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Mistral Jobs in Boston, MA (NOW HIRING)

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. • ...

Klaviyo

Senior AI Engineer

Boston, MA · On-site

$113K - $155K/yr

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

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 ...

Mirakl - Labs

Lead AI Engineer

Boston, MA · Hybrid

$111K - $146K/yr

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

The Hollister Group

AI Developer

Boston, MA · On-site

$70 - $110/hr

Develop, fine-tune, and integrate models such as GPT-4-turbo, Claude, Llama 3, and Mistral using OpenAI API, Hugging Face, or custom AWS/Azure pipelines. * Build retrieval-augmented generation (RAG ...

Photon

Principal Data Scientist

Boston, MA · On-site

Lead model selection, adaptation, and optimization strategies across proprietary (OpenAI, Claude, Gemini) and open-source foundation models (Llama, Mistral, Qwen), evaluating when to use RAG vs. Fine ...

New

Career Site

Lead AI Engineer

Quincy, MA

$180K - $280K/yr

Develop and implement AI solutions leveraging fine-tuned Large Language Models (e.g., OpenAI models, LLaMA, Mistral). * Design, develop, and optimize Retrieval-Augmented Generation (RAG) pipelines ...

Granite Telecommunications

Lead AI Engineer

Quincy, MA · On-site

$180K - $280K/yr

Develop and implement AI solutions leveraging fine-tuned Large Language Models (e.g., OpenAI models, LLaMA, Mistral). * Design, develop, and optimize Retrieval-Augmented Generation (RAG) pipelines ...

NTT DATA, Inc.

AI Security Architect

Boston, MA · On-site

Mistral * Hugging Face * I Frameworks * LangChain * LangGraph * LlamaIndex * Semantic Kernel * CrewAI * utoGen * Programming * Python * Jav * C# * REST APIs * SQL * JavaScript (preferred) * Cloud ...

Granite Telecommunications

Lead AI Engineer

Quincy, MA · On-site

$180K - $280K/yr

Develop and implement AI solutions leveraging fine-tuned Large Language Models (e.g., OpenAI models, LLaMA, Mistral). * Design, develop, and optimize Retrieval-Augmented Generation (RAG) pipelines ...

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All JobsMistral JobsMistral Jobs in Boston, MA

Mistral information

See Boston, MA salary details

$16.3K

$262.1K

$420.4K

How much do mistral jobs pay per year?

As of Aug 20, 2026, the average yearly pay for mistral in Boston, MA is $262,130.00, according to ZipRecruiter salary data. Most workers in this role earn between $217,300.00 and $325,900.00 per year, depending on experience, location, and employer.

What is a Mistral?

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 are the key skills and qualifications needed to thrive as a Mistral engineer?

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 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 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 is it like to work at Mistral?

Working as a Mistral involves engaging in roles that may require technical skills, teamwork, and adherence to safety protocols. Employees often work in collaborative environments with a focus on efficiency and quality, and may need to be adaptable to changing project demands or schedules.

What are popular job titles related to Mistral jobs in Boston, MA?

For Mistral jobs in Boston, MA, the most frequently searched job titles are:

What job categories do people searching Mistral jobs in Boston, MA look for?

The top searched job categories for Mistral jobs in Boston, MA are:

What cities near Boston, MA are hiring for Mistral jobs?

Cities near Boston, MA with the most Mistral job openings:

Mistral jobs near you
Infographic showing various Mistral job openings in Boston, MA as of August 2026, with employment types broken down into 75% Full Time, and 25% Contract. Highlights an 75% In-person, and 25% Remote job distribution, with an average salary of $262,130 per year, or $126 per hour.

Senior AI Application Engineer

Klaviyo

Boston, MA • On-site

Full-time

Re-posted 21 days ago

Job description

Job Summary:
Klaviyo is a company that empowers creators by making first-party data accessible and actionable. They are seeking a Senior AI Application Engineer to design, build, and scale production-grade LLM integrations and AI-powered automation tools, focusing on applied AI research and full-stack software engineering.
Responsibilities:
• Design and build LLM-powered applications: Architect and develop production-grade systems leveraging large language models (GPT-4, Claude, Mistral, Llama) for internal automation, knowledge retrieval, and intelligent workflow assistance.
• Build and maintain AI integration pipelines: Design robust, scalable API integrations between AI models and internal systems such as HRIS, ticketing, CRM, and knowledge bases, ensuring reliability, low latency, and high availability.
• Develop full-stack AI features end-to-end: Own the complete development of AI features across the stack from backend model orchestration and API layers to frontend interfaces that make AI accessible to non-technical employees.
• Architect and manage CI/CD pipelines for AI systems: Build and maintain automated deployment pipelines for AI models and services, including model evaluation frameworks, A/B testing infrastructure, and safe rollout strategies.
• Implement RAG and retrieval systems: Design and build retrieval-augmented generation systems grounded in Klaviyo internal knowledge, ensuring accuracy, relevance, and up-to-date responses at scale.
• Evaluate and fine-tune AI models: Lead benchmarking, evaluation, and fine-tuning of foundation models for Klaviyo use cases, including prompt engineering and parameter-efficient fine-tuning techniques.
• Establish AI engineering best practices: Define coding standards, testing frameworks, and architectural patterns for AI development at Klaviyo, enabling the team to ship reliable AI features consistently.
• Build AI observability and monitoring tooling: Instrument AI systems with latency monitoring, output quality evaluation, hallucination detection, cost dashboards, and production alerting.
• Collaborate with Product and Data Science: Work closely with PMs, data scientists, and ML engineers to translate requirements into technical implementations, maintaining a tight feedback loop between experimentation and production.
• Drive security and compliance in AI systems: Ensure AI integrations follow data privacy best practices, implement guardrails for sensitive data handling, and maintain compliance with Klaviyo security and governance standards.
Qualifications:
Required:
• 3+ years of software engineering experience, with at least 2 years focused on building AI, ML, or LLM-powered systems in production.
• Deep expertise with large language models such as OpenAI, Anthropic, Mistral, or Llama, and experience integrating them into production applications via API.
• Strong full-stack engineering skills across Python (FastAPI, Flask, or Django) and TypeScript or JavaScript, with experience in modern frontend frameworks.
• Proven experience designing and building CI/CD pipelines for software or ML systems using tools such as GitHub Actions, Jenkins, or CircleCI.
• Experience with RAG systems, vector databases (Pinecone, Weaviate, pgvector), and embedding models.
• Proficiency with cloud infrastructure (AWS, GCP, or Azure), containerization (Docker, Kubernetes), and infrastructure-as-code tools such as Terraform or Pulumi.
• Experience with prompt engineering, model evaluation frameworks, and LLM observability tools such as LangSmith or Weights and Biases.
Company:
Klaviyo is an automation and email platform designed to help grow businesses. Founded in 2012, the company is headquartered in Boston, USA, with a team of 1001-5000 employees. The company is currently Late Stage.

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