Machine Learning Engineer Jobs in California

In the colorful tech field of California, the number of machine learning engineer opportunities is mind-blowing. Along with having pioneer companies, new startups, and famous research institutions, California provides a dynamic environment for those who are devoted to artificial intelligence and data science. From Silicon Valley to San Francisco and surrounding areas, the state offers the fertile grounds for innovative technologies where one can be a part of leading projects that address the intricate problems and contribute to the future of machine learning.

1. Google

Requirements:

• Developing proficiency in Python and Java.
• Become a pro user of machine learning frameworks including TensorFlow or PyTorch.
• Outstanding the knowledge of algorithms and data structures.
• At least a master’s degree in computer science, engineering or related field should preferably be attained.

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2. Facebook

Requirements:

• Tactics like classification, regression, clustering, reinforcement learning and others.
• Accumulated experience in high-scale data processing using tools i.e. Hadoop, Spark, or Flink.
• The knowledge of at least one programming language like Python, C++, or Java should be deep.
• Skills in working with other teams across departments and delivering complex ideas clearly and sensefully.

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3. Apple

Requirements:

• Deeper comprehension of statistical model, machine learning algorithm and data analysis methods.
• Proficiency in the languages of these programmes, such as Python, Swift, and Objective C.
• Acing basic programming skills with deep learning frameworks such as Keras, TensorFlow, and PyTorch.
• Awareness of the cloud environment and a understanding of the concepts of distributed systems as well is important.

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4. Amazon

Requirements:

• I have gained first hand experience in model building and deployment at scale.
• Broad understanding of computer science basic principles and software engineering theory.
• Knowing about AWS infrastructure components such as SageMaker, Lambda, and S3.
• Fantastic problem-solving competences and skills to work in the rapidly changing environment.

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5. NVIDIA

Requirements:

• An ability to use GPU and parallel programming.
• Mastering of machine learning frameworks such as cuDNN, TensorFlow, and PyTorch.
• They have a deep expertise in different deep learning approaches such as CNNs and RNNs.
• Master in computer science, electrical engineering, or related program is preferable.

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6.Netflix

Requirements:

• The applicant excelled in statistics, math, or related quantitative disciplines during his schooling.
• The applications like recommendation systems, natural language processing or computer vision.
• An ability to work in particular programming languages (Python, Scala, or Java, for instance) is a must.
• The skills of working with people in different departments and achieving common ambitious goals.

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7. Uber

Requirements:

• Research on machine learning algorithms, data science, and data analysis data.
• Our knowledge of utilizing big data technology such as Apache Spark and Hadoop will help us to establish a proper and professional Data Science team for our organization.
• Mastery in certain programming languages like Python, R, or Scala are required.
• Good communication skills and ability to explain the business needs to the related technical styles in details.

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8. LinkedIn

Requirements:

• Deep understanding of various machine learning techniques and algorithms.
• Sufficient understanding of components of distributed computing frameworks like Apache Hadoop or Spark.
• Mastery of programming languages like Java, Ptyhon, or Scala (can be mentioned).
• Enhanced analytical thinking and issues solution mastery.

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9. X

Requirements:

• The knowledge of machine learning libraries such as TensorFlow, PyTorch and scikit-learn is important.
• Get familiarity with NLP and text mining utilities.
• Familiarity with programming languages like Python, Java, or Scala are essential competencies.
• Competence in working in a busy environment alongside various colleagues.

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10. Adobe

Requirements:

• The essential that is also here include machine learning, data mining, statistics.
• Deep learning education pyramid is a wide knowledge base that allows you to get an extensive startup in frameworks such as TensorFlow, Keras, and PyTorch.
• An ability to effectively use programming languages like Python, Java, or C++ as among the important skills required for this type of roles.
• Proper communicational and interpersonal traits are vital.

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11. Intel

Requirements:

• Intelligibility with and mastery of machine learning mathematical models and methods.
• The familiarization of FPGA hardware or Intel Movidius boards to me was a completely new experience.
• Knowledge of programming languages like Python, C++ or Java will do the trick if you are saying yes to these.
• The exceptional flair of expressions and adaptability in diverse situations performing tasks.

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12. Airbnb

Requirements:

• Finding out about Machine Learning methods like supervised learning, unsupervised learning & reinforcement learning, etc.
• Engaging with big data processing frameworks (e.g. Apache Spark, Hadoop) was also very important part of my career development.
• Familiarity with these programming languagessuch as Python, Scala, or Java.
• Being self-reliant and part of a team at work in a highly-dynamic surrounding.

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13. Salesforce

Requirements:

• Mastering various machine learning algorithms and techiques is also important.
• Experience in clouds platform like Salesforce Einstein or AWS allows me to learn the skills used when creating and deploying enterprise-grade applications.
• Knowing programming languages such as Python, Jave or Scala.
• Sharpen spatial/mechanical and logical/problem-solving abilities.

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14. Intuit

Requirements:

• By hand-on experience in building and deploying machine learning models, it’s be possible to gain a deeper knowledge of production level.
• For instance, fluency in programming languages, such as Python, Java, or Scala, are typical.
• These technologies achieve scalability by distributing the processing of data over large numbers of computers (Apache Hadoop, Spark, et al).
• These weak joints can render the bridges unsafe for vehicles, typically trucks, to use efficiently.

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15. Cisco

Requirements:

• These techniques of machine learning should be in engineering for learning algorithms such as supervised, unsupervised and deep learning.
• Skill on the creation of information storing solution such as Hadoop, Spark , and Kafka.
• Knowing how to professionally use programming languages like Python, Java or Scala.
• A special quality that will facilitate the quick workarounds of the ever-evolving puzzles and the ability to work together with professionals in other departments.

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16. PayPal

Requirements:

• Seeing the mechanics behind the scenes and the core principles of machine learning algorithms and methods.
• Trying out third-party software like Hadoop, Spark, and Hive is also part of getting acquainted with big data technology.
• Programming languages such as Python, Java, and Scala being a core skillset gives one an advantage to work on different kinds of projects.
• Flexibility to handle a high speed, teammate nature of work.

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17. Lyft

Requirements:

• Proficiency in different machine learning strategies, i.e., supervised learning, unsupervised learning, and reinforcement learning are of great care.
• Having worked with data processing frameworks like Apache Spark or Hadoop which are widely used in the field makes me a great candidate for this position.
• Proficiency in programming languages such as python, Scala or Java is necessary in order to be able to perform various analytics tasks.
• Excellent communication and team work are nut important for success in this position.

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18. Square

Requirements:

• Good understanding about machine learning, data mining, and statical analysis.
• Exposure to deep learning frameworks like TensorFlow, Keras, or PyTorch being examples.
• Fluency in programming languages can be achieved with the skills that combine such sets as the instances of Python, Java or C++.
• Listening and critical thinking skills with the ability to work under pressure will be among my strengths.

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19. Dropbox

Requirements:

• An ingrained capamity of machine learning algorithms and methods.
• Knowledge in a working with big data processing platforms like Apache Spark, or Apache Hadoop ecosystem.
• Programming skills in languages, Pyhon, Scala, or Java, among others.
• The ability to think analytically and to approach and solve problems quickly is another robust skill needed by future leaders.

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20. eBay

Requirements:

• This includes surgical devices utilizing machine learning techniques like supervised learning, unsupervised learning, and reinforcement learning.
• The big data experience would include a good understanding of technologies like Hadoop, Spark, or Kafka.
• The adopted programming language(s) should include Python, Java, and Scala alternatives.
• Highly effective communication and collaboration teamwork and individuals’ skills.

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21. Oracle

Requirements:

• Not only deep understanding of machine learning algorithms and techniques, but also learning the theory of how the algorithms work is necessary.
• Let us use Courses such as Oracle Cloud services or AWS to experience them.
• One must also be efficient in the programming languages, e.g. Python, Java, or Scala.
• First end is data collection and analysis that enables to generate models, identify patterns, test hypotheses, and create solutions.

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22. Tesla

Requirements:

• Machines learning practices including algorithms examples which are supervised learning, unsupervised learning and reinforcement learning.
• Processing experience with well-known big data processing systems like Spark or Hadoop.
• Proficientness in programming languages like Python, Scala, or Java, the most popular programming languages in this field.
• Skill of working independently as well as a team without succumbing to pressure in a high-speed environment.

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23. Twitch

Requirements:

• Great deal of experience on the fields of machine learning, data mining, and statistics.
• The familiarity with libraries for deep learning like TensorFlow, Keras, and PyTorch.
• Language proficiency in programming languages like Python, Java, or C++ is a must skill needed to create quality software.
• Outstanding communication and proven teamwork cultivation skills.

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24. Palantir Technologies

Requirements:

• Proficiency in the machine learning techniques like supervised learning, unsupervised learning and reinforcement learning would be the key skill set.
• Knowledge of big data processing frameworks like Apache Spark and Hadoop can be added as a skill.
• Single-handedly triumphing in languages like Python, Java, or Scala is just an example.
• High communication and interpersonal skills ​.

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25. Genentech

Requirements:

• Deeper knowledge in the machine learning algorithm and techniques are the biggest inputs.
• Practical knowledge of bioinformatics or computational biology solutions to fall within this description.
• Acquaintance with programming languages, Python, R, and MATLAB.
• The ability to analyze well and the ability to solve problems.

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Here are given some popular job portals to efficiently discover your ideal job.

• LinkedIn Jobs
• Indeed
• Glassdoor
• Naukri.com

The mean compensation of a Machine Learning Engineer depends on whether he/she is based in a metropolitan city or a smaller town as well as on other factors such as of the length of work experience, schooling level and specific industry. Notwithstanding, as partly was in January 2022, the average annual salary for Machine Learning Engineer usually goes from $100,000 to $160,000 USD.

1. Entry-Level:

• At the same time, entry-level machine learning engineers normally have not worked much, meaning that they have 0-2 years of professional experience.

2. Mid-Level:

• Having 2 to 5 years of experience is common among the mid-level machine learning engineers.

3. Experienced:

• Experienced machine learning engineers are practiced in machine learning field for up to 5 years or more.

4. Senior/Lead:

• The senior or lead machine learning engineers are senior professionals who have a lot of experience and can show what they succeeded in.

What is the educational background that I need to attain if I want to become a Machine Learning Engineer in California?

The minimum qualification of a bachelor’s or master’s degree in computer science, data science, mathematics, or related field is applied along with programming languages proficiency such as Python or R and experience with machine learning frameworks like TensorFlow or PyTorch.

The most important industry in California where Machine Learning (ML) engineers are hired is information technology?

Maleine learning enginners position themselves highly demanded profession in the many sectors of the California, such as tech, healthcare, finance, e-commerce, entertainment and so on.

What are some of the different roles of machine learning in the area of medical tourism in California?

California Machine Learning Engineers are known for their contribution in designing and implementing machine learning models, analyzing data, to collaborating with different departments and for their constant update on the latest trends and technologies.

Salary levels for Machine Learning Engineers in California is another factor that you might be interested in.

CA offers 120,000-180,000 salary per year taking into account such features as experience, educational background, exact location and size of company.

As for the skills that would be of use to a Machine Learning Engineer in California, what specific ones can be incorporated to improve the prospects?

Competence in deep learning, natural language processing, computer vision, and cloud computing will give you better odds, plusbada certiac nprominent institutions like Coursera, Udacity, and AWS.