Mid Level AI Model Trainer Jobs
Mid level ai model trainer jobs go to professionals ready to own annotation pipelines end to end, guide junior trainers, and make data quality decisions with limited oversight. Openings are spread across on-site, remote, and hybrid settings in Technology & Software, Banking & Financial Services, and Investment & Asset Management, with employers like PwC, Bosch, and Goldman Sachs hiring at this level now.
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We are seeking a highly skilled AI Engineer to design and build Generative and Agentic AI systems that transform how our company operates and serves customers. This role focuses on developing AI applications powered by large language models (LLMs), retrieval-augmented generation (RAG), Model Context Protocol (MCP) servers, and Agentic AI across the enterprise for internal and customer facing use cases.
The ideal candidate has strong experience with a modern AI/ML stack, including a profound Python experience, including AI relevant packages and tools, LLM architectures and frameworks, RAG, MCP, prompt engineering, use of AI tools, building teams of AI agents, and production-grade AI systems design and development.
You will work closely with technology, data, and business teams to build scalable AI solutions that drive operational efficiency and innovation across the enterprise.
Key Responsibilities:
- Design, build, and deploy scalable LLM-powered applications, solutions, and digital products for customer support, business use cases, and internal productivity.
- Develop AI agents, Agentic Platforms, and Agentic AI systems capable of reasoning, planning, and executing multi-step workflows.
- Implement Retrieval-Augmented Generation (RAG) architectures and pipelines to leverage proprietary data, and internal knowledge bases.
- Build MCP servers, multi-connectivity enabled and multi-modal Agentic platforms, and AI assistants to support internal teams and customer facing.
- Integrate AI/ML solutions with enterprise systems, APIs, and data platforms.
- Design prompt strategies, evaluation frameworks, and guardrails to ensure accuracy, security, and regulatory compliance.
- Optimize LLM performance through fine-tuning, prompt engineering, and model orchestration.
- Develop MLOps and LLMOps pipelines for monitoring, evaluation, and continuous improvement of AI systems.
- Help in forming buy or build decisions and work with external vendors, consultants and internal teams to deliver scalable top-quality AI solutions timely.
- Stay up to date with emerging advancements in AI/ML, Generative AI, Agentic frameworks, and model architectures.
Required Qualifications:
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Applied Mathematics, or related field.
- 5+ years of software engineering experience, including work with machine learning (ML) or AI systems.
- Hands-on experience building LLM-powered applications in production environments.
- Strong programming skills in Python, and familiarity with AI/ML relevant packages such as NumPy, Pandas, SciPy and Scikit-learn.
- Experience with LLM ecosystems such as:
- OpenAI / Anthropic / Google, Open-source LLMs
- Hugging Face
- LangChain, LlamaIndex, or similar orchestration frameworks
- Experience building RAG pipelines and working with vector databases.
- Understanding of prompt engineering, embeddings, and model evaluation.
- Experience building APIs, MCPs, and scalable backend services.
- Experience with Claude Code, Codex, Cursor, GitHub Copilot, or similar.
- Ability to collaborate with cross-functional teams.
- Passion for technology and AI.
Preferred Qualifications:
- Experience building AI agents, agentic platforms, or autonomous workflows.
- Familiarity with agent frameworks (LangGraph, AutoGen, CrewAI, Semantic Kernel, Frontier, etc.).
- Experience with fine-tuning LLMs or parameter-efficient training methods (LoRA, PEFT).
- Experience with cloud-based AI infrastructure (AWS, Azure, or GCP).
- Familiarity with Java, JS, and Java applications and environments.
- Experience with MLOps / LLMOps tools and evaluation pipelines.
- Experience implementing AI governance, observability, and guardrails.
Salary Range:
The pay range for this position is $135,000 to $200,000 annually. Actual compensation will vary based on multiple factors, including employee knowledge and experience, role scope, business needs, geographical location, and internal equity.
Perks and Benefits:
- 4 weeks accrued paid time off + 9 paid national holidays per year
- Free onsite gym at our Boston Location
- Tuition Reimbursement
- Low cost and excellent coverage health insurance options that start on Day 1 (medical, dental, vision)
- Robust health and wellness program and fitness reimbursements
- Auto and home insurance discounts
- Matching gift opportunities
- Annual 401(k) Employer Contribution (up to 7.5% of your base salary)
- Various Paid Family leave options including Paid Parental Leave
- Resources to promote Professional Development (LinkedIn Learning and licensure assistance)
- Convenient location directly across from South Station and Pre-Tax Commuter Benefits
About the Company
The Plymouth Rock Company and its affiliated group of companies write and manage over $2.3 billion in personal and commercial auto and homeowner's insurance throughout the Northeast and mid-Atlantic, where we have built an unparalleled reputation for service. We continuously invest in technology, our employees thrive in our empowering environment, and our customers are among the most loyal in the industry. The Plymouth Rock group of companies employs more than 1,900 people and is headquartered in Boston, Massachusetts. Plymouth Rock Assurance Corporation holds an A.M. Best rating of “A-/Excellent”
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Top Industries Hiring
- Technology & Software
- Banking & Financial Services
- Investment & Asset Management
- Education
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Mid Level AI Model Trainer Jobs: Frequently Asked Questions
How do I get a mid level ai model trainer job?
Position yourself around ownership, not just contribution. Highlight projects where you shaped annotation guidelines, resolved edge cases independently, or improved output quality at scale. Applications that show you can run a workflow without hand-holding, and that you have a point of view on model behavior, stand out at this level. Concrete examples of measurable impact matter more than credentials.
Which companies hire mid level ai model trainers?
Companies hiring mid level ai model trainers right now include PwC, Bosch, and Goldman Sachs, based on current listings on Migrate Mate as of November 2026. Hiring at this level comes from both large AI labs scaling their training operations and technology companies building proprietary models that need experienced trainers to maintain data quality.
Are there remote mid level ai model trainer jobs?
Yes, and remote availability is notably strong for this role. About 43% of mid level ai model trainer openings are remote or hybrid as of November 2026, reflecting the nature of annotation and evaluation work that translates well to distributed teams. Filtering by remote or hybrid on Migrate Mate will surface the current mix.
How do I move up to a mid level ai model trainer role?
Moving from entry level to mid level means shifting from executing tasks to owning them. That means building deeper expertise in a specific model type or domain, volunteering to lead annotation projects, and documenting the decisions you make so others can follow them. Demonstrating that your judgment produces consistently cleaner data over time is what earns a mid level title.
Which industries hire the most mid level ai model trainers?
Mid Level ai model trainer roles concentrate in Technology & Software, Banking & Financial Services, and Investment & Asset Management, based on current listings on Migrate Mate as of November 2026. These sectors drive demand because they are actively developing or refining AI products that require sustained human feedback to improve model accuracy and reduce harmful or incorrect outputs.