AI Engineer

dypsis.ai; United States; Remote; USD 30,000 - 39,000; Full time

Benefits offered by this job

Health insurance

Meal allowance

Job summary

dypsis.ai seeks an AI-focused engineer to build applied AI systems that improve workflows, knowledge access, and decision-making. The role covers ML, generative AI, agent-based apps, and federated learning from data prep to production integration.

You will develop Python pipelines, retrieval-augmented generation, and internal chatbots, collaborating with cross-functional teams to deploy scalable, observable ML solutions.

Qualifications

• Bachelor’s or Master’s degree in computer science, data science, artificial intelligence, or a related field.
• Strong Python skills and hands-on experience with AI or LLM frameworks such as CrewAI, LangChain, Transformers, or vLLM.
• Understanding of RAG architectures and vector storage, such as FAISS, Chroma, or PostgreSQL with pgvector.
• Experience building APIs, for example with FastAPI.
• Practical MLOps knowledge, including Docker, CI/CD, model versioning, and observability.
• Analytical problem-solving, clear communication, and a collaborative approach.

Responsibilities

• Develop AI applications and Python pipelines using LLM and machine learning frameworks.
• Build text and image retrieval-augmented generation systems and internal chatbots.
• Create automations for tasks such as document analysis, report generation, internal search, and decision support.
• Integrate and scale solutions with cross-functional teams, translating business needs into practical tools.
• Track model quality and performance, applying MLOps practices to production systems.
• Prepare data pipelines and train machine learning models.

Skills

Python

Analytical problem-solving

Clear communication

Collaborative approach

Education

Bachelor’s or Master’s in computer science or related field

Tools

LangChain

Transformers

vLLM

CrewAI

FastAPI

Docker

CI/CD

Model versioning

Observability

FAISS

Chroma

pgvector

Job description

Role overview

Build applied AI systems that improve operational workflows, knowledge access, and decision-making. The work spans machine learning, generative AI, agent-based applications, and federated learning, from preparing data and building prototypes through integrating and monitoring production solutions.

Responsibilities

• Develop AI applications and Python pipelines using LLM and machine learning frameworks.
• Build text and image retrieval-augmented generation systems and internal chatbots.
• Create automations for tasks such as document analysis, report generation, internal search, and decision support.
• Integrate and scale solutions with cross-functional teams, translating business needs into practical tools.
• Track model quality and performance, applying MLOps practices to production systems.
• Prepare data pipelines and train machine learning models.

Requirements

• Bachelor’s or master’s degree in computer science, data science, artificial intelligence, or a related field.
• Strong Python skills and hands-on experience with AI or LLM frameworks such as CrewAI, LangChain, Transformers, or vLLM.
• Understanding of RAG architectures and vector storage, such as FAISS, Chroma, or PostgreSQL with pgvector.
• Experience building APIs, for example with FastAPI.
• Practical MLOps knowledge, including Docker, CI/CD, model versioning, and observability.
• Analytical problem-solving, clear communication, and a collaborative approach.

Nice to have

• Further training or certifications in machine learning, deep learning, or MLOps.
• Experience with coding agents, context engineering, or LLM fine-tuning.
• Familiarity connecting AI tools to internal platforms such as chat, knowledge, or CRM systems.
• Interest in agentic systems and product-focused applied AI.

Benefits and work setup

• Annual salary of €27,000–€35,000, depending on experience and technical level.
• Health insurance and a meal allowance.