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Ai Data Abstraction Jobs (NOW HIRING)

Data and Perception Engineer

San Francisco, CA · On-site

$134K - $162K/yr

Conduit builds autonomous factories through a single data abstraction layer across every machine ... We partner with manufacturers to turn their existing infrastructure into AI without rip and replace ...

Data and Analytics Architect

Irving, TX · On-site

$61.25 - $78.75/hr

Define data abstraction layers ensuring third-party SaaS and legacy databases map cleanly to ... Architect secure, scalable Model Context Protocol (MCP) servers and gateways to connect LLMs and AI ...

Senior Staff Enterprise Architect, Data

Palo Alto, CA · On-site

$79 - $105.75/hr

Specify patterns (federation, replication, abstraction layer) balancing performance, cost, and data ... Evaluate AI-powered data observability platforms for quality monitoring, pipeline failure ...

Senior Staff Enterprise Architect, Data

Palo Alto, CA · Hybrid

$79 - $105.75/hr

Specify patterns (federation, replication, abstraction layer) balancing performance, cost, and data ... Evaluate AI-powered data observability platforms for quality monitoring, pipeline failure ...

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Ai Data Abstraction information

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How much do ai data abstraction jobs pay per hour?

As of Sep 12, 2026, the average hourly pay for ai data abstraction in the United States is $25.33, according to ZipRecruiter salary data. Most workers in this role earn between $18.51 and $31.97 per hour, depending on experience, location, and employer.

What is AI data abstraction?

AI data abstraction is the process of extracting, organizing, and summarizing information from large datasets using artificial intelligence techniques. This role often involves identifying relevant data, cleaning and structuring it, and transforming it into formats suitable for further analysis or machine learning tasks. Professionals in AI data abstraction help ensure that only the most meaningful and actionable information is retained, making it easier for organizations to derive insights and make data-driven decisions.

What are the key skills and qualifications needed to thrive as an AI data abstraction specialist, and why are they important?

To thrive as an AI Data Abstraction Specialist, you need a strong background in data analysis, attention to detail, and familiarity with data management, typically supported by a degree in computer science, information systems, or a related field. Proficiency with data annotation tools, machine learning platforms, and database systems is often required, along with knowledge of programming languages such as Python or SQL. Strong problem-solving skills, communication, and the ability to work collaboratively are essential soft skills for this role. These skills ensure accurate data extraction, high-quality datasets, and effective support for AI model development.

What are some common challenges faced in AI data abstraction roles and how can they be addressed?

Professionals in AI Data Abstraction often encounter challenges such as ensuring data accuracy, dealing with incomplete or inconsistent data sources, and maintaining data privacy standards. Collaborating closely with data engineers and domain experts can help clarify ambiguities and improve data quality. Regular training on data handling protocols and leveraging automated validation tools can also minimize errors and streamline the abstraction process. Adapting to evolving project requirements and maintaining clear documentation are essential for long-term success in this role.

What is the difference between Ai Data Abstraction vs Data Analyst?

AspectAi Data AbstractionData Analyst
Required CredentialsTypically requires knowledge of AI, data processing, and programming skillsRequires proficiency in data analysis, statistics, and often a degree in related fields
Work EnvironmentOften involves working with AI models, machine learning tools, and large datasetsFocuses on interpreting data, creating reports, and supporting decision-making
Industry UsageUsed in AI development, data engineering, and machine learning projectsCommon in business intelligence, marketing, finance, and operations

While both roles handle data, Ai Data Abstraction focuses on preparing and structuring data for AI models, whereas Data Analysts interpret data to generate insights. Understanding these differences helps in choosing the right career path or job focus within data-related fields.

How to become a data abstractor?

To become a data abstractor, you typically need a high school diploma or equivalent, strong attention to detail, and proficiency in data management tools like spreadsheets or database software. Relevant skills include reading comprehension, accuracy, and sometimes certification in health information or data management. Gaining experience through training programs or entry-level positions can also help establish a career in data abstraction.

What other helpful pages are available for Ai Data Abstraction?

Other pages related to Ai Data Abstraction:

Infographic showing various Ai Data Abstraction job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 84% Full Time, 11% Part Time, and 3% Contract. Highlights an 85% Physical, 3% Hybrid, and 12% Remote job distribution, with an average salary of $52,687 per year, or $25.3 per hour.

Data and Perception Engineer

San Francisco, CA • On-site

Conduit
1 - 5K employees

$134K - $162K/yr

Other

This job post has expired 2 days ago. Applications are no longer accepted.


Key responsibilities

  • Own customer CV/ML deployments end to end, including problem scoping, data pipeline design, model training, deployment, and validation.

  • Build and maintain end-to-end pipelines from training to inference, including data collection, labeling, evaluation, deployment, and monitoring.

  • Stream and process video data at industrial scale, implementing real-time inference, intelligent downsampling, smart triggers, and alerting.


Job description

Conduit builds autonomous factories through a single data abstraction layer across every machine, robot, sensor and software a factory might have, agnostic of brand or backend. We partner with manufacturers to turn their existing infrastructure into AI without rip and replace, and are able to light up an entire factory in a matter of days, not months, with as few as 2 FDEs at a time. We are live with manufacturers across the country and are growing quickly. We are hiring the people who are excited to tackle challenges at the intersection of data science, industrial automation, and software engineering and bring AI to American manufacturing.


The Role

This is a customer-first role applied to perception, computer vision, data science and ML. Live factory data streams, including defects, ergonomics, cycle times, machine state, operator behavior, and material flow, will drive your research, and you will stand up the streaming vision system that captures, classifies, and acts on those signals in real time. You are technical enough to own the full pipeline: data collection on real factory hardware, manual and automated labeling, model training and evaluation in PyTorch, inference deployment on edge hardware you specced and ordered.


What you'll do

  • Own customer CV/ML deployments end to end. Scope the problem, build edge compute, design the data pipeline, train the model, deploy inference, validate on the floor.
  • Build end-to-end pipelines from training to inference. Data collection, training, evaluation, deployment, monitoring.
  • Stream and process video at industrial volume. Multi-camera setups, real-time inference on the edge, intelligent downsampling, smart triggers, alerting.
  • Apply CV to industrial problems: defect detection, classification, action / ergonomics analysis, machine state, material tracking, operator-assist.
  • Spec and order the hardware to run it. GPUs, edge boxes, cameras, lenses, lighting. You are comfortable being trusted with a $40K compute order.
  • Translate customer needs into clean engineering briefs for the SF team. Build relationships with plant managers and operators so the system gets used.


Who You Are

  • 5+ years of applied computer vision and perception work, including production deployments. You have shipped and iterated on inference pipelines in deployment.
  • You have built end-to-end pipelines from training to inference, including the data labeling muscle — both manual workflows and automated / programmatic labeling, weak supervision, pseudo-labeling, active learning.
  • Strong Python. Strong PyTorch. You are conversational with modern CV, detection, segmentation, classification, action recognition, vision transformers, multi-modal, and the relevant inference toolchain (TensorRT, ONNX, Triton, etc.).
  • You are comfortable around hardware and are confident prescribing hardware across a diverse breadth of cotnexts. You have selected cameras, ordered GPUs, set up edge inference boxes.
  • You are great with customers. You can do a plant tour, push back on a CEO, and earn the trust of an operator who has never seen a model before.
  • You want to be a part of the reindustrialization of the United States


Bonus Points

  • Experience with industrial machine vision (Cognex, Keyence, Zebra / Adaptive Vision, MVTec Halcon).
  • Experience with NVIDIA Jetson, Orin, Isaac, Triton, TensorRT, DeepStream.
  • Experience streaming video at scale: RTSP, GStreamer, multi-cam sync, edge-to-cloud pipelines.
  • Experience with ergonomics, pose estimation, action recognition, or video understanding.
  • Experience with annotation platforms (Scale, Labelbox, V7, internal tools) and building automated labeling loops.


Why Conduit?

This is the rare opportunity to work at the forefront of Physical AI at a company with traction and a real technical moat. At Conduit, you will train your model and see its benefits in the real world.

  • Top tier pay and equity: We want to make it easy to join Conduit.
  • Generational opportunity. Be early at a company defining the software layer for industrial automation.
  • American re-industrialization is happening. We’re building the platform to make it real — faster.
  • Zero bureaucracy. High impact. You’ll be on the front lines, solving real problems for real factories.
  • You will level up. You’ll work directly with the founder and exec team and grow into a senior operator


Conduit is an equal opportunity employer. We welcome applications from all qualified candidates.

To apply, email hiring@conduit.inc with your resume and a note on why you think you might make a strong fit.