Junior AI/ML Engineer

Requirements:

• Good proficiency in Python; familiarity with building APIs using FastAPI (or a similar web framework).  

• Basic understanding of the AI application development lifecycle (data → prompting/model calls → evaluation → deployment).  

• Hands-on familiarity with at least one major LLM platform/API (e.g., OpenAI, Anthropic, Amazon Bedrock, or Gemini) and awareness of common LLM frameworks (e.g., LangGraph, LlamaIndex, agent frameworks).  

• Understanding of common LLM integration patterns such as RAG and basic agent workflows.  

• Exposure to deploying applications (cloud or on-prem) and understanding of fundamentals like logging, configuration, and performance basics.  

• Ability to run and interpret simple quality checks for generative AI (e.g., retrieval success, basic classification metrics, and human/LLM-assisted review).  

• Strong problem-solving skills, attention to detail, and willingness to learn.  

• Clear communication skills and ability to collaborate in a team environment.
   

Responsibilities: 

• Support the design, implementation, and maintenance of AI applications such as chatbots, Q&A tools, and agent-based workflows under guidance from senior engineers.  

• Work with the team to gather requirements and understand user needs; help translate them into LLM-powered features and prototypes.  

• Help build and maintain data pipelines, prompt templates, and small-to-medium datasets to improve model outputs.  

• Assist with testing and evaluation of AI system quality (accuracy, safety, latency), and document findings and improvements.  

• Contribute to rapid prototyping (proofs of concept) to validate technical feasibility and demonstrate value to stakeholders.  

• Follow engineering best practices (version control, code reviews, documentation) and continuously learn new LLM tools and techniques.  

Nice to have  

• Experience running small experiments (e.g., prompt variants) and learning from user feedback.  

• Basic understanding of retrieval systems (keyword search, vector search, embeddings) and how they support RAG.  

• Experience building simple UIs or demos using Streamlit, Gradio, or similar tools.  

• Awareness of emerging protocols/standards in the LLM ecosystem (e.g., MCP, A2A, ACP).  

• Exposure to cloud AI platforms (Azure OpenAI, Amazon Bedrock, GCP Vertex AI) or local model serving (e.g., vLLM).  

• Familiarity with enterprise AI tooling (e.g., Databricks, AWS, Azure AI services) is a plus. 

• Some experience with observability/monitoring concepts (logs, traces, dashboards) for AI applications. 

What we offer: 

• Annual paid vacation of 18 working days. 

• Extra vacation days for long-lasting cooperation. 

• Annual paid sick leave of 10 days. 

• Maternity/Paternity leave. 

• The opportunity for sabbatical leave. 

• Marriage and Parenthood Package. 

• Compensation for sports activities or health insurance covering (up to 250$ per year) — after the trial period. 

• Career development plan. 

• English and Spanish classes. 

• Paying taxes and managing PE (Private Entrepreneur). 

• Technical equipment. 

• Internal Referral program. 

• Opportunity to take part in company volunteering activities. 

• Sombra is a “Friendly to Veterans” award-holder.