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Remote Spatial Analysis Jobs in California (NOW HIRING)

Jitx Inc.

Senior Software Engineer

Berkeley, CA · On-site +1

$150K - $197K/yr

... and spatial data structures - Constraint solving and optimization Simulation Integration ... Architected to support headless and remote. We may use artificial intelligence (AI) tools to ...

Ionis

Director, Computational Biology

Carlsbad, CA · On-site +1

We continue to invest time, money and energy into making our onsite, hybrid and remote work ... omics analyses and integration (including RNA-seq, ATAC-seq - bulk, single cell - spatial ...

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All JobsSpatial Analysis JobsRemote Spatial Analysis JobsRemote Spatial Analysis Jobs in California

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:
Remote Spatial Analysis jobs near you
Senior Machine Learning Engineer, Weather & Degraded Road Surfaces

Senior Machine Learning Engineer, Weather & Degraded Road Surfaces

Waymo

Mountain View, CA • On-site, Remote

$204K - $259K/yr

Other

Posted 4 days ago

Job description

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 Driver-The World's Most Experienced Driver-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.

The DRAW team is a perception problem-domain team - our name stands for Degraded Road Surfaces and Weather. We take a high-level business problem like "waymo vehicles need to drive safely in snow" and use whatever technologies and tools we need to solve the problem at hand. Most of our work is ML-related. Recently we have been working with both large supervised multi-model models (lidar+camera+radar) as well as few-shot detection using Vision Language Models (VLMs). We work closely with perception platform teams that build infra for us as well as behavior teams that focus on changing the car's behavior in response to new outputs we produce.

Previously, our main focus was on driving in rain and dense fog. The team built Waymo's first ever ML weather estimators to determine the weather around the vehicle and set the vehicle's speed appropriately. We also developed signals to determine when our sensors are in need of cleaning. Finally, we delivered ML models that let the vehicle avoid floods and puddles. We have also worked to make the waymo ADV driver appropriately around potholes, sand, trenches, debris, etc. Our new focus area is snow - we need to build models to understand road friction, snow accumulation, tire tracks in snow, etc.

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

You will:

  • Apply machine learning techniques to build multi-modal sensor fusion architectures and spatial-temporal representation learners for object detection and tracking, occupancy and semantic segmentation, road understanding, etc.

  • Develop scalable recipes for large data, large model training running on Alphabet's compute infrastructure, create methods and recipes for pre-training and post-training.

  • Develop methods and recipes for distributed fine-tuning enabling multiple developers to simultaneously improve the model, develop methods and recipes to avoid regression against a production system.

  • Develop and maintain model evaluation recipes and metrics for measuring and improving performance of pre-trained and fine-tuned models

You have:

  • Bachelors in Computer Science or a similar discipline, or an equivalent amount of deep learning experience

  • 5+ years experience in Machine Learning and/or Computer Vision

  • Experience with Python

  • Experience with ML frameworks like PyTorch, JAX, or Tensorflow.

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
$204,000—$259,000 USD

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