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Mistral Jobs in Virginia (NOW HIRING)

Spatial Front, Inc

Data Scientist

Arlington, VA · On-site

Preferred : • Experience applying data science to DoD or federal agency mission problems. • Familiarity with Oracle RDBMS 19c • Experience with LLM models such as OpenAI, Gemini, Mistral, and ...

Spatial Front, Inc

Data Scientist

Arlington, VA · On-site

Preferred : • Experience applying data science to DoD or federal agency mission problems. • Familiarity with Oracle RDBMS 19c. • Experience with LLM models such as OpenAI, Gemini, Mistral, and ...

Appian Corporation

Senior AI Security Engineer

Mclean, VA · On-site

$115K - $158K/yr

Understanding of fine-tuning methodologies (LoRA, QLoRA) for smaller, domain-specific open-source models (e.g., Llama 3, Mistral) tailored for security log analysis * Passion for staying abreast of ...

Amivero

AI Engineer

Reston, VA · On-site

Preferred : • Active DHS Clearance • Experience with AWS Bedrock, Amazon OpenSearch, and broader AWS AI/ML ecosystem. • Experience working with foundation models such as Claude, Llama, Mistral ...

Rohirrim, Inc.

Senior AI Engineer

Mclean, VA · On-site

$105K - $145K/yr

Experience with fine-tuning or instruction-tuning open-source LLMs (LLaMA, Mistral, etc.). * Knowledge of secure-by-design principles and air-gapped or FedRAMP-compliant deployment environments.

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Mistral information

See Virginia salary details

$14.9K

$239.2K

$383.7K

How much do mistral jobs pay per year?

As of Jul 30, 2026, the average yearly pay for mistral in Virginia is $239,226.00, according to ZipRecruiter salary data. Most workers in this role earn between $198,300.00 and $297,400.00 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?

AspectMistralData Scientist
Required CredentialsTypically requires a background in engineering, physics, or related fields; certifications are optionalRequires a degree in computer science, statistics, or related fields; certifications like Certified Data Scientist are common
Work EnvironmentOften works in research labs, tech companies, or startups focusing on AI and machine learningWorks in various industries including finance, healthcare, and tech, analyzing data to inform decisions
Employer & Industry UsageUsed mainly in AI research and development, especially in natural language processingWidely 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 Virginia? For Mistral jobs in Virginia, the most frequently searched job titles are:
What job categories do people searching Mistral jobs in Virginia look for? The top searched job categories for Mistral jobs in Virginia are:
What cities in Virginia are hiring for Mistral jobs? Cities in Virginia with the most Mistral job openings:
Mistral jobs near you
Infographic showing various Mistral job openings in Virginia as of July 2026, with employment types broken down into 91% Full Time, 4% Part Time, 3% Contract, and 2% Nights. Highlights an 81% Physical, 3% Hybrid, and 16% Remote job distribution, with an average salary of $239,226 per year, or $115 per hour.

LLMOps Engineer with Security Clearance

The Josef Group Inc.

Chantilly, VA • On-site

Other

Posted 8 days ago

Job description

LLMOps Engineer | Top Secret Clearance required - Chantilly VA Salary to 250K and great benefits! Are you passionate about building and operating production-scale Large Language Model infrastructure? We're looking for an experienced LLMOps Engineer to help deploy, optimize, and scale self-hosted AI platforms. What we're looking for:
✅ Deep understanding of LLM internals (Transformers, tokenization, inference, quantization, fine-tuning)
✅ Hands-on experience with vLLM deployment and production operations
✅ Kubernetes, Docker, GPU clusters, and AWS, Azure, or GCP
✅ Expertise serving open-weight models like Llama, Mistral, and Qwen
✅ Experience with tensor parallelism, continuous batching, PagedAttention, KV-cache optimization, and model quantization (AWQ, GPTQ, FP8)
✅ Strong DevOps background with CI/CD, Infrastructure as Code, observability, monitoring, and incident response
✅ Proven success managing production LLM environments for performance, reliability, scalability, and cost efficiency If you've been responsible for keeping a live, self-hosted LLM platform running at peak performance, we'd love to hear from you. 📩 Contact Debbie at The Josef Group, to learn more about this exciting opportunity.

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