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Data Preprocessing Jobs in Los Angeles, CA (NOW HIRING)

Senior AI Engineer

Los Angeles, CA · On-site

$160K - $190K/yr

Expertise in data modeling, preprocessing, and model evaluation at scale. * Familiarity with generative AI models (LLMs, diffusion models, GANs) and their real-world applications. * Strong knowledge ...

Senior AI Engineer

Los Angeles, CA · On-site

$180 - $240/hr

Expertise in data modeling, preprocessing, and model evaluation at scale. * Familiarity with generative AI models (LLMs, diffusion models, GANs) and their real-world applications. * Strong knowledge ...

Senior Machine Learning Platform Engineer

Irvine, CA · On-site

$112K - $154K/yr

Strong knowledge of data management at scale , including preprocessing and retrieval of video/image datasets. * Proficiency with CI/CD pipelines , infrastructure-as-code (Terraform, CloudFormation ...

Senior Machine Learning Platform Engineer

Irvine, CA · On-site

$112K - $154K/yr

Strong knowledge of data management at scale , including preprocessing and retrieval of video/image datasets. * Proficiency with CI/CD pipelines , infrastructure-as-code (Terraform, CloudFormation ...

Showing results 41-51

Data Preprocessing information

See Los Angeles, CA salary details

$49.6K

$177.8K

$262.4K

How much do data preprocessing jobs pay per year?

As of Aug 22, 2026, the average yearly pay for data preprocessing in Los Angeles, CA is $177,809.00, according to ZipRecruiter salary data. Most workers in this role earn between $143,800.00 and $183,200.00 per year, depending on experience, location, and employer.

What is data preprocessing?

Data preprocessing is the process of cleaning, transforming, and organizing raw data into a usable format for analysis or machine learning. It involves steps such as handling missing values, removing duplicates, normalizing or scaling data, and encoding categorical variables. Proper data preprocessing helps improve the quality and performance of predictive models by ensuring the data is accurate, consistent, and suitable for analysis.

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

To thrive as a Data Preprocessing Specialist, you need a strong background in statistics, data cleaning, and data transformation, often supported by a degree in computer science, data science, or a related field. Proficiency with tools such as Python (pandas, NumPy), SQL, and data visualization platforms is typically essential, along with familiarity with data management systems. Attention to detail, problem-solving abilities, and effective communication are standout soft skills in this position. These skills are crucial for ensuring high-quality, reliable datasets that underpin accurate data analysis and machine learning outcomes.

What are some common challenges faced in a data preprocessing role, and how can they be effectively managed?

Professionals in Data Preprocessing often encounter challenges such as handling incomplete or inconsistent data, managing large datasets, and ensuring data quality before analysis. Addressing these issues typically involves using specialized tools to automate data cleaning, establishing clear data validation rules, and collaborating closely with data engineers and analysts. Staying updated with best practices and leveraging scripting languages like Python or R can also streamline the preprocessing workflow, making it easier to deliver reliable and accurate datasets for downstream analysis.

What is the difference between Data Preprocessing vs Data Analysis?

AspectData PreprocessingData Analysis
Primary FocusCleaning, transforming, and preparing raw data for analysisInterpreting data to extract insights and support decision-making
Skills RequiredData cleaning, scripting, understanding of data formatsStatistical analysis, data visualization, critical thinking
Work EnvironmentData engineering teams, data science projectsBusiness intelligence, research, data science teams
Tools UsedPython, R, SQL, ETL toolsExcel, Tableau, R, Python, statistical software

While data preprocessing involves preparing raw data for analysis by cleaning and transforming it, data analysis focuses on interpreting the prepared data to uncover trends and insights. Both roles are essential in the data pipeline but serve different purposes in the data lifecycle.

What job categories do people searching Data Preprocessing jobs in Los Angeles, CA look for?

The top searched job categories for Data Preprocessing jobs in Los Angeles, CA are:

What cities near Los Angeles, CA are hiring for Data Preprocessing jobs?

Cities near Los Angeles, CA with the most Data Preprocessing job openings:

Infographic showing various Data Preprocessing job openings in Los Angeles, CA 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, with an average salary of $177,809 per year, or $85.5 per hour.

Senior AI Engineer

First Resonance

Los Angeles, CA • On-site

$160K - $190K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 2 days ago


Job description

Overview

We’re looking for a Senior Software Engineer with a passion for AI to join us in our mission of bringing the ION Factory OS to next-generation hardware builders around the globe. This role is based in Los Angeles, CA (HQ in El Segundo).

Are you excited by the opportunity to build AI-powered software that accelerates the development of eVTOLs, rockets, robots, and autonomous vehicles?

Responsibilities & Duties
  • Lead the design, implementation, and optimization of production-ready AI systems within the ION Factory OS.

  • Ship customer-facing features that directly impact manufacturing workflows, including AI-driven functionality (e.g., generative procedure creation, anomaly detection, recommendations) and core product features not reliant on AI.

  • Architect and maintain scalable software systems, including AI/ML pipelines and broader product infrastructure.

  • Design and implement AI features using retrieval-augmented generation (RAG) pipelines to deliver context-aware insights and recommendations.

  • Leverage Model Context Protocol (MCP) and similar frameworks to connect AI models seamlessly with structured/unstructured data sources and external tools.

  • Collaborate with product managers and customers to translate real-world challenges into robust software solutions.

  • Partner with data engineering to process and transform structured and unstructured manufacturing data into usable formats.

  • Ensure reliability, scalability, and maintainability of all systems in production, leveraging CI/CD and cloud-native workflows.

  • Stay ahead of advancements in software engineering and AI, bringing the best practices into shipped product features.

  • Mentor junior engineers and help raise the technical bar across the team.

Minimum Qualifications & Skills
  • 7+ years of professional software engineering experience, including 3+ years shipping AI/ML-powered products into production.

  • Proven track record of building and shipping customer-facing applications (AI and non-AI) that deliver measurable business value.

  • Experience architecting scalable systems on cloud platforms (AWS, Azure, GCP).

  • Expertise in data modeling, preprocessing, and model evaluation at scale.

  • Familiarity with generative AI models (LLMs, diffusion models, GANs) and their real-world applications.

  • Strong knowledge of APIs and modern software design patterns for integrating AI into SaaS products.

  • Excellent problem-solving, communication, and cross-functional collaboration skills.

  • Passion for AI innovation paired with the ability to deliver non-AI product functionality when needed.

Desired Qualifications
  • Experience building AI systems for real-time, low-latency, or edge deployments.

  • Familiarity with modern data governance, privacy, and compliance standards (SOC2, GDPR, ITAR).

  • Hands-on experience with retrieval-augmented generation (RAG) for building AI systems that combine large language models with external knowledge sources.

  • Understanding of and/or experience with Model Context Protocol (MCP) or similar emerging standards for connecting AI systems with data and tools.

  • Customer-facing experience gathering requirements, presenting solutions, and demonstrating value.

  • Contributions to open-source projects or published research in applied AI/ML.

  • Experience mentoring engineers and contributing to engineering best practices.

Benefits & Perks

  • Health Insurance; medical, vision, dental, & life insurance.

  • Paid Parental Leave.

  • Employee Stock Option Plan.

  • Team outings, group lunches, open office, happy hours.

  • Paid holidays, sick days.

  • Flexible Friday and PTO.

  • 401K.

First Resonance is an equal opportunity employer dedicated to building an inclusive and diverse workforce.

First Resonance participates in E-Verify. As part of our onboarding process, a new hire's Form I-9 information will be shared with the federal government to confirm they are authorized to work in the U.S.

Pay is based on factors such as (but not limited to) scope and responsibilities of the position, candidate's work experience and skillset, and location.

First Resonance accelerates the speed and reliability of hardware development for companies manufacturing the next generation of hardware products. This includes space exploration, electric airplanes, autonomous vehicles, nuclear reactors, robotics, and more. We are a group of software, hardware, and manufacturing engineers that are bringing the best of modern UX and data science to an industry that has been overly rigid in its innovation. We are removing the barriers preventing radical advancement by providing tools to manufacturing engineers and operators to move information more freely, collaborate with their teams more easily, and use the power of data to predict problems and provide insights that result in better hardware quality and delivery.

Compensation Range: $160K - $190K