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Open nowFirst seen 43 hours ago

AI/Machine Learning Engineer

4 Staffing Corp95 open roles

Where
Fremont, CA, United States
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Your applicationOpen nowAI/Machine Learning Engineer4 Staffing Corp · Fremont, CA, United States

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on 4 Staffing Corp's own form.

The reply lands in your private mailbox

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The clock on this job

Early applications get read.

11.8% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
  1. 2.1%1 day
  2. 4.4%3 days
  3. 11.8%7 days
  4. 18.6%14 days
  5. 35.6%30 days
  6. 45.1%60 days
This job: first seen 43 hours ago

The posting

Job Description: 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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