Senior AI/ML Engineer, Computer Vision
Our client, a rapidly growing AI startup specializing in cutting-edge computer vision solutions, is seeking a talented Senior AI/ML Engineer to join their innovative team in San Antonio, Texas, US . This hybrid role offers the opportunity to work on challenging projects that push the boundaries of artificial intelligence. You will be responsible for designing, developing, and deploying advanced machine learning models, with a particular focus on computer vision applications. This includes tasks such as object detection, image segmentation, facial recognition, and video analysis.
The ideal candidate will have a strong foundation in machine learning algorithms, deep learning frameworks (e.g., TensorFlow, PyTorch), and experience with large-scale datasets. You will work closely with data scientists, software engineers, and product managers to translate business requirements into robust AI solutions. Responsibilities include data preprocessing and augmentation, model training and evaluation, performance optimization, and integration into production systems. Experience with cloud platforms (AWS, Azure, GCP) and MLOps practices is highly desirable. You will also contribute to research efforts, staying abreast of the latest advancements in AI and computer vision.
Key Responsibilities:
Design, develop, and implement state-of-the-art machine learning models for computer vision tasks. Perform data collection, preprocessing, annotation, and augmentation to prepare datasets for training. Train, evaluate, and optimize deep learning models using frameworks like TensorFlow and PyTorch. Deploy ML models into production environments, ensuring scalability and reliability. Develop and maintain ML pipelines and MLOps infrastructure. Collaborate with cross-functional teams to define project requirements and deliver AI solutions. Conduct research on new AI techniques and algorithms, and assess their applicability. Optimize model performance for speed, accuracy, and resource efficiency. Troubleshoot and resolve issues related to ML model deployment and performance. Contribute to the continuous improvement of the AI/ML platform and best practices.
Qualifications:
Master's or Ph.D. in Computer Science, Electrical Engineering, or a related quantitative field. 5+ years of professional experience in AI/ML engineering, with a strong focus on computer vision. Proficiency in Python and relevant ML libraries (e.g., Scikit-learn, OpenCV). Deep understanding of deep learning architectures (CNNs, RNNs, Transformers). Experience with cloud platforms (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes). Familiarity with MLOps principles and tools (e.g., MLflow, Kubeflow). Strong analytical and problem-solving skills. Excellent communication and teamwork abilities. Experience with large-scale data processing frameworks (e.g., Spark) is a plus. This hybrid role provides a fantastic opportunity to work with a talented team on cutting-edge AI technology. We offer a competitive salary, stock options, and a comprehensive benefits package, along with professional development opportunities.
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The ideal candidate will have a strong foundation in machine learning algorithms, deep learning frameworks (e.g., TensorFlow, PyTorch), and experience with large-scale datasets. You will work closely with data scientists, software engineers, and product managers to translate business requirements into robust AI solutions. Responsibilities include data preprocessing and augmentation, model training and evaluation, performance optimization, and integration into production systems. Experience with cloud platforms (AWS, Azure, GCP) and MLOps practices is highly desirable. You will also contribute to research efforts, staying abreast of the latest advancements in AI and computer vision.
Key Responsibilities:
Design, develop, and implement state-of-the-art machine learning models for computer vision tasks. Perform data collection, preprocessing, annotation, and augmentation to prepare datasets for training. Train, evaluate, and optimize deep learning models using frameworks like TensorFlow and PyTorch. Deploy ML models into production environments, ensuring scalability and reliability. Develop and maintain ML pipelines and MLOps infrastructure. Collaborate with cross-functional teams to define project requirements and deliver AI solutions. Conduct research on new AI techniques and algorithms, and assess their applicability. Optimize model performance for speed, accuracy, and resource efficiency. Troubleshoot and resolve issues related to ML model deployment and performance. Contribute to the continuous improvement of the AI/ML platform and best practices.
Qualifications:
Master's or Ph.D. in Computer Science, Electrical Engineering, or a related quantitative field. 5+ years of professional experience in AI/ML engineering, with a strong focus on computer vision. Proficiency in Python and relevant ML libraries (e.g., Scikit-learn, OpenCV). Deep understanding of deep learning architectures (CNNs, RNNs, Transformers). Experience with cloud platforms (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes). Familiarity with MLOps principles and tools (e.g., MLflow, Kubeflow). Strong analytical and problem-solving skills. Excellent communication and teamwork abilities. Experience with large-scale data processing frameworks (e.g., Spark) is a plus. This hybrid role provides a fantastic opportunity to work with a talented team on cutting-edge AI technology. We offer a competitive salary, stock options, and a comprehensive benefits package, along with professional development opportunities.
Apply tot his job
Apply To this Job