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Mistral Jobs (NOW HIRING)

ClifyX

AI Engineers

Bentonville, AR · On-site

... Mistral AI • Experience with Azure • Experience with Element Platform for ML and LLMs • Experience with CPlex (IBM) and PuLP Company : ClifyX provides innovative business solutions which ...

BrightAI

Senior AI Engineer - LLM, RAG

Palo Alto, CA · On-site

$123K - $168K/yr

Responsibilities : • Lead the architecture and development of RAG systems that combine LLMs (e.g., LLAMA, Mistral, Claude, GPT) with structured and unstructured external information sources. • ...

Infovision

AI Engineer

Dallas, TX · On-site

... Mistral, Falcon) Experience with vector search, semantic similarity, and embedding strategies (OpenAI Embeddings, Sentence Transformers) Strong understanding of data pipelines -- ingestion ...

WorkNovas LLC

Gen AI Engineer

Sunrise, FL · On-site

Required Qualifications Strong experience with LLMs (e.g., OpenAI, Anthropic, Llama, Mistral). Hands-on experience with LangChain and/or LangGraph. * Solid understanding of LLM memory architectures ...

Klaviyo

Senior AI Application Engineer

Boston, MA · On-site

Architect and develop production-grade systems leveraging large language models (GPT-4, Claude, Mistral, Llama) for internal automation, knowledge retrieval, and intelligent workflow assistance. • ...

ITBMS Inc.

AI/ML Engineer with Agentic AI

Plano, TX · On-site

LLM Expertise: • Must have hands-on experience working with modern LLMs (OpenAI, Anthropic, LLaMA, Mistral, Gemini),as well as a strong understanding of tokenization, model behaviors, reasoning ...

InfoVision, Inc.

AI Engineer

Dallas, TX · On-site

Proficient with LLM APIs - OpenAI, Anthropic, Gemini, and open-source models (LLaMA, Mistral, Falcon) * Experience with vector search , semantic similarity, and embedding strategies (OpenAI ...

Leidos

Data Scientist SME AI/ML

Fort George G Meade, MD · On-site

$154K - $278K/yr

Hands-on fine-tuning of open-source models (Llama 3, Mistral) in air-gapped enclaves using PyTorch or TensorFlow. * Technical Closing: Direct engineering of Retrieval-Augmented Generation (RAG ...

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Mistral information

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$15K

$241.3K

$387K

How much do mistral jobs pay per year?

As of Jul 22, 2026, the average yearly pay for mistral in the United States is $241,295.00, according to ZipRecruiter salary data. Most workers in this role earn between $200,000.00 and $300,000.00 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.
More about Mistral jobs
What cities are hiring for Mistral jobs? Cities with the most Mistral job openings:
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What job categories do people searching Mistral jobs look for? The top searched job categories for Mistral jobs are:
Mistral jobs near you
Infographic showing various Mistral job openings in the United States as of July 2026, with employment types broken down into 94% Full Time, 1% Part Time, 3% Contract, and 2% Nights. Highlights an 78% Physical, 3% Hybrid, and 19% Remote job distribution, with an average salary of $241,295 per year, or $116 per hour.

GenAI Engineer-W2

Vkore Solutions

Austin, TX • On-site

Contractor

Posted 15 days ago

Job description

We are looking for a GenAI Ops Engineer to train, fine-tune, and deploy Generative AI models (LLMs, Diffusion Models, Transformers, etc.). You will optimize model performance, manage training pipelines, and integrate AI solutions into production.

Key Responsibilities:

  • Train and fine-tune LLMs using PyTorch, DeepSpeed, and LoRA.
  • Optimize inference using ONNX, vLLM, TensorRT, and GPU acceleration.
  • Manage datasets, preprocess data, and implement RAG with vector databases (FAISS, Chroma, Pinecone).
  • Automate training workflows using ML flow, Weights & Biases, and Ray.
  • Deploy models using Kubernetes, Docker, and cloud AI services AWS or GCP.
  • Monitor model performance, mitigate drift, and optimize resource utilization.

Requirements:

  • Experience with LLM training, fine-tuning, and inference optimization.
  • Proficiency in Python, cloud AI services, and distributed training.
  • Familiarity with retrieval-augmented generation (RAG) and prompt engineering.
  • Strong problem-solving skills and ability to work in fast-paced AI environments.

Preferred:

  • Experience with open-weight models (LLaMA, Mistral, Gemma, Falcon, etc.).
  • Hands-on knowledge of multi-agent architectures and synthetic data generation.