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Sensor Fusion Jobs in California (NOW HIRING)

Rivet Industries

ML Researcher

San Jose, CA · On-site

$150K - $290K/yr

Sensor Fusion & Pose Estimation: Research background in multi-sensor data fusion, tracking, or SLAM * Model Optimization: Experience optimizing ML models for mobile/embedded deployment Foundational ...

Archer

Computer Vision Engineer

San Jose, CA · On-site

$140K - $260K/yr

Perform sensor calibration and multi-sensor fusion across camera, lidar, and radar * Optimize perception algorithms for real-time performance on embedded compute * Analyze test data to characterize ...

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How much do sensor fusion jobs pay per hour?

As of Aug 16, 2026, the average hourly pay for sensor fusion in California is $29.34, according to ZipRecruiter salary data. Most workers in this role earn between $23.70 and $33.94 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a sensor fusion engineer, and why are they important?

To thrive as a Sensor Fusion Engineer, you need a strong background in mathematics, signal processing, and computer science, typically supported by a degree in engineering or a related field. Experience with tools like MATLAB, Python, C++, and frameworks such as ROS, as well as knowledge of sensor technologies (e.g., LiDAR, radar, IMU), is essential. Strong problem-solving, collaboration, and communication skills help you integrate and interpret data from diverse sensors and work effectively within multidisciplinary teams. These abilities are critical for developing reliable systems that accurately perceive and interpret complex real-world environments.

What is the difference between Sensor Fusion vs Sensor Data Analyst?

AspectSensor FusionSensor Data Analyst
Required CredentialsBachelor's or higher in engineering, computer science, or related fields; knowledge of algorithms and programmingBachelor's or higher in data analysis, statistics, or related fields; proficiency in data tools and visualization
Work EnvironmentResearch labs, tech companies, automotive, aerospace industriesData analysis firms, research institutions, tech companies
Industry UsageDeveloping integrated sensor systems for autonomous vehicles, robotics, aerospaceInterpreting sensor data for insights, reporting, and decision-making

Sensor Fusion involves integrating data from multiple sensors to create comprehensive information, often requiring advanced algorithms and programming skills. Sensor Data Analysts focus on examining sensor data to extract insights, using statistical tools and visualization. While both roles work with sensor data, Sensor Fusion is more technical and algorithm-driven, whereas Sensor Data Analysts emphasize data interpretation and reporting.

What is sensor fusion and what does a sensor fusion engineer do?

Sensor fusion is the process of integrating data from multiple sensors to produce more accurate, reliable, and comprehensive information than would be possible using a single sensor. Professionals in this field design algorithms and systems that combine inputs from sources like cameras, lidar, radar, and inertial sensors to enhance perception and decision-making, especially in applications like autonomous vehicles, robotics, and IoT devices. Their work ensures that sensor data is interpreted in a way that improves overall system performance and safety.

How does a sensor fusion engineer typically collaborate with hardware and software teams during a project?

Sensor Fusion engineers work closely with both hardware and software teams to ensure the seamless integration of multiple sensor data streams. They often participate in cross-functional meetings to align on sensor specifications, data formats, and system constraints. Regular coordination is required to troubleshoot integration challenges and optimize algorithms for real-time performance, making strong communication and teamwork skills essential for success in this role.

What are popular job titles related to Sensor Fusion jobs in California?

For Sensor Fusion jobs in California, the most frequently searched job titles are:

What job categories do people searching Sensor Fusion jobs in California look for?

The top searched job categories for Sensor Fusion jobs in California are:

What cities in California are hiring for Sensor Fusion jobs?

Cities in California with the most Sensor Fusion job openings:

Sensor Fusion jobs near you
Infographic showing various Sensor Fusion job openings in California as of August 2026, with employment types broken down into 73% Full Time, 7% Part Time, 2% Temporary, and 18% Contract. Highlights an 92% Physical, 2% Hybrid, and 6% Remote job distribution, with an average salary of $61,019 per year, or $29.3 per hour.

Business Development Manager - Physical AI

Altera

San Jose, CA

Full-time

Posted 26 days ago

Job description

Job Details:Job Description:

We are seeking a Business Development Manager to drive growth in FPGA-based solutions across the Physical AI domain - spanning robotics, autonomous systems, industrial and factory automation, and edge AI. This role focuses on expanding design wins across intelligent machines that sense, decide, and act in the physical world, from collaborative robots and autonomous platforms to factory-automation controllers and edge AI appliances. You will act as the bridge between customers, product management, engineering, and ecosystem partners to position FPGA solutions against competing architectures including ASSPs/SoCs, GPUs, and microcontroller-based platforms.

Physical AI is converging perception, decision, and actuation onto real-time machines while pushing more intelligence to the edge, and industrial automation is moving toward connected, software-defined, and AI-enabled factories. FPGAs are uniquely positioned to unify deterministic control, sensor fusion, real-time networking, and edge AI inference on a single adaptable platform. As several of these markets are fast-emerging, the role includes helping establish and scale the market motion - which requires strong technical business leadership at the system level.

Key Responsibilities

1. Market Development & Strategy

Identify and prioritize target segments including:

  • Robotics: industrial and collaborative robots (cobots), autonomous mobile robots (AMR/AGV), humanoids, end-of-arm tooling

  • Autonomous systems: drones / UAVs, autonomous ground and off-road vehicles, autonomous material handling

  • Industrial and factory automation: PLC / PAC controllers, motion and servo-drive control, machine control, IIoT / edge gateways

  • Edge AI: edge AI appliances and gateways, smart cameras and sensors, on-premise inference platforms

Track and interpret trends in:

  • Edge AI and on-device inference (model deployment, quantization, AI acceleration)

  • Multi-sensor fusion (camera, LiDAR, IMU, force / torque)

  • Real-time deterministic control, multi-axis motion, and industrial networking convergence (fieldbus TSN)

  • Industry 4.0 / IIoT, predictive maintenance, and the software-defined factory

  • Robotics and autonomy software stacks (ROS / ROS2) and AI frameworks

Identify opportunities where customers require:

  • Deterministic, low-latency control and motion loops

  • High-throughput, low-power edge AI inference

  • Multi-sensor aggregation and time synchronization

  • Functional safety for human-machine collaboration

  • Reconfigurability across evolving platforms and long industrial lifecycles

2. Customer Engagement & Design Wins

  • Build relationships with robotics OEMs, industrial-automation vendors (controls, drives, machine builders), autonomous-system developers, edge AI platform vendors, module / subsystem suppliers, and system integrators

Drive early-stage engagement with Sales to:

  • Influence system and safety architecture decisions

  • Position FPGA-based solutions across control, sensing, networking, and edge AI systems

  • Secure design-ins across platforms, machines, and derivatives

  • Support technical sales discussions spanning:

  • Motor / motion control (field-oriented control, multi-axis servo, encoder interfacing)

  • Industrial control and real-time networking (PLC / PAC, EtherCAT, PROFINET, EtherNet/IP, TSN)

  • Sensor fusion and perception pipelines

  • Edge AI / ML inference (CNN- and transformer-based workloads)

  • Functional-safety implementation (safe motion, redundancy, diagnostics)

Engage in system-level discussions involving:

  • Perception planning actuation pipelines

  • Centralized vs distributed control architectures (robot, machine, and factory cell)

  • Deterministic vs GPU-based processing trade-offs

3. Ecosystem & Partnerships

Build and manage relationships with:

  • Sensor, encoder, and actuator / drive vendors

  • Industrial networking, controls, and automation-software vendors

  • IP providers and software / AI stack vendors (ROS ecosystem, vision / AI frameworks)

  • Robotics and automation module makers, ODMs, and system integrators

  • Enable joint solutions and reference designs to accelerate customer adoption

4. Sales Enablement & Execution

  • Develop high-impact sales collateral including solution briefs, reference architectures (motion control, industrial networking, sensor fusion, edge AI), competitive positioning vs FPGA / SoC / ASSP / GPU / MCU alternatives, and ROI / TCO analyses

Support Sales teams with:

  • Use-case driven messaging for robotics, autonomous systems, industrial automation, and edge AI applications

  • Customer presentations and technical positioning

  • Opportunity qualification and deal progression

  • Deliver presentations at customer meetings, industry events, and trade shows

5. Internal Collaboration

  • Provide structured market feedback to product management and engineering

  • Influence product direction based on customer needs related to:

  • Real-time I/O and deterministic networking

  • Motion-control and safety features

  • Edge AI capabilities and AI fabric

  • Power, thermal, and form-factor for embedded, mobile, and industrial deployment

  • Support pricing discussions and business case development

The pay range below is for Bay Area California only. Actual salary may vary based ona number offactors including job location, job-related knowledge, skills, experiences,trainings, etc. We also offer incentive opportunities that reward employees based on individual and company performance.

$166.9K- $241.6KUSD

We use artificial intelligence to screen, assess, or select applicants for the position.Applicants must be eligible for any required U.S. export authorizations.

    Qualifications:

    Required Qualifications

    • Bachelor's Degree in Electrical Engineering, Computer Engineering, or related field (Master's preferred)


    7+ years of experience in:

    • Robotics, industrial / factory automation, autonomous systems, or edge AI / embedded systems

    • Semiconductor, module, controls, or OEM environments

    Strong understanding of:

    • Motion / motor control and real-time systems

    • Industrial control and networking concepts

    • Sensor technologies and fusion (camera, LiDAR, IMU, force / torque)

    • AI / ML fundamentals (edge inference pipelines)

    • Familiarity with key interfaces and networks:

    • EtherCAT, PROFINET, EtherNet/IP, TSN, real-time Ethernet

    • Encoder interfaces (BiSS, EnDat, SSI), MIPI CSI-2

    • Experience engaging global customers and managing long design cycles


    Preferred Qualifications

    • Experience with FPGA-based systems or FPGA solution selling

    • Understanding of high-speed I/O and memory subsystems, multi-axis motion control, and edge AI deployment constraints (latency, power, form factor)

    • Familiarity with ROS / ROS2, AI frameworks, and edge AI toolchains

    • Awareness of functional-safety and industrial standards (ISO 10218, ISO/TS 15066, IEC 61508 / SIL, IEC 61131-3, IEC 62443)

    Prior experience with:

    • Robotics OEMs or integrators

    • Industrial automation / controls / drive companies

    • Autonomous-system, drone, or AMR/AGV developers

    • Edge AI platform or appliance vendors

    • MBA or business training is a plus


    Critical Success Factors

    • Design-in mindset: Ability to engage early and secure long lifecycle platform wins

    • System-level thinking: Understanding the complete signal chain from sensing through processing to actuation

    • Execution focus: Ability to convert opportunities into pipeline and revenue

    • Customer-centric approach: Strong listening skills and ability to translate requirements into solutions

    • Ecosystem leverage: Driving wins through partnerships, not just silicon features


    KPIs / Success Metrics

    • Design wins and revenue growth across robotics, autonomous systems, industrial automation, and edge AI segments

    • Number of qualified opportunities identified in motion control, industrial networking, sensor fusion, and edge AI systems

    • Pipeline growth and forecast accuracy

    • Engagements with OEMs, automation vendors, module vendors, and system integrators

    • Contribution to sales enablement and deal progression

    Job Type: RegularShift:Shift 1 (United States of America)Primary Location:San Jose, California, United StatesAdditional Locations:Posting Statement:All qualified applicants will receive consideration for employment without regard to race, color, religion, religious creed, sex, national origin, ancestry, age, physical or mental disability, medical condition, genetic information, military and veteran status, marital status, pregnancy, gender, gender expression, gender identity, sexual orientation, or any other characteristic protected by local law, regulation, or ordinance.

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