AI/ML Engineer
DIGITALL Nature Corp
Praca zdalna
- Lokalizacja
- Remote (Bulgaria)
- Godziny pracy
- Full Time
- Opublikowano
- 19 paź 2026
Przed aplikowaniem sprawdź na stronie pracodawcy, czy oferta nadal jest aktualna, i zapoznaj się z pełnymi warunkami.
Opis stanowiska
Interfejs jest w języku polskim. Nazwy stanowisk i opisy pracodawców pozostają w oryginalnym języku publikacji, którym może być angielski.
At DIGITALL we dont just deliver technology we deliver the future! We are explorers, knowledge-hunters, tech geeks, problem solvers and game changers who want to inspire and be inspired. Our DIGITALL people are always one step forward: working with top-notch technologies, creating innovations ahead of the market trends, sharing the passion for discovering better ways. As a human-centric organization, our teams are built on mutual respect and open communication, allowing everyone to be authentic, express ideas and unleash their potential. We are proud of our DIGITALL bright minds and never stop developing their skills to keep pushing boundaries together and do what we love. DIGITALL operates globally with a team of 1000 experts in 16 locations across 8 countries.
We are seeking an AI/ML Engineer to build and operationalize AI solutions across RAG, agentic workflows, knowledge graphs, and machine learning. The role is hands-on and spans experimentation, backend development, deployment, evaluation, and production support.
This is your job:
Design and build RAG and agentic AI solutions from prototype through production;
Develop AI workflows using Python, LangGraph, LangChain, or comparable frameworks;
Build backend services and APIs using FastAPI, REST APIs, and containerized deployment patterns;
Develop retrieval pipelines covering ingestion, embeddings, indexing, retrieval, reranking, grounding, and citations;
Support GraphRAG and knowledge graph use cases that combine structured and unstructured information;
Build and maintain data and AI pipelines using Databricks;
Integrate AI applications with Azure and enterprise services, including identity, security, logging, and monitoring;
Evaluate solution quality using retrieval metrics, RAG evaluations, LLM-based evaluation, and human review;
Collaborate with engineers, architects, product teams, and domain specialists to move use cases into production;
Support technical documentation, troubleshooting, optimization, and post-production improvements.
Your qualifications:
3+ years of relevant software, data, machine learning, or AI engineering experience;
Strong programming capability in Python and experience building production APIs or backend services;
Hands-on experience with RAG, LLM applications, or agentic AI workflows;
Experience with FastAPI, REST APIs, Docker, Azure DevOps Git, and CI/CD;
Experience with Microsoft Azure and cloud-based application deployment;
Familiarity with Databricks, data pipelines, SQL, and common Python data/ML libraries;
Understanding of authentication, authorization, RBAC, secrets management, logging, and monitoring;
Experience evaluating AI systems through retrieval metrics, RAGAS or similar frameworks, or task-specific benchmarks;
Strong communication and collaboration skills across technical and non-technical teams;
Ability to take ownership and work iteratively from experimentation to secure, maintainable production solutions;
Master's degree in Computer Science, Engineering, Data Science, AI/ML, Statistics, or a related technical field.
Preferred: Experience with GraphRAG, knowledge graphs, ontologies, graph databases, Azure AI services, MCP, or enterprise technology environments.
Organizational information:
All applications will be treated in strict confidentiality.
Please note that only shortlisted candidates will be invited to an interview.
Originally posted on Himalayas