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ML/AI Engineer

Lingaro
7 days ago
Full-time
Remote
Mexico
AI Services

    • The person we are looking for will become part of Data Science and AI Competency Center working in AI Engineering team. The key duties are:  
    • Design, deliver and scale GenAI solutions  
    • Practical and innovative implementations of LLM/ML/AI automation, for scale and efficiency 
    • Working with Data Science teams to implement AI Agents and Machine Learning models into production 
    • Design, delivery and management of industrialized processing pipelines 
    • Implementing AI /MLOps/LLMOps frameworks and supporting Data Science teams in best practices 
    • Gathering and applying knowledge on modern techniques, tools and frameworks in the area of ML Architecture and Operations 
    • Defining and implementing best practices in ML models life cycle and ML operations/LLM operations 
    • Gathering technical requirements & estimating planned work 
    • Presenting solutions, concepts and results to internal and external clients 
    • Creating technical documentation

    • At least 4+ years of Data engineering experience with last 1 year-experience in building Data processing  
    • At least 4+ years of experience in production-ready Python code development (e.g., microservices, APIs, etc.) 
    • At least 1+ years of experience with GenAI (various LLM models, agents, RAGs, prompt engineering, MCP, specification-driven-development) 
    • At least 2+ years of experience in production-ready ML-related code development 
    • Additionally for all levels: 
    • Good understanding of ML/AI concepts: types of algorithms, machine learning frameworks, model efficiency metrics, model life-cycle, AI architectures 
    • Good understanding of Cloud concepts and architectures, as well as working knowledge with selected cloud services, preferably Azure or GCP 
    • Experience in designing and implementing data pipelines 
    • Good communication skills 
    • Ability to work in a team and support others 
    • Taking responsibility for tasks and deliverables 
    • Great problem-solving skills and critical thinking 
    • Fluency in written and spoken English. 
    • Nice to have skills & knowledge:  
    • Experience with LangGraph, FastAPI, CosmoDB, Redis, SpyGlass, Kubernetes 
    • Experience in designing, programming ML algorithms, and data processing pipelines using Python 
    • Experience in at least one of following domains: Data Warehouse, Data Lake, Data Integration, Data Governance, Machine Learning, Deep Learning, MLOps 
    • Practical experience in MLOps/LLMOps tools like AzureML/AzureAI (or GCP equivalents) 
    • Practical experience with Databricks 
    • Practical experience in Spark/PySpark and Hive within Big Data Platforms like Databricks, EMR or similar 
    • Good understanding of CI/CD and DevOps concepts, and experience in working with selected tools (preferably GitHub Actions, GitLab, or Azure DevOps) 
    • Experience in productizing ML solutions using technologies like Spark/Databricks or Docker/Kubernetes.