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Data & ML Engineer

Foster Weise Covey (Launch Foundry) · Tegucigalpa

Mid 🇬🇧 English
Python SQL TensorFlow PyTorch Git CI/CD MLOps LLMs embeddings NoSQL REST APIs C# .NET

Description du poste

About the role

We are building intelligent, production‑grade data systems that drive real business decisions. As a Data & ML Engineer you will bridge the gap between experimentation and impact, owning the full lifecycle from pipeline design to model deployment and monitoring.

Key responsibilities

  • Design and maintain scalable data architectures that feed machine‑learning models and analytical workflows.
  • Build, validate, and deploy supervised, unsupervised and recommender‑system models into production.
  • Automate ETL/ELT pipelines with built‑in quality, reliability and observability.
  • Implement MLOps practices: versioning, CI/CD, and monitoring for data and model drift.
  • Collaborate with AI Product Engineers to integrate models into APIs and services.
  • Perform cross‑validation, A/B testing and hyper‑parameter tuning aligned with business KPIs.
  • Document models, metrics and pipelines to ensure traceability in a production environment.

Required profile

  • 2–3 years of hands‑on experience in data engineering and machine learning.
  • Advanced Python and SQL skills (SQL Server, stored procedures, functions, jobs).
  • Strong AWS knowledge (Redshift, Athena, S3, Lambda, Step Functions, SNS/SQS, Personalize).
  • Experience with TensorFlow (advanced) and PyTorch (intermediate).
  • Solid grounding in ETL processes, statistical modeling, regression and classification techniques.
  • Proficiency in MLOps tools (Git, CI/CD, production model lifecycle management).
  • Intermediate English proficiency.

Required skills

  • Python
  • SQL (SQL Server)
  • AWS Redshift
  • AWS Athena
  • AWS S3
  • AWS Lambda
  • AWS Step Functions
  • AWS SNS/SQS
  • AWS Personalize
  • TensorFlow
  • PyTorch
  • Git
  • CI/CD
  • MLOps
  • LLMs and embeddings (plus)
  • NoSQL
  • REST APIs
  • C# / .NET (plus)

What we offer

  • A technical environment where your work ships to production and generates measurable business impact.
  • Collaboration with cross‑functional teams across multiple business units.
  • Clear growth path alongside a product and data team that values craftsmanship.

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Foster Weise Covey (Launch Foundry)

Tegucigalpa