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Mistral Jobs (NOW HIRING)

Conch Technologies Inc

AI ML Engineer

Lakeland, FL · Remote

Proven track record deploying and optimizing open-source LLMs (e.g., LLaMA, Mistral) in non-cloud, restricted, or air-gapped private infrastructures * Deep Framework Proficiency: Heavy hands-on ...

Sia

Associate Consultant, Generative AI

Manhattan, NY · On-site

What You'll Do You'll design and implement GenAI/LLM solutions leveraging models such as Claude, GPT, Gemini, Llama, and Mistral - selecting the right approach (RAG, agents, fine-tuning, prompt ...

Qualified Health

Applied AI Engineer

Palo Alto, CA · On-site

$180K - $250K/yr

Evaluate and integrate state-of-the-art LLMs (OpenAI, Anthropic, Mistral, etc.) into production use cases. * Contribute to building a scalable workflow infrastructure that will support 100+ workflows ...

Mirakl

Lead AI Engineer

Boston, MA · On-site

$111K - $146K/yr

OpenAI, Anthropic, Gemini, Mistral and Open-source models • Agentic & Retrieval: LangGraph, LangChain, LlamaIndex, MCP and Vector Databases • Infrastructure: AWS or GCP, Docker and Kubernetes ...

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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 21, 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.
AIML Engineer with Agentic AI experience

AIML Engineer with Agentic AI experience

Emergere Technologies

Plano, TX • On-site

Other

This job post has expired today. Applications are no longer accepted.

Job description

Position: AI ML engineer with Agentic AI experience

Location: PLanp,TX( 3 days Onsite) (2 positions)

Type: Contract

 

Job Profile:

An expert Prompt engineer with a strong software engineering a background and an excellent communicator with 8+ years of experience implementing AI and ML use cases. (Primarily AI)

Knowledge of Computer vision related projects.

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 patterns, and evaluation frameworks.
    • Prompt Design & Optimization (zero-shot, few-shot, chain-of-thought, ReAct, self-consistency)
    • Structured prompt templates
    • Refinement (prompt chaining, decomposition, and verification strategies)
    • Safety, Guardrails & Compliance
  • Experience building conversational flows (chatbots).

Retrieval-Augmented Generation (RAG) :

  • Work with embedding models, vector databases, context windows, and chunking strategies
  • Work experience in Vector database (FAISS, Milvus, Pinecone or any)

Machine Learning:

  • Machine Learning Engineer with strong experience in building, deploying, and optimizing end-to-end ML systems. 
  • Skilled in data preprocessing, feature engineering, model development, and production deployment using modern ML frameworks. 
  • Proficient in Python, PyTorch/ TensorFlow, cloud services, and MLOps practices.

Software Engineering:

  • Python proficiency.
  • Very good understanding and work experience with REST APIs, JSON, YAML.
  • Ability to integrate LLM prompts into production applications.
  • Familiarity with Git, version control, and experiment tracking.

Apply