Machine Learning Engineer

Job not on LinkedIn

🕒 July 29

🇨🇴 Colombia – Remote

💵 $2.5k - $4k / month

⏳ Contract/Temporary

🟡 Mid-level

🟠 Senior

🤖 Machine Learning Engineer

👻 Ghost score 19%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Hire Hangar Global

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2023

💼 Consulting

📣 Marketing

📦 Logistics

Consulting • Marketing • Logistics

Hire Hangar Global is a remote-first global recruitment and staffing marketplace that connects companies (from startups and tech firms to real estate and consulting agencies) with contract and full-time talent across marketing, sales, customer success, product, AI/data, and operational roles. The platform lists hundreds of remote positions across dozens of countries and supports hiring and scaling teams by offering sourcing, recruiting operations, and candidate placement services. Hire Hangar emphasizes flexible, contract-based engagements and positions itself as a hub for businesses looking to scale quickly and professionals seeking remote opportunities.

📋 Description

• Design, build, and maintain data pipelines for ingestion, transformation, and feature engineering • Develop, train, evaluate, and iterate on machine learning models for classification, regression, clustering, and NLP tasks • Fine-tune and adapt pre-trained LLMs and foundation models • Build and manage MLOps infrastructure, including model versioning, experiment tracking, and deployment pipelines • Work with structured and unstructured text, tabular, and time-series data at scale • Monitor production model performance and implement retraining and drift-detection strategies • Collaborate with engineering and product teams to turn data insights into AI features • Document data schemas, model architectures, and pipeline logic • Complete the application form and record a video as the first interview step

🎯 Requirements

• Strong Python skills with hands-on experience in core ML libraries (scikit-learn, PyTorch, TensorFlow, or similar) • Solid data engineering experience, including SQL, ETL pipelines, and large-scale datasets • Practical experience with model training, evaluation, hyperparameter tuning, and deployment • Familiarity with LLMs and transformer-based architectures • Experience with fine-tuning or prompt engineering in production contexts • Experience with experiment tracking and MLOps tooling (MLflow, Weights & Biases, DVC, or similar) • Strong grasp of statistical concepts, data quality principles, and model performance metrics • Prior remote work experience • Fluency with remote collaboration tools and platforms such as Slack, Zoom, Google Workspace, and Asana • Applications without prior remote-work experience will not be considered • Preferred: distributed data processing frameworks such as Spark or Dask • Preferred: vector databases and embedding-based retrieval systems • Preferred: real-time or streaming data pipelines using Kafka or Flink • Preferred: cloud-native ML platforms such as AWS SageMaker, GCP Vertex AI, or Azure ML • Preferred: data governance, lineage tracking, or compliance-aware data workflows • Ability to work US time zones (EST–PST) • English proficiency is required

🏖️ Benefits

• Competitive pay • Real growth opportunities • Long-term career opportunity • Remote work arrangement