Data Scientist / Machine Learning Engineer

📌 Position

Data Scientist - Machine Learning (Production & AI)

Location

Remote from LATAM

Contract Type

Full-time contractor (via In All Media)

Time Zone Alignment

US Time Zones (Central Time)

🧭 About In All Media

In All Media is a global technology and design firm focused on building impactful digital solutions through remote, distributed teams across LATAM. We partner with international clients across industries, providing long-term technical expertise, product innovation, and team augmentation.

🚀 Project Overview

The project centers on building, scaling, and maintaining end-to-end production machine learning pipelines and infrastructure in a cloud-native setting. The primary goal is to empower data-driven decision-making across the enterprise by delivering robust, scalable ML solutions. In this role, you will bridge model experimentation with production deployment, helping the team advance its core predictive algorithms while expanding into modern AI and LLM-driven capabilities.

🔍 Key Responsibilities

• ML Model Development & Deployment: Develop, deploy, and maintain production-grade Machine Learning (ML) models in cloud environments beyond local notebook development.
• Feature Engineering & EDA: Perform Exploratory Data Analysis (EDA) and design feature engineering pipelines to support production ML workflows.
• Pipeline Infrastructure: Build, maintain, and optimize data pipelines that feed and sustain ML models in production.
• Model Monitoring & Maintenance: Monitor model performance, health, and drift post-deployment to ensure continuous reliability in production.
• Cross-Functional Collaboration: Partner with software engineering, data, and business stakeholders to translate business goals into scalable ML solutions.
• AI & LLM Integration: Contribute to Artificial Intelligence (AI) and Large Language Model (LLM) based capabilities where applicable.

💡 Must-Have Skills

• Production ML Experience: 2+ years of professional experience building, deploying, monitoring, and maintaining production ML models in real-world environments.
• Programming & Data Languages: Strong Python programming skills along with advanced SQL capabilities.
• Enterprise ML Platforms: Experience utilizing AWS SageMaker or equivalent enterprise ML platforms (such as Google Vertex AI or Azure ML) to support production pipelines.
• Version Control & Autonomy: Proficient with Git for version control and a demonstrated ability to work independently within production settings.

🌟 Nice-to-Have Skills

• MLOps Ecosystem: Familiarity with MLOps and orchestration tools such as MLflow, Apache Airflow, or dbt (Data Build Tool).
• Data Warehousing: Hands-on experience working with Snowflake.
• Domain Expertise: Prior background in marketing, growth, experimentation, or causal inference.
• Generative AI: Practical experience working with LLMs (Large Language Models) or autonomous AI agents.
• Methodologies: Experience operating within Agile development environments.

🌐 Time Zone & Collaboration

The role requires alignment with US Time Zones. Candidates must be available during standard US business hours to ensure real-time collaboration with cross-functional engineering, data, and business partners.

💬 Language

All interviews, documentation, and daily communication will be conducted exclusively in English.

Note

This contract is managed through In All Media. We provide the platform and infrastructure for LATAM’s top talent to work with global leaders.