... Mistral, etc) including fine-tuning models, prompt engineering, embeddings and context window. • Strong collaboration skills to work effectively with cross-functional teams, communicate complex ...
... Mistral, etc) including fine-tuning models, prompt engineering, embeddings and context window. • Strong collaboration skills to work effectively with cross-functional teams, communicate complex ...
Expert in Large Language models (OpenAI, Anthropic, Mistral, etc) including fine-tuning models, prompt engineering, embeddings and context window. * Strong collaboration skills to work effectively ...
Expert in Large Language models (OpenAI, Anthropic, Mistral, etc) including fine-tuning models, prompt engineering, embeddings and context window. * Strong collaboration skills to work effectively ...
Expert in Large Language models (OpenAI, Anthropic, Mistral, etc) including fine-tuning models, prompt engineering, embeddings and context window. * Strong collaboration skills to work effectively ...
Expert in Large Language models (OpenAI, Anthropic, Mistral, etc) including fine-tuning models, prompt engineering, embeddings and context window. * Strong collaboration skills to work effectively ...
Expert in Large Language models (OpenAI, Anthropic, Mistral, etc) including fine-tuning models, prompt engineering, embeddings and context window. * Strong collaboration skills to work effectively ...
Expert in Large Language models (OpenAI, Anthropic, Mistral, etc) including fine-tuning models, prompt engineering, embeddings and context window. * Strong collaboration skills to work effectively ...
Expert in Large Language models (OpenAI, Anthropic, Mistral, etc) including fine-tuning models, prompt engineering, embeddings and context window. * Strong collaboration skills to work effectively ...
Expert in Large Language models (OpenAI, Anthropic, Mistral, etc) including fine-tuning models, prompt engineering, embeddings and context window. * Strong collaboration skills to work effectively ...
Mistral information
See Delaware salary details
$15K - $48.9K
2% of jobs
$48.9K - $82.7K
2% of jobs
$82.7K - $116.6K
6% of jobs
$116.6K - $150.4K
5% of jobs
$150.4K - $184.2K
2% of jobs
$201.2K is the 25th percentile. Wages below this are outliers.
$184.2K - $218.1K
14% of jobs
The median wage is $245.5K / yr.
$218.1K - $251.9K
22% of jobs
$251.9K - $285.8K
13% of jobs
$297.9K is the 75th percentile. Wages above this are outliers.
$285.8K - $319.6K
22% of jobs
$319.6K - $353.5K
7% of jobs
$353.5K - $387.3K
3% of jobs
$15K
$241.5K
$387.3K
How much do mistral jobs pay per year?
As of Jul 24, 2026, the average yearly pay for mistral in Delaware is $241,503.00, according to ZipRecruiter salary data. Most workers in this role earn between $200,200.00 and $300,300.00 per year, depending on experience, location, and employer.
What are the key skills and qualifications needed to thrive as a Mistral Engineer, and why are they important?
To thrive as a Mistral Engineer, you need a solid background in software engineering, machine learning, and natural language processing, often supported by a degree in computer science or a related field. Familiarity with frameworks like PyTorch or TensorFlow, experience with distributed systems, and version control tools such as Git are typically required. Strong problem-solving skills, collaboration, and adaptability help individuals excel in this dynamic, innovative environment. These competencies are crucial for driving advancements in AI technology and delivering robust, scalable solutions.
What are Mistral jobs?
Mistral jobs refer to roles related to Mistral, which can indicate either a workflow orchestration service in IT or positions at Mistral AI, a company specializing in artificial intelligence and large language models. In the context of workflow orchestration, Mistral jobs involve creating, managing, and monitoring automated workflows, often in cloud or DevOps environments. At Mistral AI, jobs can include research, software engineering, and AI model development. Responsibilities usually focus on building scalable, efficient systems or advancing state-of-the-art machine learning technologies.
What is the difference between Mistral vs Data Scientist?
| Aspect | Mistral | Data Scientist |
|---|---|---|
| Required Credentials | Typically requires a background in engineering, physics, or related fields; certifications are optional | Requires a degree in computer science, statistics, or related fields; certifications like Certified Data Scientist are common |
| Work Environment | Often works in research labs, tech companies, or startups focusing on AI and machine learning | Works in various industries including finance, healthcare, and tech, analyzing data to inform decisions |
| Employer & Industry Usage | Used mainly in AI research and development, especially in natural language processing | Widely used across industries for data analysis, predictive modeling, and business insights |
While both Mistral and Data Scientists work with advanced technology, Mistral typically focuses on AI research and development, often requiring a strong engineering background. Data Scientists analyze data to generate insights across industries. The roles overlap in technical skills but differ in focus and application.
What are some typical challenges faced by Mistral engineers when integrating AI models into production environments?
Mistral engineers often encounter challenges such as ensuring model scalability, managing latency, and maintaining robust security when deploying AI models into production. They must frequently collaborate with data scientists, DevOps, and product teams to fine-tune models, monitor real-world performance, and address unexpected behavior. Staying updated with rapid advancements in machine learning frameworks and cloud infrastructure is also crucial. Effective communication and agile problem-solving are key to overcoming these hurdles and delivering reliable AI solutions.
What are popular job titles related to Mistral jobs in Delaware? For Mistral jobs in Delaware, the most frequently searched job titles are:
What job categories do people searching Mistral jobs in Delaware look for? The top searched job categories for Mistral jobs in Delaware are:
What cities in Delaware are hiring for Mistral jobs? Cities in Delaware with the most Mistral job openings:
Full-time
This job post has expired today. Applications are no longer accepted.
Job description
Job Summary:
JPMorgan Chase is one of the oldest financial institutions, providing innovative financial solutions to a diverse clientele. The Applied AI/ML Lead will drive machine learning and generative AI projects, working collaboratively with product managers and engineers to implement cutting-edge AI solutions that enhance the Home Lending sector.
Responsibilities:
• Work with product managers, data scientists, ML engineers, and other stakeholders to understand requirements.
• Design, develop, and deploy state-of-the-art AI/ML/GenAI solutions to meet business objectives.
• Architect and implement robust, cloud-native MLOps/LLMOps pipelines and distributed AI/ML infrastructure (AWS, Azure, GCP) for scalable, efficient deployment and monitoring of models in production.
• Direct the development and deployment of advanced generative AI solutions (LLMs, RAG, NLP, AI Agents) and classical ML models, integrating state-of-the-art techniques into the ML platform to create innovative fintech products.
• Develop advanced monitoring and management tools to ensure high reliability and scalability of AI/ML systems.
• Develop and maintain automated pipelines for model deployment, ensuring scalability, reliability, and efficiency.
• Implement monitoring mechanisms to track model performance in real-time and ensure model reliability.
• Communicate AI/ML capabilities and results to both technical and non-technical audiences.
• Build AI Agents and chatbot
• Stay informed about the latest trends and advancements in the latest AI/ML research, implement cutting-edge techniques, and leverage external APIs for enhanced functionality.
Qualifications:
Required:
• Bachelor’s degree or MS or PhD in quantitative discipline, e.g. Computer Science, Mathematics, Operations Research, Data Science.
• 5+ years of experience in Machine Learning and Artificial Intelligence engineering.
• Experience in applied AI/ML engineering, with a track record of developing and deploying business critical machine learning models in production.
• Proficiency in programming languages like Python for model development, experimentation, and integration with OpenAI API.
• Extensive hands-on technical experience with machine learning frameworks, libraries, and APIs, such as TensorFlow, PyTorch, Scikit-learn, AWS Bedrock, Transformers, LangChain/LngGraph.
• Experience with cloud computing platforms (e.g., AWS, Azure, or Google Cloud Platform), containerization technologies (e.g., Docker and Kubernetes), orchestration tools (Airflow, FastAPI, etc.) and architectural design, implementation, and performance optimization.
• Solid understanding of fundamentals of statistics, machine learning (e.g., classification, regression, deep learning, reinforcement learning), and generative model architectures.
• Expert in Large Language models (OpenAI, Anthropic, Mistral, etc) including fine-tuning models, prompt engineering, embeddings and context window.
• Strong collaboration skills to work effectively with cross-functional teams, communicate complex concepts, and contribute to interdisciplinary projects.
Preferred:
• Familiarity with the financial services industries.
• Expertise in designing and implementing pipelines using Retrieval-Augmented Generation (RAG).
• Hands-on knowledge of Chain-of-Thoughts, Tree-of-Thoughts, Graph-of-Thoughts prompting strategies.
• Familiarity with ethical AI, including bias mitigation, explainability and escalation protocols for risky outputs.
Company:
With a history tracing its roots to 1799 in New York City, JPMorganChase is one of the world's oldest, largest, and best-known financial institutions—carrying forth the innovative spirit of our heritage firms in global operations across 100 markets. Founded in 2000, the company is headquartered in New York, USA, with a team of 10001+ employees. The company is currently Late Stage.
JPMorgan Chase is one of the oldest financial institutions, providing innovative financial solutions to a diverse clientele. The Applied AI/ML Lead will drive machine learning and generative AI projects, working collaboratively with product managers and engineers to implement cutting-edge AI solutions that enhance the Home Lending sector.
Responsibilities:
• Work with product managers, data scientists, ML engineers, and other stakeholders to understand requirements.
• Design, develop, and deploy state-of-the-art AI/ML/GenAI solutions to meet business objectives.
• Architect and implement robust, cloud-native MLOps/LLMOps pipelines and distributed AI/ML infrastructure (AWS, Azure, GCP) for scalable, efficient deployment and monitoring of models in production.
• Direct the development and deployment of advanced generative AI solutions (LLMs, RAG, NLP, AI Agents) and classical ML models, integrating state-of-the-art techniques into the ML platform to create innovative fintech products.
• Develop advanced monitoring and management tools to ensure high reliability and scalability of AI/ML systems.
• Develop and maintain automated pipelines for model deployment, ensuring scalability, reliability, and efficiency.
• Implement monitoring mechanisms to track model performance in real-time and ensure model reliability.
• Communicate AI/ML capabilities and results to both technical and non-technical audiences.
• Build AI Agents and chatbot
• Stay informed about the latest trends and advancements in the latest AI/ML research, implement cutting-edge techniques, and leverage external APIs for enhanced functionality.
Qualifications:
Required:
• Bachelor’s degree or MS or PhD in quantitative discipline, e.g. Computer Science, Mathematics, Operations Research, Data Science.
• 5+ years of experience in Machine Learning and Artificial Intelligence engineering.
• Experience in applied AI/ML engineering, with a track record of developing and deploying business critical machine learning models in production.
• Proficiency in programming languages like Python for model development, experimentation, and integration with OpenAI API.
• Extensive hands-on technical experience with machine learning frameworks, libraries, and APIs, such as TensorFlow, PyTorch, Scikit-learn, AWS Bedrock, Transformers, LangChain/LngGraph.
• Experience with cloud computing platforms (e.g., AWS, Azure, or Google Cloud Platform), containerization technologies (e.g., Docker and Kubernetes), orchestration tools (Airflow, FastAPI, etc.) and architectural design, implementation, and performance optimization.
• Solid understanding of fundamentals of statistics, machine learning (e.g., classification, regression, deep learning, reinforcement learning), and generative model architectures.
• Expert in Large Language models (OpenAI, Anthropic, Mistral, etc) including fine-tuning models, prompt engineering, embeddings and context window.
• Strong collaboration skills to work effectively with cross-functional teams, communicate complex concepts, and contribute to interdisciplinary projects.
Preferred:
• Familiarity with the financial services industries.
• Expertise in designing and implementing pipelines using Retrieval-Augmented Generation (RAG).
• Hands-on knowledge of Chain-of-Thoughts, Tree-of-Thoughts, Graph-of-Thoughts prompting strategies.
• Familiarity with ethical AI, including bias mitigation, explainability and escalation protocols for risky outputs.
Company:
With a history tracing its roots to 1799 in New York City, JPMorganChase is one of the world's oldest, largest, and best-known financial institutions—carrying forth the innovative spirit of our heritage firms in global operations across 100 markets. Founded in 2000, the company is headquartered in New York, USA, with a team of 10001+ employees. The company is currently Late Stage.