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Machine Learning Data Associate Jobs in Encinitas, CA

Bespoke Labs

Machine Learning Engineer

San Diego, CA

Build and maintain the infrastructure around RL training: rollout collection, data curation, reward model serving, and experiment orchestration * Run and scale training experiments on cloud or HPC ...

Bespoke Labs

Machine Learning Engineer

San Diego, CA · On-site

Build and maintain the infrastructure around RL training: rollout collection, data curation, reward model serving, and experiment orchestration * Run and scale training experiments on cloud or HPC ...

Seasats

Senior Machine Learning Engineer

San Diego, CA · On-site

$180K - $250K/yr

Senior Machine Learning Engineer Location: San Diego, CA (in-office) Salary Range: $180,000 - $250 ... You'll take models from experiment to production: curating fleet data, training and distilling ...

Seasats

Senior Machine Learning Engineer

San Diego, CA · On-site

$180K - $250K/yr

Senior Machine Learning Engineer Location: San Diego, CA (in-office) Salary Range: $180,000 - $250 ... You'll take models from experiment to production: curating fleet data, training and distilling ...

Seasats

Senior Machine Learning Engineer

San Diego, CA · On-site

$180K - $250K/yr

Senior Machine Learning Engineer Location: San Diego, CA (in-office) Salary Range: $180,000 - $250 ... You'll take models from experiment to production: curating fleet data, training and distilling ...

Seasats

Senior Machine Learning Engineer

San Diego, CA · On-site

$180K - $250K/yr

Senior Machine Learning Engineer Location: San Diego, CA (in-office) Salary Range: $180,000 - $250 ... You'll take models from experiment to production: curating fleet data, training and distilling ...

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All JobsMachine Learning Data Associate JobsMachine Learning Data Associate Jobs in Encinitas, CA

Machine Learning Data Associate information

See Encinitas, CA salary details

$10

$20

$33

How much do machine learning data associate jobs pay per hour?

As of Sep 13, 2026, the average hourly pay for machine learning data associate in Encinitas, CA is $20.13, according to ZipRecruiter salary data. Most workers in this role earn between $16.54 and $21.44 per hour, depending on experience, location, and employer.

What is a machine learning data associate?

Machine Learning Data Associates are professionals who support the development of machine learning models by preparing, labeling, and validating data sets. Their work ensures that data used for training algorithms is accurate, consistent, and properly annotated. They may also assist with data cleaning, quality checks, and sometimes basic data analysis tasks. This role is crucial in industries where high-quality labeled data is essential for building effective AI systems.

What are the key skills and qualifications needed to thrive as a machine learning data associate?

To thrive as a Machine Learning Data Associate, you need strong analytical skills, attention to detail, and a basic understanding of data annotation and labeling processes, often supported by a degree in computer science or a related field. Familiarity with data management tools, annotation platforms, and sometimes scripting languages like Python is typically required. Strong communication, collaboration, and problem-solving abilities help you work efficiently with data science teams and ensure high-quality outcomes. These skills and qualities are crucial for producing accurate datasets that directly impact the effectiveness of machine learning models.

How does a machine learning data associate typically collaborate with data scientists and engineers within a project team?

As a Machine Learning Data Associate, you play a vital role in supporting data scientists and engineers by annotating, cleaning, and organizing large datasets to ensure high data quality. You'll frequently communicate with team members to clarify labeling guidelines, provide feedback on data inconsistencies, and report any edge cases encountered during annotation. This collaboration ensures that the datasets used for training machine learning models are accurate and comprehensive, directly impacting the success of the project. Expect regular team meetings and ongoing feedback loops to maintain alignment with evolving project requirements.

What is the difference between Machine Learning Data Associate vs Data Analyst?

AspectMachine Learning Data AssociateData Analyst
Required SkillsData cleaning, labeling, basic programming, understanding of ML workflowsData interpretation, visualization, statistical analysis
Work EnvironmentTech companies, AI startups, research labsBusiness, finance, marketing, healthcare sectors
Common CertificationsData Science certifications, Python, SQLExcel, Tableau, SQL certifications

The main difference is that Machine Learning Data Associates focus on preparing and labeling data specifically for machine learning models, while Data Analysts interpret data to generate insights for business decisions. Both roles require strong data skills and often overlap, but their primary objectives and work environments differ.

How do I become a machine learning data associate?

To become a machine learning data associate, candidates typically need a high school diploma or equivalent, with some roles preferring a bachelor's degree in computer science, data science, or related fields. Relevant skills include data annotation, understanding of machine learning concepts, and proficiency with tools like Excel, SQL, or data labeling platforms. Gaining experience through internships or certifications can improve job prospects in this field.

Is a Machine Learning Data Associate a good job?

A Machine Learning Data Associate role involves preparing and managing data for machine learning models, often requiring skills in data cleaning, annotation, and familiarity with tools like Python or SQL. It can be a good entry-level position for those interested in AI and data science, offering opportunities to develop technical skills and gain industry experience. Compensation and job satisfaction vary depending on the employer and location, but it generally provides a solid foundation for a career in machine learning or data analysis.

What cities near Encinitas, CA are hiring for Machine Learning Data Associate jobs?

Cities near Encinitas, CA with the most Machine Learning Data Associate job openings:

Machine Learning Data Associate jobs near you
Infographic showing various Machine Learning Data Associate job openings in Encinitas, CA as of August 2026, with employment types broken down into 1% As Needed, 77% Full Time, 18% Part Time, and 4% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $41,862 per year, or $20.1 per hour.

Senior Engineer - Machine Learning

San Diego, CA • On-site

Qualcomm
Technology, Communication and Media • 10K+ employees
Learn more about Qualcommexternal

$140K - $211K/yr

Other

Re-posted 12 days ago

Qualcomm rating

8.8

Company rating: 8.8 out of 10

Based on 11 frontline employees who took The Breakroom Quiz

Job description

Company

Qualcomm Incorporated

Job Area

Engineering Group, Engineering Group > Machine Learning Engineering

General Summary

We are seeking a highly skilled Core ML Engineer to design, develop, and optimize machine learning systems that power next-generation AI platforms and applications. This role focuses on model development, inference optimization, and scalable ML infrastructure, enabling production-grade AI capabilities across enterprise systems. The ideal candidate combines strong software engineering fundamentals with deep ML expertise, and thrives in building robust, high-performance systems at scale.

Key ResponsibilitiesCore ML System Development
  • Design and implement machine learning models and pipelines for production use.
  • Build scalable training, evaluation, and deployment workflows.
  • Develop reusable ML components, libraries, and frameworks.
Inference & Performance Optimization
  • Optimize model inference for latency, throughput, and cost.
  • Implement advanced techniques such as caching, quantization, batching, and routing.
  • Benchmark and profile models across diverse workloads and hardware environments.
Model Integration & Deployment
  • Integrate ML/LLM models into APIs, microservices, and applications.
  • Build and maintain model-serving infrastructure (e.g., vLLM, ONNX, custom runtimes).
  • Collaborate with platform and infrastructure teams for scalable deployment.
Data & Pipeline Engineering
  • Design data pipelines for ingestion, preprocessing, feature engineering, and validation.
  • Improve data quality and model reliability through systematic evaluation.
Cross-functional Collaboration
  • Partner with product, platform, and hardware teams to deliver end-to-end ML solutions.
  • Participate in design reviews and contribute to system architecture decisions.
Minimum Qualifications
  • Bachelor’s degree in Computer Science, Engineering, Information Systems, or related field and 2+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
  • Master’s degree in Computer Science, Engineering, Information Systems, or related field and 1+ year of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
  • PhD in Computer Science, Engineering, Information Systems, or related field.
Preferred Qualifications

Strong programming skills in Python and at least one systems language (C++/Rust/Go).

Solid understanding of
  • Machine learning fundamentals (supervised, unsupervised, deep learning).
  • Transformer architectures / LLMs.
  • Model evaluation and debugging.
Experience with ML frameworks, model deployment, and building scalable software and APIs
  • ML frameworks (PyTorch, TensorFlow).
  • Model deployment and serving systems.
  • Building scalable software and APIs.
Experience with LLMs, retrieval systems, and distributed compute
  • Large Language Models (LLMs), multimodal models, or generative AI.
  • Retrieval systems and RAG pipelines.
  • Distributed computing and GPU/accelerator environments including model serving and efficient cache/state management (e.g., KV cache, embeddings) across disaggregated systems.
  • Kubernetes, Docker, and CI/CD pipelines.
  • Agentic and multi-step AI workflows, tool integration, orchestration, and multi-component pipelines.
Knowledge of
  • Model optimization techniques (quantization, distillation, caching).
  • Vector databases and search systems (OpenSearch, Qdrant, etc.).
  • Cost-aware system design – model routing (small vs. large models), dynamic batching, and caching strategies.
Pay range and Other Compensation & Benefits

$140,800.00 - $211,200.00. The above pay scale reflects the broad, minimum to maximum, pay scale for this job code for the location for which it has been posted. Salary is only one component of total compensation at Qualcomm. We also offer a competitive annual discretionary bonus program and opportunity for annual RSU grants (employees on sales-incentive plans are not eligible for our annual bonus). In addition, our highly competitive benefits package is designed to support your success at work, at home, and at play.

Equal Opportunity Statement

Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities. Qualcomm is an equal opportunity employer; all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or any other protected classification.

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What Qualcomm employees say

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Benefits

Hours and flexibility

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About Qualcomm

Sourced by ZipRecruiter

Qualcomm is enabling a world where everyone and everything can be intelligently connected. You interact with products and technologies made possible by Qualcomm every day, including 5G-enabled smartphones that double as pro-level cameras and gaming devices, smarter vehicles and cities, and the technology behind the smart, connected factories that manufactured your latest purchase. Our powerful connectivity solutions keep you connected—even in remote areas. Qualcomm 5G and AI innovations are the power behind the connected intelligent edge. You’ll find our technologies behind and inside the innovations that deliver significant value across multiple industries and to billions of people every day.

Industry

Technology, communication and media

Company size

10,000+ Employees

Headquarters location

San Diego, CA, US

Year founded

1985

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