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Machine Learning Algorithms Jobs in California (NOW HIRING)

Manage machine learning algorithm lifecycle. * Coordinate data collection and annotation efforts. * Work with real-time data and content coming from various data sources. * Manage machine learning ...

The ideal candidate will have strong expertise in machine learning algorithms, data engineering, model deployment, and cloud technologies. Key Responsibilities: * Design, develop, and deploy machine ...

Manage machine learning algorithm lifecycle. * Coordinate data collection and annotation efforts. * Work with real-time data and content coming from various data sources. * Manage machine learning ...

Machine Learning Engineer San Mateo, Pittsburgh Company Overview At Skild AI, we are building the ... Develop and implement state-of-the-art reinforcement learning algorithms for robotic applications.

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 ...

Our mission is to pioneer success stories through the application of generative AI and state-of-the-art machine learning algorithms, thereby generating transformative business and societal impact.

Description In this role, you will innovate foundational machine learning algorithms for computational photography and computer vision, to research, design and qualify novel cameras and sensors for ...

In this role, you will innovate foundational machine learning algorithms for computational photography and computer vision, to research, design and qualify novel cameras and sensors for future Apple ...

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Machine Learning Algorithms information

What are machine learning algorithms?

Machine learning algorithms are computational methods that enable computers to learn patterns and make decisions or predictions from data without being explicitly programmed for each task. These algorithms can be classified into categories such as supervised learning, unsupervised learning, and reinforcement learning, each suited for different data and goals. Examples include decision trees, support vector machines, neural networks, and clustering algorithms. The choice of algorithm depends on the type of problem, the nature of the data, and the desired outcome.

What are the key skills and qualifications needed to thrive as a Machine Learning Algorithms Engineer, and why are they important?

To excel as a Machine Learning Algorithms Engineer, you need a solid background in mathematics, statistics, programming (especially Python or R), and a relevant degree in computer science or a related field. Familiarity with machine learning frameworks (like TensorFlow, PyTorch, or scikit-learn), data preprocessing tools, and cloud platforms is typically required, along with knowledge of version control systems. Strong analytical thinking, problem-solving abilities, and effective communication skills set top performers apart in this role. These skills and qualities are critical for designing robust models, collaborating with cross-functional teams, and translating complex data into actionable solutions.

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-demand industries or at large tech companies can earn salaries of $500,000 or more, including base pay, bonuses, and stock options. Achieving this level typically requires a strong educational background, specialized certifications, and a track record of successful projects.

Which 3 jobs will survive AI?

Machine learning engineers, data scientists, and AI specialists are likely to continue thriving as AI advances because they develop, interpret, and improve AI systems. These roles require specialized skills in programming, statistical analysis, and domain expertise that are difficult to fully automate. Continuous learning and staying updated with new tools like TensorFlow or PyTorch are essential for these jobs.

What is the difference between Machine Learning Algorithms vs Data Scientists?

AspectMachine Learning AlgorithmsData Scientists
CredentialsKnowledge of algorithms, programming, statisticsAdvanced degrees in data science, statistics, or related fields
Work EnvironmentDeveloping, testing, and tuning algorithmsAnalyzing data, building models, interpreting results
Industry UsageEmbedded within data science workflows and toolsLeading data analysis projects, decision-making

While machine learning algorithms are the core tools used by data scientists, the role of a data scientist encompasses understanding, applying, and interpreting these algorithms within broader data analysis and business contexts. Machine learning algorithms are technical components, whereas data scientists integrate these tools to derive insights and inform strategies.

Is ML a high paying job?

Machine Learning (ML) jobs are generally well-paid due to the specialized skills required, such as programming, data analysis, and knowledge of algorithms. Salaries vary based on experience, location, and industry, but many ML roles offer competitive compensation compared to other tech positions.

What is a $900,000 AI job?

A $900,000 AI job typically refers to high-level roles in artificial intelligence, such as senior machine learning engineers, AI research directors, or chief AI officers, often requiring advanced skills in algorithms, data science, and deep learning. These positions usually involve leadership responsibilities, extensive experience, and may be located in competitive tech hubs or large organizations with substantial AI investments.

What are some common challenges faced when collaborating with cross-functional teams as a Machine Learning Algorithms specialist?

As a Machine Learning Algorithms specialist, collaborating with cross-functional teams such as data engineers, software developers, and product managers can present challenges like aligning on project goals, communicating complex technical concepts to non-experts, and integrating models into existing systems. It's important to establish clear communication channels, define shared objectives early, and actively participate in iterative feedback cycles. These practices help ensure that machine learning solutions are both technically sound and aligned with business needs.
What job categories do people searching Machine Learning Algorithms jobs in California look for? The top searched job categories for Machine Learning Algorithms jobs in California are:
Deep Learning Engineer - Perception Algorithms

Deep Learning Engineer - Perception Algorithms

Apple

Sunnyvale, CA

$147K - $272K/yr

Full-time

Medical, Dental, Retirement

Posted 12 days ago


Apple rating

8.1

Company rating: 8.1 out of 10

Based on 661 frontline employees who took The Breakroom Quiz

6th of 30 rated technology retailers


Job description

Do you have a passion for deep learning and computer vision problems? We are looking for someone who thrives on collaboration and wants to push the boundaries of what is possible today!
Join our team of committed deep learning engineers in the Video Computer Vision group! We are a centralized applied research and engineering organization responsible for developing real-time on-device Computer Vision, Machine Perception, and Generative technologies across Apple products. Our shipped technologies power features in ARKit, MeasureApp, RoomScan, Accessibility, and multiple VisionPro features.
As a member of the Video Computer Vision group you will develop new technologies in the area of scene understanding and for Apple’s next generation products.
Description
We are looking for a skilled Deep Learning Engineer for our team. In this role, you will perform research and development work to design algorithms for challenging real world problems in the domain of scene understanding.","responsibilities":"Data curation for improving performance on perception tasks (training and evaluation sets).
Research, design, train, and evaluate machine learning/deep learning algorithms to address product goals.
Benchmark and analyze machine learning/deep learning algorithms to understand limitations.
Optimize algorithms for real time and low power constraints.
Support algorithm integration into Apple products and ensure quality user experience.
Collaborate with teams across Apple with multidisciplinary skills.
Preferred Qualifications
PhD degree with focus on machine learning, computer vision, robotics or MS with a comparable industry career of 3+ years.
Consistent track record of researching, inventing and/or shipping advanced machine learning algorithms.
Experience in language-guided image understanding tasks e.g. open-vocabulary image classification, language-guided visual grounding, open-vocabulary semantic segmentation, etc.
Experience with designing and training with pipelines which consume large (billion scale) data for training efficient vision language models for edge-devices. This includes data curation for training vision language models, writing efficient data loading pipelines, utilizing distributed GPU training framework.
Experience with advanced task-specific quality optimization techniques (few-shot learning, meta-learning, domain adaptation, knowledge-distillation, fine-grained learning) for improving network performance and handling specific failure cases (long-tailed distributions/under-represented classes) for downstream tasks.
Experience in designing and optimizing network towards inference efficiency.
Strong coding skills in ObjectiveC.
Excellent communication and collaboration skills.
Minimum Qualifications
BS in Computer Science or related field with a minimum of 3 years of relevant industry experience.
Experience in designing and training deep learning networks for image understanding tasks, e.g. image classification, object detection, semantic segmentation, panoptic segmentation, etc.
Experience in developing downstream perception algorithms with vision-language models, e.g. CLIP
Solid mathematical foundation of machine learning and deep learning techniques.
Strong coding skills in python (with pytorch) and C/C++. Solid mathematical foundation of machine learning and deep learning techniques.
Pay & Benefits
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $147,400 and $272,100, and your base pay will depend on your skills, qualifications, experience, and location.
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

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About Apple

Sourced by ZipRecruiter

Imagine what you could do here! At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Dynamic, intelligent people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same real passion for innovation that goes into our products also applies to our practices strengthening our dedication to leave the world better than we found it.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Cupertino, CA, US

Year founded

1976