Medior AI/ML Engineer

Kr Labs; United States; Remote; USD 90,000 - 130,000; Full time

Benefits offered by this job

Remote-first

Mentoring from senior engineers

AWS certification support

Job summary

Kr Labs is seeking an engineer to build practical AI and ML solutions for client projects. You will own delivery areas, combining Python data engineering with LLM-powered capabilities such as document processing and information retrieval.

You will implement data pipelines, LLM features, and retrieval components, plus deploy and operate services on AWS. Strong English communication and independent execution are essential.

Qualifications

• 2–4 years building and shipping software with Python, ideally with data or AI
• A relevant degree or strong portfolio of real projects/open-source work
• Experience cleaning, structuring, storing data, and building APIs around it
• Experience connecting language models to real data and validating answers
• Hands-on experience deploying and operating AWS services
• Professional English, clear communication and independent execution

Responsibilities

• Develop Python data-processing services and ETL pipelines for AI/ML workloads
• Implement LLM features such as RAG, conversational interfaces, summarization, and API automation (AWS Bedrock)
• Build and tune retrieval components and validate results
• Validate system behavior with accuracy checks and regression tests
• Deploy and operate services on AWS using Lambda, S3, API Gateway, Step Functions, ECS or Fargate
• Contribute to architecture and technical scoping, follow code review, testing, and documentation practices

Skills

Python development

Data engineering

LLM integration

AWS deployment

API design

Education

Bachelor's degree or equivalent

Tools

AWS Lambda

AWS S3

API Gateway

Step Functions

ECS / Fargate

Terraform / CDK

Job description

Role overview

Build practical AI and machine learning solutions for client projects, taking features from prototypes into dependable services. You will own defined areas of delivery, combining Python data engineering with LLM-powered capabilities such as document processing, conversational assistants, and information retrieval.

Responsibilities

• Develop Python data-processing services and ETL pipelines that prepare data for AI and machine learning workloads.
• Implement LLM features such as retrieval-augmented generation, conversational interfaces, summarization, and API-based automation, including with AWS Bedrock.
• Build and tune retrieval components, then check that they return useful, reliable results.
• Validate system behavior with accuracy checks and regression tests before release.
• Deploy and operate services on AWS using tools such as Lambda, S3, API Gateway, Step Functions, and, where appropriate, ECS or Fargate containers.
• Contribute to architecture and technical scoping with guidance from senior engineers; follow code review, testing, documentation, and handover practices.

Requirements

• Around 2-4 years building and shipping software with Python, ideally involving data or AI, or a portfolio demonstrating equivalent ability.
• A relevant degree or a strong portfolio of real projects or open-source work.
• Practical skills in cleaning, structuring, and storing data, and building APIs around it.
• Experience connecting language models to real data and checking the accuracy of their answers.
• Hands-on experience deploying and operating AWS services.
• Professional spoken and written English, plus clear communication, independent execution, and early escalation of risks.

Nice to have

• Client delivery or consulting experience, and experience moving prototypes into production.
• AWS certification or interest in earning one; support for certification is available.
• Familiarity with AI development frameworks, search-oriented databases, containers, orchestration, or infrastructure as code such as Terraform or CDK.
• Hungarian or German language skills.

Benefits and work setup

• Remote-first working arrangement, varied client projects, and ownership of meaningful live-system work.
• Mentoring from senior engineers and support for AWS certification.