Machine Learning Engineer - Computer Vision
Posted 17 days ago
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Principal Machine Learning Engineer - Computer Vision
Posted 3 days ago
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Responsibilities:
- Lead the research, design, and development of state-of-the-art computer vision models.
- Implement and optimize deep learning algorithms for image and video processing tasks.
- Develop and deploy production-ready machine learning pipelines.
- Conduct experiments, analyze results, and iterate on model performance.
- Collaborate with cross-functional teams to define project requirements and deliver solutions.
- Mentor junior machine learning engineers and researchers.
- Stay current with the latest advancements in computer vision and ML research.
- Evaluate and integrate new tools, technologies, and methodologies.
- Present findings and research to technical and non-technical audiences.
Qualifications:
- Ph.D. or Master's degree in Computer Science, Machine Learning, AI, or a related quantitative field.
- 7+ years of experience in machine learning engineering, with a strong focus on computer vision.
- Deep understanding of deep learning concepts and architectures (CNNs, RNNs, Transformers, GANs).
- Proficiency in Python and ML libraries (TensorFlow, PyTorch, Keras, OpenCV).
- Experience with model optimization, deployment, and MLOps.
- Strong background in linear algebra, calculus, and probability.
- Experience with large-scale datasets and distributed training.
- Excellent problem-solving, analytical, and critical thinking skills.
- Strong communication and collaboration abilities.
- Demonstrated ability to lead technical projects and mentor teams.
Principal AI Engineer - Machine Learning
Posted 10 days ago
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Key Responsibilities:
- Lead the research, design, and implementation of sophisticated machine learning models and algorithms.
- Develop and deploy AI-powered applications and systems that solve complex business problems.
- Work with large datasets, ensuring data quality, preprocessing, and feature engineering.
- Utilize deep learning frameworks (e.g., TensorFlow, PyTorch) for model development and optimization.
- Collaborate with cross-functional teams to integrate AI solutions into existing products and services.
- Mentor junior AI engineers, providing technical guidance and support.
- Stay abreast of the latest advancements in AI, machine learning, and related fields.
- Evaluate and select appropriate AI technologies and tools for project needs.
- Develop and implement MLOps strategies for model deployment, monitoring, and maintenance.
- Conduct experiments and fine-tune models for optimal performance and accuracy.
- Communicate complex technical concepts to both technical and non-technical audiences.
Remote Machine Learning Engineer - Computer Vision
Posted 18 days ago
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Responsibilities:
- Develop, train, and deploy machine learning models for computer vision tasks, including image classification, object detection, segmentation, and tracking.
- Design and implement efficient data pipelines for collecting, annotating, and pre-processing large image and video datasets.
- Research and experiment with state-of-the-art computer vision algorithms and deep learning architectures.
- Optimize model performance for inference speed and accuracy on various hardware platforms.
- Collaborate with software engineers to integrate ML models into production systems and applications.
- Stay current with the latest research and developments in the field of computer vision and machine learning.
- Write clean, well-documented, and maintainable code in Python and relevant ML frameworks (e.g., TensorFlow, PyTorch).
- Evaluate and benchmark model performance, providing insights and recommendations for improvement.
- Participate in code reviews and contribute to technical discussions within the team.
- Contribute to the overall MLOps strategy, including model deployment, monitoring, and maintenance.
- Master's or Ph.D. in Computer Science, Electrical Engineering, AI, or a related field with a focus on computer vision.
- 3+ years of experience in developing and deploying computer vision models.
- Strong proficiency in Python and deep learning frameworks such as TensorFlow, PyTorch, or Keras.
- Solid understanding of computer vision fundamentals, including image processing, feature extraction, and object recognition techniques.
- Experience with deep learning architectures like CNNs, RNNs, and Transformers for vision tasks.
- Familiarity with cloud platforms (AWS, GCP, Azure) and ML services is a plus.
- Excellent problem-solving and analytical skills.
- Strong communication and collaboration skills, with the ability to work effectively in a remote team.
- Experience with data augmentation, transfer learning, and model optimization techniques.
Lead AI Engineer - Machine Learning Innovation
Posted 10 days ago
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AI Research Scientist - Machine Learning
Posted 3 days ago
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Principal AI Research Scientist - Machine Learning
Posted 3 days ago
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Lead Machine Learning Engineer - Scalable AI Solutions
Posted 3 days ago
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Principal Research Scientist - AI & Machine Learning
Posted 18 days ago
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Principal AI Engineer, Machine Learning Operations
Posted 10 days ago
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Responsibilities:
- Design, implement, and manage end-to-end MLOps pipelines for automated model training, deployment, and monitoring.
- Develop and maintain infrastructure for managing large-scale datasets and machine learning models.
- Implement CI/CD practices for machine learning models, ensuring efficient and reliable deployment.
- Monitor model performance in production, identify issues, and implement solutions for retraining and optimization.
- Collaborate with data scientists and software engineers to integrate ML models into production systems.
- Develop and manage cloud-based ML platforms and services (e.g., AWS SageMaker, Azure ML, Google AI Platform).
- Implement best practices for model versioning, experiment tracking, and reproducibility.
- Ensure the scalability, reliability, and security of AI/ML infrastructure.
- Contribute to the architectural design of AI systems and platforms.
- Stay abreast of the latest advancements in MLOps, machine learning, and cloud technologies.
- Mentor junior engineers and contribute to the technical vision of the AI team.
- Develop and maintain comprehensive documentation for MLOps processes and infrastructure.
- Master's or Ph.D. in Computer Science, Engineering, Data Science, or a related quantitative field.
- Minimum of 7 years of experience in software engineering or machine learning, with at least 3 years focused on MLOps.
- Proven expertise in building and managing ML pipelines using tools like Kubeflow, MLflow, TFX, or similar.
- Strong proficiency in programming languages such as Python, and experience with ML frameworks like TensorFlow, PyTorch, or scikit-learn.
- Extensive experience with cloud platforms (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes).
- Deep understanding of CI/CD principles and tools (e.g., Jenkins, GitLab CI, CircleCI).
- Experience with data engineering, data pipelines, and database management.
- Excellent problem-solving, analytical, and communication skills.
- Ability to work independently and lead technical initiatives in a remote environment.
- Familiarity with distributed systems and big data technologies.