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Assistant Mlops Jobs in Nevada (NOW HIRING)

Description Position Summary The Assistant Vice President of Artificial Intelligence (AVP of AI) is ... Implement AIOps/MLOps and model governance practices aligned with banking regulations and internal ...

Build and operationalize LLM-enabled capabilities (e.g., copilots, HR knowledge assistants ... LLMOps/MLOps capabilities (evaluation, monitoring, governance workflows, model/prompt/version ...

Assistant Mlops information

What is an Assistant MLOps?

Assistant MLOps are professionals who support the deployment, monitoring, and management of machine learning models in production environments. They assist senior MLOps engineers with tasks like automating workflows, managing data pipelines, maintaining infrastructure, and ensuring model performance. Their role bridges the gap between data science and IT operations, helping organizations scale and maintain their AI solutions efficiently. Assistant MLOps often have knowledge of cloud services, CI/CD tools, and basic programming, and they work closely with data scientists and engineers.

What are the typical daily responsibilities of an Assistant MLOps?

As an Assistant MLOps professional, you can expect your daily tasks to involve supporting the deployment, monitoring, and maintenance of machine learning models in production environments. This often includes collaborating with data scientists to automate model training and testing workflows, managing cloud-based resources, and ensuring that data pipelines are running smoothly. You'll also help troubleshoot issues related to model performance or infrastructure and assist in implementing best practices for version control and continuous integration. Working closely with both engineering and data teams, you'll play a key role in ensuring that ML models remain reliable and scalable in real-world applications.

What are the key skills and qualifications needed to thrive as an Assistant MLOps?

To thrive as an Assistant MLOps, you need a solid understanding of machine learning fundamentals, programming (especially Python), and experience with cloud platforms; a degree in computer science or a related field is typically preferred. Familiarity with tools like Docker, Kubernetes, CI/CD pipelines, and version control systems (e.g., Git) is important, and certifications in cloud services (AWS, Azure, GCP) can be advantageous. Strong problem-solving, communication, and collaboration skills help you bridge the gap between data science and operations teams. These combined skills ensure efficient deployment, monitoring, and maintenance of machine learning models in production environments.

What is the difference between Assistant Mlops vs Data Engineer?

AspectAssistant MlopsData Engineer
Required CredentialsCertifications in cloud platforms, basic scripting, ML toolsComputer science degree, SQL, Python, data architecture
Work EnvironmentCollaborates with ML teams, supports deployment pipelinesBuilds data pipelines, manages databases, processes large datasets
Industry UsageAI/ML projects, cloud-based environmentsData infrastructure, analytics, big data solutions

Assistant Mlops and Data Engineer roles share overlapping skills in cloud platforms and scripting. However, Assistant Mlops focuses on supporting ML deployment and operations, while Data Engineers primarily build and maintain data infrastructure. Both roles are essential in data-driven organizations but serve different functions within the data ecosystem.

What are the most commonly searched types of Mlops jobs in Nevada?

The most popular types of Mlops jobs in Nevada are:

What are popular job titles related to Assistant Mlops jobs in Nevada?

For Assistant Mlops jobs in Nevada, the most frequently searched job titles are:

What cities in Nevada are hiring for Assistant Mlops jobs?

Cities in Nevada with the most Assistant Mlops job openings:

AVP, Artificial Intelligence

Las Vegas, NV • On-site

Credit One Bank
Finance and Insurance • 501 - 1,000 employees

Full-time

Re-posted yesterday


Job description

Job Summary:
Credit One Bank is a data-driven financial services company based in Las Vegas. The Assistant Vice President of Artificial Intelligence is responsible for leading the delivery and execution of AI and machine learning capabilities within a regulated banking environment, focusing on fraud prevention, credit risk management, and customer experience personalization.
Responsibilities:
• Lead development and deployment of AI/ML and Generative AI solutions for fraud detection, credit scoring, underwriting, AML, and customer engagement.
• Serve as technical authority for model architecture, feature engineering, training pipelines, and inference services.
• Manage and mentor AI Engineers and ML practitioners; provide code and design reviews.
• Implement AIOps/MLOps and model governance practices aligned with banking regulations and internal Model Risk Management (MRM) standards.
• Partner with Risk, Compliance, Legal, Cybersecurity, and Data teams to ensure Responsible AI adoption.
• Oversee model validation, explainability, bias testing, and audit readiness.
• Collaborate with product and business leaders to translate financial use cases into scalable AI solutions.
Qualifications:
Required:
• Lead development and deployment of AI/ML and Generative AI solutions for fraud detection, credit scoring, underwriting, AML, and customer engagement.
• Serve as technical authority for model architecture, feature engineering, training pipelines, and inference services.
• Manage and mentor AI Engineers and ML practitioners; provide code and design reviews.
• Implement AIOps/MLOps and model governance practices aligned with banking regulations and internal Model Risk Management (MRM) standards.
• Partner with Risk, Compliance, Legal, Cybersecurity, and Data teams to ensure Responsible AI adoption.
• Oversee model validation, explainability, bias testing, and audit readiness.
• Collaborate with product and business leaders to translate financial use cases into scalable AI solutions.
• 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.
• 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.
• Excellent communication, problem-solving, and project management skills.
• Ability to collaborate effectively and follow up ensure achievement of deadlines, outcomes and results.
• Demonstrate company core values of excellence, ownership, collaboration, and integrity.
Preferred:
• Bachelor’s degree in Computer Science, Engineering, Data Science, or related field.
• 5-8 + 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.