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60 Argo Ai Machine Learning Engineer Jobs Hiring Near You

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 ...

BeeGenius

AI/Machine Learning Engineer

Sunnyvale, CA · On-site

Bee Genius is building the future of work and is seeking an AI/Machine Learning Engineer to join their team. The role involves developing and implementing machine learning models and algorithms to ...

CyberMedia Technologies

AI / Machine Learning Engineer

$117K - $140K/yr

We are seeking to hire a AI/Machine Learning Engineer to our team! Role Overview: As an AI/ML Engineer for CTEC, you will develop Agentic AI systems designed to automate and optimize health benefits ...

SynergisticIT

AI & Machine Learning Engineer

Seattle, WA · On-site

$130K - $156K/yr

We Focus on Java /Full stack/Devops and Data Science /Data Engineers/Data analysts/BI Analysts/ Machine learning/AI candidates Ideal Candidates: * Recent grads in CS, Engineering, Math, or Statistics ...

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AI/Machine Learning Engineer

4 Staffing Corp

Fremont, CA • On-site

Full-time

Re-posted 15 days ago

Job description

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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