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Wearable Data Science Jobs in California (NOW HIRING)

Head of Partnerships

Menlo Park, CA · Remote

$200K - $300K/yr

... science, and real-world health data to empower individuals to take control of their health. Our flagship January app uses data from continuous glucose monitors, wearables, and food logs to predict ...

Senior Data Architect

San Francisco, CA · On-site

$79.25 - $106/hr

Partner with Data Engineering, Data Science, and Business Domain owners to advocate for unified ... Preferred : • Experience in the healthcare, wellness, consumer electronics, wearables, digital ...

Head of Partnerships

Menlo Park, CA · On-site +1

$200K - $300K/yr

... science, and real-world health data to empower individuals to take control of their health. Our flagship January app uses data from continuous glucose monitors, wearables, and food logs to predict ...

We thrive in a fast paced environment where team members are often encouraged to wear multiple hats ... You will translate analytics needs from Data Science, Engineering, Product, and Program Management ...

Sr Machine Learning Engineer

San Diego, CA · On-site

$112K - $154K/yr

Collaborate with engineers, data scientists, and mission stakeholders to align ML solutions with ... Ability to comply with Navy safety requirements and wear required personal protective equipment ...

Sr Machine Learning Engineer

San Diego, CA · On-site

$131K - $173K/yr

Collaborate with engineers, data scientists, and mission stakeholders to align ML solutions with ... Ability to comply with Navy safety requirements and wear required personal protective equipment ...

PHM Engineer

Foster City, CA · On-site

$61.76 - $68.62/hr

Develop offline diagnostic algorithms to detect anomalies, wear-and-tear patterns, and early fault ... D. in Mechanical Engineering, Electrical Engineering, Data Science, or a related field. #LI-LP1

Showing results 21-40

Wearable Data Science information

What is the difference between Wearable Data Science vs Wearable Data Analyst?

AspectWearable Data ScienceWearable Data Analyst
Required CredentialsDegree in Data Science, Computer Science, or related field; knowledge of machine learningDegree in Data Analysis, Statistics, or related field; proficiency in data visualization tools
Work EnvironmentResearch labs, tech companies, healthcare startupsHealthcare providers, fitness companies, wearable device firms
Employer & Industry UsageDevelops algorithms, models, and wearable tech innovationsAnalyzes wearable data to inform decisions, improve products, and report findings

Wearable Data Science focuses on developing algorithms and models to interpret wearable device data, often involving machine learning. Wearable Data Analysts interpret and visualize this data to support business or healthcare decisions. Both roles require strong analytical skills but differ in technical depth and responsibilities.

What is wearable data science?

Wearable data science is a field focused on analyzing and interpreting data collected from wearable devices such as smartwatches, fitness trackers, and health monitors. Professionals in this area develop methods to process large volumes of sensor data to gain insights into health, activity, and behavior patterns. The insights can be used to improve health outcomes, enhance user experiences, and support research in various domains including healthcare, sports, and consumer technology.

What are the key skills and qualifications needed to thrive as a wearable data scientist, and why are they important?

To thrive as a Wearable Data Scientist, you need a solid background in data analysis, statistics, machine learning, and a relevant degree in fields like computer science, engineering, or data science. Familiarity with programming languages such as Python or R, experience with data visualization tools, and knowledge of wearable sensor platforms are typically required. Strong problem-solving abilities, attention to detail, and effective communication skills help you translate complex data into actionable insights. These skills are vital for developing accurate models and delivering meaningful results that drive innovation in wearable technology.

How do wearable data scientists typically collaborate with hardware engineers and software developers during product development?

Wearable data scientists work closely with hardware engineers to understand sensor specifications and data collection constraints, ensuring that the data is accurate and usable for analysis. They also collaborate with software developers to integrate data processing algorithms into wearable devices or companion apps, often providing feedback on data flow, storage, and real-time analytics. This cross-functional teamwork is essential for developing robust products that deliver actionable insights to users and meet technical requirements.
What job categories do people searching Wearable Data Science jobs in California look for? The top searched job categories for Wearable Data Science jobs in California are:
What cities in California are hiring for Wearable Data Science jobs? Cities in California with the most Wearable Data Science job openings:
Infographic showing various Wearable Data Science job openings in California as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Software Engineer, AI Specialist - Wearables AI (Technical Leadership)

Meta

Burlingame, CA • On-site

$219K - $301K/yr

Full-time

Posted 26 days ago


Meta rating

7.8

Company rating: 7.8 out of 10

Based on 45 frontline employees who took The Breakroom Quiz

135th of 242 rated software companies


Job description

Meta is seeking a distinguished software engineer with deep AI specialization to drive transformative technical initiatives for Wearables AI. In this role, you will define and lead the architectural direction of large-scale AI systems powering Meta's wearable devices - including smart glasses and next-generation wearable platforms. You will build intelligent on-device and cloud-based AI experiences spanning multimodal understanding, contextual assistants, and real-time interactive AI systems. This is a role for a technical leader who operates at the intersection of cutting-edge AI research and production-scale engineering, shaping both the systems and the culture that powers Meta's wearables AI future.
Responsibilities
Identify and solve the most complex AI modeling and systems challenges for wearables, including architecting an omni LLM for wearables interactions, optimized for power, latency, and compute constraints
• Define extensible technical foundations and cross-organizational standards for wearables AI model development, evaluation, and deployment pipelines across Meta's wearable device portfolio
• Drive the technical vision and multi-year roadmap for Wearables AI platform capabilities, influencing priorities across teams and cross-functional partners including research, hardware, product, and data science
• Evaluate emerging AI architectures and industry developments in wearables AI to identify opportunities and risks relevant to Meta's competitive position
• Lead the design and implementation of multimodal AI systems for wearables, including vision, audio, and agentic capabilities, reliability, and real-time performance are critical
• Identify where AI tooling and automation can eliminate entire categories of engineering work, and drive adoption of AI-native workflows across wearables engineering teams
• Collaborate with research scientists to translate novel AI techniques into production wearables systems that deliver seamless, intelligent user experiences
• Mentor engineers across the organization by providing customized technical coaching, leading architecture reviews, and establishing a culture of rigor for wearables AI development
• Partner with hardware, legal, policy, and compliance teams to ensure wearables AI systems meet privacy, security, and integrity standards for always-on, sensor-rich devices
• Define new metrics and data-driven decision-making principles for long-term wearables AI initiatives, connecting technical outcomes to organization-level priorities and business impact
Minimum Qualifications
• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
• 12+ years of experience in software engineering with a focus on AI, LLM systems, or applied AI in production environments
• Experience architecting and delivering large-scale AI, including training infrastructure, model serving, or foundation model pipelines
• Experience leading multi-team technical initiatives end-to-end, including defining strategy, driving cross-functional alignment, and delivering measurable outcomes against organization-level goals
• Experience identifying and resolving systemic engineering issues that span models, multiple systems or abstraction layers, including developing frameworks that prevent recurring classes of failures
• Experience communicating complex AI designs and technical trade-offs in writing and presentations to both technical and non-technical audiences, including engineering leadership
Preferred Qualifications
• Contributions to peer-reviewed AI research (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR, KDD) or demonstrated track record of translating research advances into production AI systems
• Experience with large-scale Omni LLM training optimization, distributed training frameworks, or inference efficiency techniques such as quantization, distillation, or speculative decoding
• Experience with conversational AI, vision understanding, wearables AI systems
• Experience applying AI and automation tooling to eliminate categories of engineering toil and measurably improve team-level or organization-level engineering efficiency
About Meta
Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today-beyond the constraints of screens, the limits of distance, and even the rules of physics.
Equal Employment Opportunity
Meta is proud to be an Equal Employment Opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics. You may view our Equal Employment Opportunity notice here.

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