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Machine Learning Engineer Jobs in Bellflower, CA

Prosum Inc.

Machine Learning Engineer

CA · On-site

$75 - $89/hr

Machine Learning Engineer Pay Rate: $75-$89/hour Position Summary We are seeking a skilled Machine Learning Engineer (MLOps) to support the full lifecycle of machine learning models, including design ...

True Anomaly

Machine Learning Engineer

Long Beach, CA · On-site

They are seeking a Machine Learning Engineer to design and develop machine learning and AI capabilities, contributing to object classification, anomaly detection, and data-driven decision-making.

True Anomaly

Machine Learning Engineer

Long Beach, CA · On-site

They are seeking a Machine Learning Engineer to join their Applied Algorithms and Autonomy team, where the role involves designing and developing machine learning and AI capabilities to support ...

Motorola

Machine Learning Engineer

Los Angeles, CA

THE OPPORTUNITY Silvus is seeking a Machine Learning Engineer who will report to the R&D Director, Machine Learning on the R&D team. The successful individual in this role will focus on applying ...

Motorola

Machine Learning Engineer

Los Angeles, CA

THE OPPORTUNITY Silvus is seeking a Machine Learning Engineer who will report to the R&D Director, Machine Learning on the R&D team. The successful individual in this role will focus on applying ...

Hadrian Automation

Machine Learning Engineer

Los Angeles, CA · On-site

$160K - $250K/yr

As a Senior Machine Learning Engineer, you will play a key role in designing, building, and scaling these systems end to end. What You'll Do: * Research, develop and deploy cutting-edge deep learning ...

Hadrian

Machine Learning Engineer

Los Angeles, CA · On-site

$160K - $250K/yr

As a Senior Machine Learning Engineer, you will play a key role in designing, building, and scaling these systems end to end. What You'll Do * Research, develop and deploy cutting-edge deep learning ...

Hadrian Automation

Machine Learning Engineer

Los Angeles, CA · On-site

$160K - $250K/yr

As a Senior Machine Learning Engineer, you will play a key role in designing, building, and scaling these systems end to end. What You'll Do: * Research, develop and deploy cutting-edge deep learning ...

HADRIAN

Machine Learning Engineer

Los Angeles, CA

$160K - $250K/yr

As a Senior Machine Learning Engineer, you will play a key role in designing, building, and scaling these systems end to end. What You'll Do: * Research, develop and deploy cutting-edge deep learning ...

HADRIAN

Machine Learning Engineer

Los Angeles, CA

$160K - $250K/yr

As a Senior Machine Learning Engineer, you will play a key role in designing, building, and scaling these systems end to end. What You'll Do: * Research, develop and deploy cutting-edge deep learning ...

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All JobsMachine Learning Engineer JobsMachine Learning Engineer Jobs in Bellflower, CA

Machine Learning Engineer information

See Bellflower, CA salary details

$32.9K

$134.6K

$202.2K

How much do machine learning engineer jobs pay per year?

As of Jun 11, 2026, the average yearly pay for machine learning engineer in Bellflower, CA is $134,560.00, according to ZipRecruiter salary data. Most workers in this role earn between $106,100.00 and $162,000.00 per year, depending on experience, location, and employer.

Is ML full of coding?

Machine Learning Engineers typically do a significant amount of coding, especially in languages like Python or R, to develop algorithms, preprocess data, and build models. Strong programming skills are essential, along with knowledge of frameworks such as TensorFlow or PyTorch, but the role also involves data analysis, model evaluation, and collaboration with teams. Coding is a core component of the job, though some tasks may involve model deployment and optimization that require different skills.

What engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data science, and often working in high-paying industries such as finance or technology can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially at large tech companies or startups with significant funding.

What do machine learning engineers do?

Machine learning engineers develop algorithms and models that enable computers to learn from data and make predictions or decisions. They often work with large datasets, use programming languages like Python or Java, and utilize tools such as TensorFlow or PyTorch to build, test, and deploy machine learning systems in production environments.

What are Machine Learning Engineers?

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 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.

Which 5 jobs will survive AI?

Machine Learning Engineers are likely to continue to be in demand as they develop, implement, and maintain AI systems, requiring specialized skills in programming, data analysis, and model optimization. Roles that involve complex problem-solving, creativity, and human interaction—such as healthcare professionals, educators, skilled tradespeople, and certain managerial positions—are also expected to persist despite AI advancements. These jobs typically require emotional intelligence, adaptability, and domain expertise that AI cannot easily replicate.

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 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.

More about Machine Learning Engineer jobs
What are the most commonly searched types of Machine Learning Engineer jobs in Bellflower, CA? The most popular types of Machine Learning Engineer jobs in Bellflower, CA are:
What are popular job titles related to Machine Learning Engineer jobs in Bellflower, CA? For Machine Learning Engineer jobs in Bellflower, CA, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer jobs in Bellflower, CA look for? The top searched job categories for Machine Learning Engineer jobs in Bellflower, CA are:
What cities near Bellflower, CA are hiring for Machine Learning Engineer jobs? Cities near Bellflower, CA with the most Machine Learning Engineer job openings:
Machine Learning Engineer jobs near you
Infographic showing various Machine Learning Engineer job openings in Bellflower, CA as of June 2026, with employment types broken down into 100% Full Time. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $134,560 per year, or $64.7 per hour.
Machine Learning Engineer

Machine Learning Engineer

Prosum Inc.

CA • On-site

$75 - $89/hr

Contractor

Posted 7 days ago

Job description

Job Description
Machine Learning Engineer
Pay Rate: $75-$89/hour
Position Summary
We are seeking a skilled Machine Learning Engineer (MLOps) to support the full lifecycle of machine learning models, including design, development, deployment, and maintenance. This role focuses on building scalable, production-ready AI/ML solutions and ensuring seamless integration within existing systems.
The ideal candidate will collaborate with cross-functional teams to deploy, monitor, and optimize machine learning models that drive operational efficiency, innovation, and data-driven decision-making. This position requires strong experience in MLOps, DevOps practices, and cloud-based AI infrastructure.
Key Responsibilities
  • Design, build, deploy, and maintain machine learning models in production environments
  • Develop and manage end-to-end MLOps pipelines, including model versioning, monitoring, and automation
  • Implement scalable ML infrastructure using cloud platforms (AWS, Azure, or GCP)
  • Build and optimize CI/CD pipelines for automated testing and deployment of ML models
  • Collaborate with data scientists, data engineers, and DevOps teams to operationalize AI solutions
  • Monitor model performance, system health, and data drift; implement logging and alerting solutions
  • Ensure reliability, scalability, and performance of ML systems in real-time inference environments
  • Maintain version control for models and code to support reproducibility and collaboration
  • Apply best practices for testing, debugging, and performance optimization
  • Ensure compliance with data security, privacy, and regulatory standards
  • Create and maintain technical documentation for ML systems and processes
Required Qualifications
  • Bachelor's degree in Computer Science, Engineering, Artificial Intelligence, or a related field
  • 3+ years of experience in machine learning engineering or MLOps
  • Hands-on experience managing the end-to-end machine learning lifecycle
  • Strong programming skills in Python, R, and/or SQL
  • Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform
  • Experience with containerization (Docker) and orchestration tools (Kubernetes)
  • Experience with infrastructure as code tools such as Terraform
  • Experience building and maintaining CI/CD pipelines (e.g., GitHub Actions)
  • Strong understanding of software development, system architecture, and deployment processes
  • Experience with monitoring, logging, and performance tuning of ML systems
  • Knowledge of version control systems (e.g., Git)
Preferred Qualifications
  • Master's degree in Computer Science, Engineering, or a related field
  • Experience working with healthcare data or regulated environments
  • Familiarity with Electronic Health Record (EHR) systems
  • Experience with predictive modeling, natural language processing (NLP), and large language models (LLMs)
  • Knowledge of retrieval-augmented generation (RAG) frameworks and their applications
  • Understanding of agile methodologies and DevOps lifecycle practices
Core Competencies
  • Production-grade ML model deployment and lifecycle management
  • Scalable infrastructure design for AI/ML workloads
  • Cross-functional collaboration and technical leadership
  • Strong analytical and problem-solving skills
  • Effective technical communication and documentation

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