real-world data, to (2) develop models and model training at scale, to (3) analyze real-world behavior and develop systems for handling the complexities of interacting with the real-world, and (4) optimize models for our onboard and offboard hardware.

In this hybrid role you will report to a Technical Lead Manager.

You will:

  • Optimize FLOPs utilization in model training and model inference through model architecture/ hardware co-development, optimize for a naturally sparse representation (most spatial-temporal information in self-driving is sparse).
  • Optimize model inference for different onboard and offboard (simulation) platforms.
  • Analyze and optimize real-time inference of complex model architectures with many model components as well as on the critical path within an onboard system.

You have:

  • Bachelors in Computer Science or a similar discipline, or an equivalent amount of deep learning experience
  • 3+ years experience in Machine Learning and/or Computer Vision
  • Experience with Python
  • Experience with ML frameworks like PyTorch or JAX

We prefer:

  • MS or PhD Degree in Machine Learning, Robotics, Computer Science or a similar discipline
  • Publications at top-tier conferences like CVPR, ICCV, ECCV, ICLR, ICML, ICRA, IROS, RSS, NeurIPS, AAAI, IJCV, PAMI
  • Experience with C++

The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process.

Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements.

Salary Range $170,000โ€”$216,000 USD