Deep Learning Engineer
Cura Label Technologies · United States
- Hybrid
- Full-time
- $100,000 / year
- United States
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Job highlights
- Design, develop, and deploy deep learning models.
- Build and optimize neural network architectures.
- Work with large datasets and preprocessing pipelines.
- Collaborate on integrating AI models into production.
- 100% remote, full-time 12-month contract.
About the role
Deep Learning Engineer at Cura Label Technologies
CuraLabel is seeking a talented Deep Learning Engineer to join our team on a one-year full-time contract. In this role, you will design, develop, and deploy deep learning models that power intelligent applications across a variety of domains. You will work with large datasets, build scalable AI solutions, optimize model performance, and collaborate with cross-functional teams to bring cutting-edge machine learning systems into production.
Responsibilities
- Design, develop, train, and deploy deep learning models for real-world applications.
- Build and optimize neural network architectures for high performance and accuracy.
- Develop data preprocessing, feature engineering, and data augmentation pipelines.
- Train, evaluate, and fine-tune machine learning and deep learning models.
- Experiment with state-of-the-art deep learning techniques and architectures.
- Collaborate with data scientists, software engineers, and product teams to integrate AI models into production systems.
- Optimize models for inference speed, scalability, and resource efficiency.
- Monitor model performance and continuously improve accuracy and reliability.
- Document experiments, model architectures, and technical implementations.
- Stay current with the latest research and advancements in deep learning and artificial intelligence.
Required Qualifications
- Bachelor's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Computer Engineering, or a related field.
- Strong experience with Python.
- Experience with PyTorch, TensorFlow, or similar deep learning frameworks.
- Strong understanding of neural networks, deep learning algorithms, and machine learning fundamentals.
- Experience training, evaluating, and deploying deep learning models.
- Knowledge of supervised, unsupervised, and self-supervised learning techniques.
- Experience working with large datasets and data preprocessing pipelines.
- Familiarity with model optimization and performance tuning.
- Experience using Git and collaborative software development workflows.
- Strong analytical, mathematical, and problem-solving skills.
- Excellent communication skills and the ability to work independently in a remote environment.
Preferred Qualifications
- Experience with transformer architectures and foundation models.
- Experience with large language models (LLMs), multimodal AI, or generative AI applications.
- Familiarity with computer vision or natural language processing.
- Experience deploying models using Docker, Kubernetes, or cloud platforms.
- Experience with AWS, Google Cloud Platform, or Microsoft Azure.
- Knowledge of MLOps, CI/CD pipelines, and model monitoring.
- Experience with distributed training and GPU optimization.
- Familiarity with ONNX, TensorRT, or other model optimization frameworks.
- Contributions to AI research, publications, or open-source projects are a plus.
What We Offer
- 100% Remote work.
- Full-time, 12-month contract.
- Opportunity to work on cutting-edge deep learning and AI projects.
- Collaborative engineering environment with experienced AI professionals.
- Exposure to modern machine learning technologies and production-scale AI systems.
If you're passionate about deep learning and building intelligent systems that solve complex problems, we'd love to hear from you.
Key skills/competency
- Deep Learning Engineer
- Python
- PyTorch
- TensorFlow
- Neural Networks
- Machine Learning
- AI Models
- Data Preprocessing
- Model Optimization
- Remote Work
Skills & topics
- Deep Learning Engineer
- Python
- PyTorch
- TensorFlow
- Machine Learning
- AI
- Neural Networks
- Model Deployment
- Data Science
- Remote
How to get hired
- Tailor your resume: Highlight Python, PyTorch/TensorFlow, and deep learning model deployment experience.
- Showcase projects: Include personal or professional projects involving AI model development and optimization.
- Emphasize remote skills: Mention strong communication and independent work abilities for remote roles.
- Prepare for technical questions: Be ready to discuss neural networks, algorithms, and model tuning.
- Highlight preferred qualifications: If applicable, showcase experience with LLMs, cloud platforms, or MLOps.
Technical preparation
Master Python and deep learning frameworks.,Understand neural networks and algorithms.,Practice data preprocessing and augmentation.,Familiarize with model optimization techniques.
Behavioral questions
Describe a challenging ML project you faced.,How do you stay updated on AI research?,Explain your approach to model optimization.,How do you collaborate with cross-functional teams?
Frequently asked questions
- What is the work arrangement for the Deep Learning Engineer role at Cura Label Technologies?
- The Deep Learning Engineer position at Cura Label Technologies is 100% remote. This allows for flexibility in where you work, as long as you have a reliable internet connection and can collaborate effectively with the team.
- Is this a permanent position for a Deep Learning Engineer at Cura Label Technologies?
- This is a full-time, 12-month contract position. While it's a fixed term, it offers a valuable opportunity to gain experience with cutting-edge AI projects and potentially extend or lead to other opportunities within the company.
- What programming languages and frameworks are essential for the Deep Learning Engineer role at Cura Label Technologies?
- Strong experience with Python is a must. You should also have hands-on experience with deep learning frameworks such as PyTorch or TensorFlow, as these are central to designing, developing, and deploying deep learning models.
- What kind of deep learning projects can I expect to work on as a Deep Learning Engineer at Cura Label Technologies?
- You can expect to work on a variety of AI projects, focusing on designing, developing, and deploying deep learning models. This includes optimizing model performance, building scalable AI solutions, and integrating these systems into production environments across different domains.
- What are the key differences between required and preferred qualifications for the Deep Learning Engineer position?
- Required qualifications include a relevant degree, Python proficiency, deep learning framework experience, and a solid understanding of ML fundamentals. Preferred qualifications are a bonus and include experience with advanced topics like transformer architectures, LLMs, computer vision, NLP, cloud deployment (AWS, GCP, Azure), and MLOps.
- How important is experience with large datasets for this Deep Learning Engineer role?
- Experience working with large datasets and developing data preprocessing pipelines is a required qualification. This indicates that handling and preparing substantial amounts of data will be a significant part of your responsibilities in this role.
- Does Cura Label Technologies offer opportunities for career growth beyond this 12-month contract for a Deep Learning Engineer?
- While this is a 12-month contract, the company values its employees and the opportunity to work on cutting-edge projects. Successful performance and contribution could lead to opportunities for contract extension or consideration for other roles within Cura Label Technologies.