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VisaSan Francisco
Job Description
Responsibilities
Collaborate with product managers, data scientists, software engineers, and other stakeholders to understand business goals and determine AI requirements.
Design and develop AI architectures, frameworks...
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Compass ConsultingSan Carlos (CA), 21 mi from San Francisco
Our client is a scientific software company that puts world-leading technology and easy-to-use software in the hands of researchers working to understand and battle disease.
Duties:
• Seeking a lab manager for a contract role to handle facilities...
Cygnus Professionals Inc.San Francisco
Responsibilities:
Lead the design of architecture for generative AI solutions within the Azure ecosystem. Collaborate with project managers, data scientists, software engineers, and other stakeholders to understand business goals and determine AI...
BlackLinePleasanton (CA), 32 mi from San Francisco
and applications.
• Monitor and maintain deployed models, making updates as needed.
Collaboration:
• Work closely with cross-functional teams, including data scientists, software engineers, and domain experts, to understand business requirements and develop...
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Deep Learning Engineer
Unreal Gigs | San Francisco | Full-time | apply.workable.com |
Company Overview: Welcome to the forefront of deep learning innovation! At our company, we're driving the next wave of AI revolution through cutting-edge deep learning technologies. Our mission is to develop groundbreaking solutions that solve complex problems and empower businesses across industries.
Join us and be part of a dynamic team committed to pushing the boundaries of what's possible with deep learning.
Position Overview: As a Deep Learning Engineer, you'll play a pivotal role in developing and deploying state-of-the-art deep learning models and systems. Working closely with a multidisciplinary team of researchers, engineers, and domain experts, you'll tackle challenging problems and deliver innovative solutions that make a real impact.
If you're passionate about leveraging deep learning to drive innovation and eager to make a meaningful difference, we want you on our team.
Requirements
Key Responsibilities:
1. Model Development: Design, implement, and optimize deep learning models for a wide range of applications, including image recognition, natural language processing, and autonomous systems.
2. Model Training and Evaluation: Train deep learning models using large-scale datasets, evaluating model performance and iteratively refining approaches to achieve state-of-the-art results.
3. Model Deployment: Architect scalable and reliable deep learning pipelines for deployment in production environments, collaborating with DevOps engineers to ensure seamless integration and monitoring.
4. Data Processing: Develop data pipelines to ingest, clean, and preprocess data for training and evaluation, ensuring data quality and integrity throughout the data lifecycle.
5. Performance Optimization: Optimize deep learning models and systems for speed, efficiency, and scalability, leveraging techniques such as distributed computing and parallel processing.
6. Cross-Functional Collaboration: Collaborate with cross-functional teams, including data scientists, software engineers, and product managers, to define requirements, prioritize tasks, and deliver solutions that meet business objectives.
7. Documentation and Reporting: Prepare documentation and technical reports to communicate model designs, implementation details, and performance metrics to stakeholders, ensuring transparency and reproducibility.
Qualifications:
• Bachelor's degree or higher in Computer Science, Electrical Engineering, Statistics, or related field.
• Strong background in deep learning, with hands-on experience in developing and deploying deep learning models in production environments.
• Proficiency in programming languages such as Python, TensorFlow, PyTorch, or Keras, with experience in data manipulation and analysis.
• Familiarity with deep learning concepts and techniques, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), and transformer models.
• Experience with cloud platforms such as AWS, Azure, or Google Cloud, and proficiency in using relevant tools and services for deep learning development and deployment.
• Strong problem-solving abilities and analytical thinking, with a keen attention to detail and a passion for tackling complex technical challenges.
• Excellent communication and collaboration skills, with the ability to work effectively in cross-functional teams and communicate technical concepts to non-technical stakeholders.
Benefits
• Competitive salary: The industry standard salary for Deep Learning Engineers typically ranges from $150,000 to $230,000 per year, depending on experience and qualifications. Exceptional candidates may be eligible for higher compensation packages.
• Comprehensive health, dental, and vision insurance plans.
• Flexible work hours and remote work options.
• Generous vacation and paid time off.
• Professional development opportunities, including access to training programs, conferences, and workshops.
• State-of-the-art technology environment with access to cutting-edge tools and resources.
• Vibrant and inclusive company culture with team-building activities and social events.
• Opportunities for career growth and advancement within the company.
• Exciting projects with real-world impact across diverse industries.
• Chance to work alongside top talent and industry experts in the field of deep learning.
Join Us: Ready to shape the future of AI with deep learning? Apply now to join our team and be part of an exciting journey of innovation and discovery!
Join us and be part of a dynamic team committed to pushing the boundaries of what's possible with deep learning.
Position Overview: As a Deep Learning Engineer, you'll play a pivotal role in developing and deploying state-of-the-art deep learning models and systems. Working closely with a multidisciplinary team of researchers, engineers, and domain experts, you'll tackle challenging problems and deliver innovative solutions that make a real impact.
If you're passionate about leveraging deep learning to drive innovation and eager to make a meaningful difference, we want you on our team.
Requirements
Key Responsibilities:
1. Model Development: Design, implement, and optimize deep learning models for a wide range of applications, including image recognition, natural language processing, and autonomous systems.
2. Model Training and Evaluation: Train deep learning models using large-scale datasets, evaluating model performance and iteratively refining approaches to achieve state-of-the-art results.
3. Model Deployment: Architect scalable and reliable deep learning pipelines for deployment in production environments, collaborating with DevOps engineers to ensure seamless integration and monitoring.
4. Data Processing: Develop data pipelines to ingest, clean, and preprocess data for training and evaluation, ensuring data quality and integrity throughout the data lifecycle.
5. Performance Optimization: Optimize deep learning models and systems for speed, efficiency, and scalability, leveraging techniques such as distributed computing and parallel processing.
6. Cross-Functional Collaboration: Collaborate with cross-functional teams, including data scientists, software engineers, and product managers, to define requirements, prioritize tasks, and deliver solutions that meet business objectives.
7. Documentation and Reporting: Prepare documentation and technical reports to communicate model designs, implementation details, and performance metrics to stakeholders, ensuring transparency and reproducibility.
Qualifications:
• Bachelor's degree or higher in Computer Science, Electrical Engineering, Statistics, or related field.
• Strong background in deep learning, with hands-on experience in developing and deploying deep learning models in production environments.
• Proficiency in programming languages such as Python, TensorFlow, PyTorch, or Keras, with experience in data manipulation and analysis.
• Familiarity with deep learning concepts and techniques, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), and transformer models.
• Experience with cloud platforms such as AWS, Azure, or Google Cloud, and proficiency in using relevant tools and services for deep learning development and deployment.
• Strong problem-solving abilities and analytical thinking, with a keen attention to detail and a passion for tackling complex technical challenges.
• Excellent communication and collaboration skills, with the ability to work effectively in cross-functional teams and communicate technical concepts to non-technical stakeholders.
Benefits
• Competitive salary: The industry standard salary for Deep Learning Engineers typically ranges from $150,000 to $230,000 per year, depending on experience and qualifications. Exceptional candidates may be eligible for higher compensation packages.
• Comprehensive health, dental, and vision insurance plans.
• Flexible work hours and remote work options.
• Generous vacation and paid time off.
• Professional development opportunities, including access to training programs, conferences, and workshops.
• State-of-the-art technology environment with access to cutting-edge tools and resources.
• Vibrant and inclusive company culture with team-building activities and social events.
• Opportunities for career growth and advancement within the company.
• Exciting projects with real-world impact across diverse industries.
• Chance to work alongside top talent and industry experts in the field of deep learning.
Join Us: Ready to shape the future of AI with deep learning? Apply now to join our team and be part of an exciting journey of innovation and discovery!
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