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Deep Learning Ai Jobs in Nevada (NOW HIRING)

Instacart

The Logistics AI group is responsible for the intelligence and execution behind Instacart ... Knowledge of deep learning frameworks and methodologies * Experience in applying machine learning ...

Instacart

The Logistics AI group is responsible for the intelligence and execution behind Instacart ... Knowledge of deep learning frameworks and methodologies * Experience in applying machine learning ...

Instacart

The Logistics AI group is responsible for the intelligence and execution behind Instacart ... Knowledge of deep learning frameworks and methodologies * Experience in applying machine learning ...

Instacart

The Logistics AI group is responsible for the intelligence and execution behind Instacart ... Knowledge of deep learning frameworks and methodologies * Experience in applying machine learning ...

Bespoke Labs

Machine Learning Engineer

Henderson, NV · On-site

About Us We are AI researchers and builders who understand how to curate data and RL environments ... deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed ...

Bespoke Labs

Machine Learning Engineer

Las Vegas, NV · On-site

About Us We are AI researchers and builders who understand how to curate data and RL environments ... deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed ...

Bespoke Labs

Machine Learning Engineer

Sparks, NV · On-site

About Us We are AI researchers and builders who understand how to curate data and RL environments ... deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed ...

Bespoke Labs

Machine Learning Engineer

Sparks, NV

About Us We are AI researchers and builders who understand how to curate data and RL environments ... deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed ...

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Deep Learning Ai information

What is the difference between Deep Learning Ai vs Machine Learning Engineer?

AspectDeep Learning AiMachine Learning Engineer
Required CredentialsDegree in Computer Science, Data Science, or related fields; knowledge of neural networksDegree in Computer Science, Data Science, or related fields; programming skills in Python, R
Work EnvironmentResearch labs, AI development teams, tech companies focusing on AI modelsSoftware development teams, data analysis projects across various industries
Industry UsagePrimarily in AI research, autonomous systems, NLP, computer visionAcross industries for predictive modeling, data analysis, automation

Deep Learning Ai specialists focus on designing and implementing neural network models for complex AI tasks, often requiring advanced knowledge of deep neural networks. Machine Learning Engineers develop broader machine learning models, including traditional algorithms. While both roles require similar educational backgrounds, Deep Learning Ai roles are more specialized in neural networks and AI research, whereas Machine Learning Engineers work across a wider range of algorithms and applications.

What are some common challenges faced by professionals working in deep learning AI, and how can they be addressed?

Professionals in Deep Learning AI often encounter challenges such as managing large datasets, ensuring model accuracy, and addressing issues like overfitting. Collaboration with data engineers and domain experts is crucial to ensure high-quality data and relevant feature selection. Additionally, staying up-to-date with rapidly evolving frameworks and algorithms requires continuous learning and participation in knowledge-sharing within the team. Regular code reviews and experimentation with different architectures can help overcome technical obstacles and improve model performance.

What are the key skills and qualifications needed to thrive as a deep learning AI engineer?

To thrive as a Deep Learning AI Engineer, you need a strong background in mathematics, programming (especially Python), and experience with neural networks, typically supported by a degree in computer science, engineering, or a related field. Proficiency with deep learning frameworks such as TensorFlow or PyTorch, and knowledge of tools like CUDA for GPU acceleration, are essential; relevant certifications can be advantageous. Analytical thinking, creativity, and effective communication are important soft skills for solving complex problems and collaborating with cross-functional teams. These skills and qualities are crucial for building robust AI models and driving innovation in this rapidly evolving field.

What is a deep learning AI professional?

Deep Learning AI professionals are experts who design, develop, and implement artificial intelligence systems that use deep neural networks to analyze complex data and solve tasks such as image recognition, natural language processing, and autonomous decision-making. They work with large datasets and advanced algorithms to build models that can learn and improve over time. These professionals often have a background in computer science, mathematics, or engineering, and are skilled in programming languages like Python and frameworks such as TensorFlow or PyTorch.
What are popular job titles related to Deep Learning Ai jobs in Nevada? For Deep Learning Ai jobs in Nevada, the most frequently searched job titles are:
What job categories do people searching Deep Learning Ai jobs in Nevada look for? The top searched job categories for Deep Learning Ai jobs in Nevada are:
What cities in Nevada are hiring for Deep Learning Ai jobs? Cities in Nevada with the most Deep Learning Ai job openings:
Deep Learning Ai jobs near you

Lead Artificial Intelligence Engineer

Credit One Bank

Las Vegas, NV • On-site

$97K - $128K/yr

Full-time

Re-posted 12 days ago

Job description

Job Summary:
Credit One Bank is a data-driven financial services company based in Las Vegas. They are seeking a Lead Artificial Intelligence Engineer to develop and produce AI and machine learning solutions that support banking and credit card businesses, focusing on building scalable, explainable, and compliant AI models for various applications.
Responsibilities:
• Develop, train, and optimize ML, deep learning, and Generative AI models.
• Implement data pipelines, feature engineering, and model inference services.
• Deploy and monitor models using enterprise MLOps practices.
• Support model explainability, bias analysis, and regulatory documentation.
• Collaborate with data engineers, risk, and compliance teams.
Qualifications:
Required:
• Develop, train, and optimize ML, deep learning, and Generative AI models.
• Implement data pipelines, feature engineering, and model inference services.
• Deploy and monitor models using enterprise MLOps practices.
• Support model explainability, bias analysis, and regulatory documentation.
• Collaborate with data engineers, risk, and compliance teams.
• Machine Learning & Modeling: Supervised, unsupervised, reinforcement learning.
• Deep learning (CNNs, RNNs, Transformers).
• Natural Language Processing (NLP) & LLMs.
• Generative AI (diffusion models, fine-tuning, RAG).
• AI Engineering & MLOps: Model training, deployment, monitoring, and retraining.
• Feature stores, vector databases, and model registries.
• CI/CD pipelines for ML (MLOps).
• GPU/accelerator compute architectures.
• Cloud & Infrastructure: Azure AI, Azure ML, AWS Sagemaker, or Google Vertex AI.
• Kubernetes, containerization, microservices.
• Data platforms (Databricks, Snowflake, Synapse).
• Responsible AI & Governance: Model explainability (SHAP, LIME).
• Fairness, bias detection, model risk controls.
• Privacy-preserving ML techniques (differential privacy, federated learning).
• Programming & Tooling: Python, PyTorch, TensorFlow, JAX.
• LangChain, semantic search, vector embeddings.
• Prompt engineering & LLM orchestration frameworks.
Preferred:
• Bachelor’s degree in Computer Science, Engineering, Data Science, or related field.
• 3–7 years of experience in AI/ML or data science.
• Experience working with large-scale financial or transactional data is preferred.
Company:
Credit One Bank is a financial services company that offers credit cards, credit score tracking, and fraud protection services. Founded in 1984, the company is headquartered in Las Vegas, USA, with a team of 1001-5000 employees. The company is currently Late Stage.

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