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Remote Sensor Fusion Engineer Jobs (NOW HIRING)

Torc Robotics

Senior, ML Engineer - Auto Tagger

Ann Arbor, MI · On-site +1

$102K - $140K/yr

... sensor fusion, and generative simulation testing. What You'll Do: * Scenario Mining at Scale ... Guide, mentor, and elevate less-experienced engineers. Lead design reviews, establish coding ...

Stack AV

Staff ML Engineer, Dynamic World Perception

... sensor fusion is highly desirable. • Strong experience in software engineering and machine learning algorithm design. • Fluency in Python. • Experience with C++. Company : Stack AV operates in ...

New

Torc Robotics

Senior, ML Engineer - Offline Perception

$107K - $146K/yr

The Senior ML Engineer will design and implement offline perception models and algorithms, manage ... fusion modules to automatically create annotations on Cloud Services from logged sensor data ...

Skyline Scientific Inc

Senior Scientist

Dayton, OH · Remote

$85K - $116K/yr

We solve hard problems in remote sensing, AI-enhanced analytics, and sensor fusion-our work ... Our engineers don't just write code-they research, design, and deploy groundbreaking AI/ML and ...

OVA.Work

Edge AI Engineer

$134K - $177K/yr

... or sensor fusion applications. • Strong understanding of software engineering principles, debugging, and performance optimization. Preferred : • Experience with NVIDIA Jetson, Raspberry Pi ...

Ditto

$223K - $259K/yr

Whether you're in a stadium, airplane, or remote military base, Ditto's peer-to-peer sync engine ... Experience with sensor fusion and perception pipelines, including integration of LiDAR, IMU, GPS ...

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Remote Sensor Fusion Engineer information

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How much do remote sensor fusion engineer jobs pay per year?

As of Jul 15, 2026, the average yearly pay for remote sensor fusion engineer in the United States is $88,896.00, according to ZipRecruiter salary data. Most workers in this role earn between $59,500.00 and $109,500.00 per year, depending on experience, location, and employer.

What is the difference between Remote Sensor Fusion Engineer vs Remote Data Scientist?

AspectRemote Sensor Fusion EngineerRemote Data Scientist
Required CredentialsBachelor's or Master's in Electrical Engineering, Computer Science, or related fields; experience with sensor systems and fusion algorithmsBachelor's or Master's in Data Science, Statistics, or related fields; proficiency in programming and statistical analysis
Work EnvironmentDevelops algorithms for sensor data integration, often in robotics, autonomous vehicles, or aerospaceAnalyzes large datasets to extract insights, often in tech, finance, or healthcare sectors
Industry UsageUsed in industries like automotive, aerospace, defense, and roboticsCommon in tech companies, research institutions, and consulting firms

While both roles involve data analysis and programming, Remote Sensor Fusion Engineers focus on integrating sensor data for real-time applications in robotics and autonomous systems. Remote Data Scientists analyze large datasets for insights and decision-making. The roles share technical skills but differ in application and industry focus.

What are the key skills and qualifications needed to thrive as a Remote Sensor Fusion Engineer, and why are they important?

To thrive as a Remote Sensor Fusion Engineer, you need a solid background in signal processing, mathematics, and experience with sensor technologies, often supported by a degree in electrical engineering, robotics, or a related field. Familiarity with programming languages like Python or C++, sensor simulation tools, and frameworks such as ROS (Robot Operating System) is typically required. Strong problem-solving abilities, analytical thinking, and effective communication are crucial soft skills for collaborating remotely and integrating complex data sources. These skills and qualifications are essential for developing reliable sensor fusion algorithms that enable accurate perception in autonomous or remote systems.

What are some typical challenges faced by Remote Sensor Fusion Engineers when integrating data from multiple sensors?

Remote Sensor Fusion Engineers often encounter challenges such as handling data discrepancies due to varying sensor resolutions, synchronization issues caused by different sensor update rates, and managing sensor noise or data loss. Ensuring that the fused data is both reliable and processed in real-time for downstream applications can be complex, especially in distributed or remote environments. Effective collaboration with hardware engineers, software developers, and data scientists is essential to address these challenges and optimize system performance.

What does a Remote Sensor Fusion Engineer do?

A Remote Sensor Fusion Engineer is responsible for integrating and analyzing data from multiple sensors, such as cameras, radars, and lidars, to create a comprehensive and accurate understanding of an environment. This role is essential in fields like autonomous vehicles, robotics, and IoT systems, where precise situational awareness is critical. As a remote position, the engineer collaborates with cross-functional teams using digital tools to design algorithms, test sensor data integration, and improve system performance from a remote location.
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Remote Sensor Fusion Engineer jobs near you
Senior, ML Engineer - Auto Tagger

Senior, ML Engineer - Auto Tagger

Torc Robotics

Ann Arbor, MI • On-site, Remote

$102K - $140K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 26 days ago

Job description

About the Company
At Torc, we have always believed that autonomous vehicle technology will transform how we travel, move freight, and do business. A leader in autonomous driving since 2007, Torc has spent over a decade commercializing our solutions with experienced partners. Now a part of the Daimler family, we are focused solely on developing software for automated trucks to transform how the world moves freight. Join us and catapult your career with the company that helped pioneer autonomous technology, and the first AV software company with the vision to partner directly with a truck manufacturer.
Meet The Team:
The Auto Tagger team is the engine behind our data flywheel, responsible for translating petabytes of raw, multi-modal vehicle data into a highly curated library of critical driving scenarios. By mining driving logs for long-tail events, we provide the foundational data required for safe autonomous trucking. Leveraging Pegasus logical layers, this team structures and catalogs findings into an observations database that directly accelerates development across autonomous perception, sensor fusion, and generative simulation testing.
What You'll Do:
  • Scenario Mining at Scale: Architect and optimize distributed data pipelines to process massive multi-sensor logs (camera, LiDAR, radar, kinematics), automatically extracting and cataloging safety-critical and long-tail driving events.
  • Advanced Event Tagging: Develop and tune both heuristic-based and ML-assisted algorithms (including exploring Vision-Language Models or semantic vector search) to automatically classify and describe complex environmental and behavioral scenarios.
  • Standardized Data Structuring: Extract and format scenario data utilizing the Pegasus layer standard (alongside opensource frameworks) to ensure semantic consistency and rigorous metadata integrity.
  • Data Flywheel Integration: Manage the ingestion of tagged events into the observations database, enabling high-speed querying and retrieval for ML training, regression testing, and system validation.
  • Cross-Functional Alignment: Operate with broad autonomy to drive consensus across organizational boundaries. Collaborate closely with downstream consumers in perception, simulation, and systems engineering to define what constitutes an "interesting scenario" and operationalize a continuous data loop.
  • Mentorship & Team Growth: Guide, mentor, and elevate less-experienced engineers. Lead design reviews, establish coding standards, and foster a culture of technical excellence and collaborative problem-solving.

What You'll Need to Succeed:
  • BS or MS in Computer Science, Robotics, Engineering, or a STEM field, with 6+ years in data engineering, ML systems, or autonomous data curation.
  • Core Languages: Strong Python and SQL skills, with heavy experience processing massive time-series or unstructured datasets.
  • ML & Dataset Curation: Hands-on machine learning and dataset curation experience, with a demonstrated history of implementing targeted datasets that measurably improve downstream model performance.
  • Data Exploration: Hands-on experience using Databricks (or similar platforms) for large-scale analytics, interactive querying, and making massive vehicle datasets searchable.
  • Cloud & Compute: Expertise in distributed compute frameworks (Ray, Spark, Beam) and cloud platforms (AWS, GCP, or Azure) for executing heavy data workloads.
  • AV Standards: Experience parsing complex data formats and applying scenario-description standards like Pegasus layers.
  • Communication: Exceptional ability to translate complex data engineering challenges into clear strategies for cross-functional stakeholders.
  • Technical Leadership: Proven track record of mentoring teams, driving system architecture, and defining engineering roadmaps.

Bonus Points!
  • Auto-labeling & VLMs: Familiarity with foundational models, auto-labeling pipelines, or zero-shot classification for scenario extraction.
  • Model Serving: Experience with vLLM, SGLang, or similar frameworks for highly optimized, high-throughput model serving and inference
  • Semantic Inference: Experience with semantic extraction and attribute mapping to help build out a robust semantic inference engine, moving beyond standard bounding-box object detection.
  • Data Tooling: Familiarity with parsing robotics formats (ROS bags, MCAP) and optimizing high-performance columnar storage formats (Parquet, Arrow).
  • Downstream Integration: Knowledge of how scenario data feeds into generative simulation workflows, neural rendering, or sensor fusion validation.
  • Advanced Retrieval: Experience building semantic retrieval systems or vector databases for automotive data.

Perks of Being a Torc'r
Torc cares about our team members and we strive to provide benefits and resources to support their health, work/life balance, and future. Our culture is collaborative, energetic, and team focused. Torc offers:
  • A competitive compensation package that includes a bonus component and stock options
  • 100% paid medical, dental, and vision premiums for full-time employees
  • 401K plan with a 6% employer match
  • Flexibility in schedule and generous paid vacation (available immediately after start date)
  • Company-wide holiday office closures
  • AD+D and Life Insurance

At Torc, we're committed to building a diverse and inclusive workplace. We celebrate the uniqueness of our Torc'rs and do not discriminate based on race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, veteran status, or disabilities. Even if you don't meet 100% of the qualifications listed for this opportunity, we encourage you to apply.
Our compensation reflects the cost of labor across several geographic markets. Pay is based on a number of factors and may vary depending on job-related knowledge, skills, and experience. Torc's total compensation package will also include our corporate bonus and stock option plan. Dependent on the position offered, sign-on payments, relocation, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits.
Job ID: R-102717
Hiring Range for Job Opening
US Pay Range
$177,300-$212,800 USD

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