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Senior ML Engineer (GenAI, AWS)

6 hours, 7 minutes ago
Colombia
Full-time
Senior
Machine Learning Engineer
Software Development
Apache Spark AWS CI/CD CloudFormation Docker Feature Engineering GCP Generative AI Machine Learning MLflow MLOps NumPy Pandas Python PyTorch Reinforcement Learning SageMaker SQL TensorFlow Terraform Transformers
Apply Now
Provectus

Provectus

Provectus provides consulting services in artificial intelligence and machine learning, assisting businesses in integrating AI solutions to meet their unique objectives and enhance their operational capabilities across various industries.

Professional Services
251-1K
Founded 2010
View All Jobs 35

Description

  • Design and implement end-to-end machine learning solutions from experimentation to production.
  • Build scalable ML pipelines and infrastructure.
  • Optimize model performance, efficiency, and reliability.
  • Write clean, maintainable, production-quality code.
  • Conduct rigorous experimentation and model evaluation.
  • Troubleshoot and resolve complex technical challenges.
  • Mentor junior and mid-level ML engineers.
  • Conduct code reviews and provide constructive feedback.
  • Collaborate with cross-functional teams including DevOps, Data Engineering, and Solutions Architects.
  • Contribute to internal ML practice development, reusable accelerators, and architectural discussions.

Requirements

  • Strong understanding of machine learning fundamentals, including supervised, unsupervised, and reinforcement learning.
  • Experience with feature engineering, model training, evaluation, hyperparameter tuning, and validation.
  • Experience with classical ML libraries and frameworks such as TensorFlow, PyTorch, or similar.
  • Knowledge of deep learning architectures including CNNs, RNNs, and Transformers.
  • Experience building production LLM-based applications.
  • Ability to design effective prompts and chain-of-thought strategies.
  • Experience building retrieval-augmented generation (RAG) architectures.
  • Familiarity with embedding models, vector search, and vector databases.
  • Experience with LLM evaluation metrics and techniques.
  • Advanced proficiency in Python and strong data manipulation skills with pandas and numpy.
  • Ability to work with SQL, ETL/ELT pipelines, and distributed computing frameworks such as Spark.
  • Experience deploying ML models to production, with Docker, CI/CD, and monitoring/observability.
  • Familiarity with experiment tracking tools such as MLflow or Weights & Biases.
  • Strong experience with AWS ML services such as SageMaker and Lambda.
  • Advanced knowledge of GCP ML and data services.
  • Experience with cloud-native ML architectures and infrastructure as code tools such as Terraform or CloudFormation.
  • Preferred: practical experience with AWS services such as ECR, EMR, and S3.
  • Preferred: practical experience with deep learning models, taxonomies or ontologies, Spark or Dask, and Great Expectations.

Benefits

  • Long-term B2B collaboration.
  • Fully remote work setup.
  • Budget for medical insurance.
  • Paid sick leave, vacation, and public holidays.
  • Continuous learning support, including unlimited AWS certification sponsorship.

Interested in this position?

Apply directly on the company website

Apply Now

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