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Machine Learning Engineer Opt Jobs in Santa Clara, CA

NR Consulting

Machine Learning Engineer

Fremont, CA · On-site

NR Consulting is a company focused on innovative technology solutions, and they are seeking a Machine Learning Engineer to develop and deploy lightweight machine learning models for edge AI ...

Skild AI

Machine Learning Engineer

San Mateo, CA · On-site

Position Overview We are looking for a Machine Learning Engineer to be responsible for designing and implementing cutting-edge reinforcement learning algorithms, conducting experiments, and ...

Adobe

Machine Learning Engineer

San Jose, CA · On-site

Position: 2026 Machine Learning Engineer Req ID: Pending Location: San Jose Our Company Changing the world through digital experiences is what Adobe's all about. We give everyone-from emerging ...

Abaka AI

Machine Learning Engineer

Mountain View, CA · On-site

They are seeking a Machine Learning Engineer to design and develop scalable training pipelines for multimodal AI systems, collaborating with data engineering and research teams to drive the technical ...

BeeGenius

AI/Machine Learning Engineer

Sunnyvale, CA · On-site

BeeGenius is building the future of work, and they are seeking an AI/Machine Learning Engineer to join their team. In this role, you will be responsible for developing and implementing machine ...

Apple

Machine Learning Engineer (Search)

Cupertino, CA · On-site

We are looking for a Machine Learning Engineer to join and play a big part in the next revolution of Maps; to enable users to find more things in innovative ways. On our team, you will have plenty of ...

Apple Inc.

Machine Learning Engineer

Sunnyvale, CA · On-site

$150.40 - $277.60/hr

Description Apple's Video Computer Vision (VCV) Face and Body technologies team is looking for a skilled Machine Learning Engineer with experience developing ML models for computer vision and ...

Proofpoint

Machine Learning Engineer

Sunnyvale, CA

Machine Learning Engineer Location : Sunnyvale, CA, USA, Hyderabad, A.P., India , Athens, Greece Role Overview: Proofpoint is building the next generation of AI-powered security systems to protect ...

New

Abaka AI

Machine Learning Engineer

Mountain View, CA · On-site

The Machine Learning Engineer will design and develop scalable training pipelines for multimodal AI systems, collaborate with data engineering and research teams, and influence core decisions around ...

Apple

Machine Learning Engineer

Santa Clara, CA

$150K - $277K/yr

Our team comprises a diverse range of backgrounds, including applied machine learning engineers with a focus on ML and LLM, and experienced distributed systems engineers. As such, we are seeking ...

Nace AI

Machine Learning Engineer

Palo Alto, CA · On-site

Nace AI is a company focused on machine learning solutions, and they are seeking a Machine Learning Engineer to translate cutting-edge research into scalable, production-ready solutions. The role ...

Gotion, Inc.

Machine Learning Engineer

Fremont, CA

Role Summary We are seeking a highly motivated Machine Learning Engineer with a strong background in model architecture design and algorithm development, ideally with experience in scientific domains ...

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Showing results 21-40

All JobsMachine Learning Engineer Opt JobsMachine Learning Engineer Opt Jobs in Santa Clara, CA

Machine Learning Engineer Opt information

See Santa Clara, CA salary details

$37K

$151.2K

$227.3K

How much do machine learning engineer opt jobs pay per year?

As of Sep 5, 2026, the average yearly pay for machine learning engineer opt in Santa Clara, CA is $151,231.00, according to ZipRecruiter salary data. Most workers in this role earn between $119,200.00 and $182,000.00 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 into production environments. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, reliable systems that organizations can use to make predictions or automate tasks. Their responsibilities include data preprocessing, choosing appropriate algorithms, model training, and ensuring the model's performance in real-world applications. Machine Learning Engineers often collaborate with data scientists, data engineers, and product teams to deliver intelligent solutions.

What are some common challenges machine learning engineers face when deploying models to production environments?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, handling data drift, and integrating models seamlessly with existing systems when deploying to production. Monitoring model performance in real time and retraining models as new data becomes available are also critical tasks. Collaboration with data engineers and DevOps teams is essential to address infrastructure and deployment hurdles while maintaining model accuracy and reliability.

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 a solid background in mathematics, statistics, and programming (especially Python), typically supported by a degree in computer science, engineering, or a related field. Familiarity with machine learning frameworks (such as TensorFlow, PyTorch), data processing tools, and cloud platforms, along with relevant certifications, is highly valuable. Strong problem-solving ability, collaboration, and effective communication are standout soft skills in this role. These skills and qualities ensure the successful development, deployment, and integration of machine learning solutions that drive business value.

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

AspectMachine Learning Engineer OptData Scientist
Required CredentialsBachelor's or Master's in CS, AI, or related fields; certifications in ML toolsBachelor's or Master's in CS, Statistics, or related fields; data analysis certifications
Work EnvironmentDevelops, tests, and deploys ML models in production systemsAnalyzes data, builds models, and provides insights for decision-making
Employer & Industry UsageTech companies, AI startups, e-commerce, financeResearch institutions, tech firms, consulting, finance
Common Search & ComparisonOften compared for technical skills and deployment focusCompared for data analysis and business insights

Machine Learning Engineers Opt focus on deploying scalable ML models in production environments, while Data Scientists primarily analyze data and develop models for insights. Both roles require strong technical skills, but their core responsibilities differ in application and deployment.

What are popular job titles related to Machine Learning Engineer Opt jobs in Santa Clara, CA?

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

What job categories do people searching Machine Learning Engineer Opt jobs in Santa Clara, CA look for?

The top searched job categories for Machine Learning Engineer Opt jobs in Santa Clara, CA are:

What cities near Santa Clara, CA are hiring for Machine Learning Engineer Opt jobs?

Cities near Santa Clara, CA with the most Machine Learning Engineer Opt job openings:

Machine Learning Engineer Opt jobs near you
Infographic showing various Machine Learning Engineer Opt job openings in Santa Clara, CA as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $151,231 per year, or $72.7 per hour.

AI/Machine Learning Engineer

4 Staffing Corp

Fremont, CA • On-site

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

AI/Machine Learning Engineer

Fremont, CA, United States

About the Job

Our client is seeking a highly skilled and motivated AI/Machine Learning Engineer to join their team. As an AI/Machine Learning Engineer, you will play a crucial role in developing and implementing cutting-edge machine learning algorithms and AI models to solve complex problems and drive innovation. You will work closely with a cross-functional team of data scientists, software engineers, and domain experts to design, train, evaluate, and deploy machine learning models in production environments.

Responsibilities

  • Design and develop machine learning models and algorithms for various applications, such as natural language processing, computer vision, predictive analytics, and recommendation systems.
  • Collaborate with data scientists, software engineers, and domain experts to understand project requirements, identify data sources, and define appropriate machine learning approaches.
  • Preprocess and clean large datasets to extract relevant features and optimize model performance.
  • Implement and fine-tune machine learning models using popular frameworks and libraries, such as TensorFlow, PyTorch, or scikit-learn.
  • Conduct experiments to evaluate model performance, analyze results, and iterate on model designs to achieve optimal accuracy, efficiency, and scalability.
  • Collaborate with software engineering teams to integrate machine learning models into production systems and deploy them at scale.
  • Monitor and maintain deployed models, ensuring their performance and reliability over time.
  • Stay up to date with the latest advancements in machine learning and AI technologies, and proactively propose innovative solutions and improvements.

Requirements

  • Bachelor's or Master's degree in Computer Science, Engineering, or a related field. A Ph.D. is a plus.
  • Strong background in machine learning, artificial intelligence, and statistical analysis.
  • Demonstrated experience in designing, developing, and deploying machine learning models and algorithms.
  • Proficiency in programming languages such as Python, R, or Java, with a solid understanding of data structures, algorithms, and software engineering principles.
  • Hands-on experience with popular machine learning frameworks and libraries, such as TensorFlow, PyTorch, or scikit-learn.
  • Familiarity with deep learning techniques and frameworks, such as convolutional neural networks (CNNs) and recurrent neural networks (RNNs).
  • Experience with data preprocessing, feature engineering, and model evaluation techniques.
  • Strong analytical and problem-solving skills, with the ability to think critically and creatively to tackle complex challenges.
  • Excellent communication and collaboration skills, with the ability to work effectively in cross-functional teams.
  • Ability to adapt quickly to new technologies and methodologies in the rapidly evolving field of AI and machine learning.

Preferred Qualifications

  • Experience with cloud platforms (e.g., AWS, Azure, or GCP) and distributed computing frameworks (e.g., Apache Spark) for training and deploying machine learning models at scale.
  • Knowledge of big data technologies, such as Hadoop and Spark, for processing and analyzing large datasets.
  • Experience with computer vision, natural language processing, or other specialized domains within AI/ML.
  • Publications or contributions to the AI/ML community, such as research papers or open-source projects.

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