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Weekend Machine Learning Jobs in Dublin, CA (NOW HIRING)

Goodfire

Machine Learning Engineer

San Francisco, CA · On-site

The Machine Learning Engineer will play a central role in building the core technology for training, evaluating, and deploying interpretable frontier AI systems, contributing to tools, infrastructure ...

Gotion, Inc.

Machine Learning Engineer

Fremont, CA · On-site

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 ...

Goodfire

Machine Learning Engineer

San Francisco, CA · On-site

They are seeking Machine Learning Engineers to build their platform for training, evaluating, and deploying interpretable AI systems at scale, contributing to the development of key technologies and ...

Goodfire

Machine Learning Engineer

San Francisco, CA · On-site

They are seeking a Machine Learning Engineer to contribute to the development of tools and infrastructure for interpretable AI systems, playing a key role in transforming research into usable product ...

Apple

Machine Learning FEA Engineer

San Francisco, CA · On-site

We are committed to pushing the boundaries of innovation and engineering excellence in product designs through machine learning and FEA simulations. We truly believe in the power of predictive ...

Canals

Machine Learning Engineer

San Francisco, CA · Remote

We're looking for a senior-level Machine Learning Engineer who can move quickly while maintaining high quality, owning end-to-end ML pipelines while shaping product features that deliver real-world ...

Eve

Machine Learning Engineer

San Francisco, CA · On-site

We're hiring an Machine Learning Engineer as the volume and complexity of legal AI workflows in our system scale rapidly. As more firms rely on Eve to automate high-stakes legal work - from intake ...

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

Apple Inc.

Machine Learning FEA Engineer

San Francisco, CA · On-site

$150.40 - $277.60/hr

The machine learning models will drive rapid design iterations by assessing potential risks and optimizing design trade-offs. You will be fully integrated with the product design team from the ...

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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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