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Machine Learning Engineer Jobs in Palmdale, CA (NOW HIRING)

Machine Learning Engineer

Los Angeles, CA ยท On-site

$150K - $180K/yr

Bachelor degree with 4+ years experience as a machine learning engineer * AND 2+ years of Python and PyTorch or TensorFlow experience * Must be a U.S. citizen with the ability to obtain necessary ...

Machine Learning Engineer

Chatsworth, CA ยท On-site

$160K - $190K/yr

We are looking for a Machine Learning Engineer to join our team and help us push the boundaries of what's possible in smart manufacturing. In this role, you will design, build, train, and deploy ...

Senior Machine Learning Engineer

Burbank, CA ยท On-site

$111K - $153K/yr

Senior Machine Learning Engineer Team: Data & Audience Platform (DAP) - ML Engineering What We Do Warner Bros. Discovery (WBD) is home to the world's most iconic entertainment, news, and sports ...

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Machine Learning Engineer information

See Palmdale, CA salary details

$33.7K

$137.6K

$206.8K

How much do machine learning engineer jobs pay per year?

As of Aug 29, 2026, the average yearly pay for machine learning engineer in Palmdale, CA is $137,640.00, according to ZipRecruiter salary data. Most workers in this role earn between $108,500.00 and $165,700.00 per year, depending on experience, location, and employer.

What is a machine learning engineer?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

What does a machine learning engineer do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

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

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

What are some common challenges faced by machine learning engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

What is the difference between Machine Learning Engineer vs Data Scientist?

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

What are the most commonly searched types of Machine Learning Engineer jobs in Palmdale, CA?

The most popular types of Machine Learning Engineer jobs in Palmdale, CA are:

What are popular job titles related to Machine Learning Engineer jobs in Palmdale, CA?

For Machine Learning Engineer jobs in Palmdale, CA, the most frequently searched job titles are:

What cities near Palmdale, CA are hiring for Machine Learning Engineer jobs?

Cities near Palmdale, CA with the most Machine Learning Engineer job openings:

Infographic showing various Machine Learning Engineer job openings in Palmdale, CA as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 22% Part Time, and 2% Contract. Highlights an 89% Physical, 2% Hybrid, and 9% Remote job distribution, with an average salary of $137,640 per year, or $66.2 per hour.

Machine Learning Engineer

Ascent Developer Solutions

Los Angeles, CA โ€ข On-site

Full-time

Re-posted 26 days ago


Job description

ROLE SUMMARYย 

The Machine Learning Engineer is a major contributor in driving our company's innovation and data-driven decision-making. By harnessing advanced analytics, machine learning, and big data technologies, this role directly impacts strategic business outcomes, revealing actionable insights and predicting trends that shape the future of our operations. Embedded at the intersection of data and strategy, the Data Scientist empowers the organization to navigate complex challenges, optimize performance, and unlock new growth opportunities.ย 

ESSENTIAL DUTIESย 

Data and analysisย 

  • Analyze public recordsย and other real estateย data using NLP and machine learning techniques toย identifyย patterns and cluster entities.ย 
  • Develop methods for evaluating and selecting large language models (LLMs) for deployment.ย 
  • Buildย predictive modelsย toย identifyย potential borrowers,ย likelihood ofย default, and quality/valuations of properties for lending activities.ย 
  • Identifyย new business opportunities through tracking competitor trends and keeping management aware of developer lending market trends and insights.ย 
  • Assistย in fostering a culture of test & learn within the company.ย 

Leadership ย 

  • Serve asย analyticsย consultant to a broad variety of line-of-business teams.ย 
  • Partner with technology teams on product changes and impacts on data/performance.ย 
  • Mentorย juniorย analysts on various data science techniques.ย 

ย QUALIFICATIONSย 

  • Bachelor's degree inย quantitativeย field.ย 
  • 5-7 years of experience in analytical or consulting roles.ย 
  • Strong data science skills with AI/ML related Python libraries such asย PyTorch, TensorFlow, andย Keras. Conceptual knowledge of LLM's.ย 
  • Strong knowledge of statistics, hypothesis testing, and setting up experiments.ย 
  • Must have deployed several models to production.ย 
  • Exposure toย data engineering skills.ย 
  • Strong communicationย and partnership skills, effective cross-department collaboration skills.ย 
  • Self-starter who can work under limited supervision.ย 
  • Mentoring skills to help develop junior analysts.ย 

WORK ENVIRONMENTย 

  • This roleย worksย on-siteย from Ascent's Encino office 2 days per weekย 

THE PAYย 

Salary range is $130,000-$150,000 per year, with a discretionary bonus of 20% per year.ย