Senior Machine Learning Engineer

LocationCali, Colombia

Work moderemote

Typefull-time

SenioritySenior

Experience5+ yrs

DepartmentCSA Billable

Company size5,001–10,000 people

First seenOct 10, 2026 · 1d ago

Verified live1d ago

At a glanceSummarised by Seekless from the posting.

Bachelor’s or Master’s degree in Computer Science, Machine Learning, Data Science, or a related field, or equivalent practical experience

5+ years of industry experience building, deploying, and scaling Machine Learning systems

Deep expertise in Python, SQL, and PySpark for distributed data processing

Hands-on experience with machine learning frameworks such as Scikit-learn, PyTorch, TensorFlow, and XGBoost

Proven experience designing and managing production ML pipelines using MLflow or similar tools

Experience deploying and operating ML solutions in cloud environments such as AWS, Azure, GCP, or Databricks

Strong understanding of end-to-end ML lifecycles, including data ingestion, training, evaluation, deployment, and monitoring

Hands-on experience with Docker, Kubernetes, and containerized ML workloads

Excellent communication skills and the ability to influence cross-functional teams

Experience working with healthcare datasets, including claims, eligibility, pharmacy, or EHR data

Advanced degree (M.S. or Ph.D.) in Computer Science, Data Science, Machine Learning, or a related field

Strong understanding of MLOps practices, including CI/CD for Machine Learning, model versioning, and automated retraining

Experience with deep learning techniques for time series forecasting, sequential data, or hierarchical modeling

Experience designing model evaluation frameworks, experimentation protocols, and performance metrics

Familiarity with Kubernetes-native ML platforms such as Kubeflow, KServe, or Airflow on Kubernetes

Experience working in fast-paced, high-growth environments with multiple concurrent priorities

We hire professionals based solely on their skills and qualifications and do not discriminate based on age, disability, religion, gender, sexual orientation, socioeconomic status, or nationality

Skills

Machine Learning

Python

PySpark

Databricks

MLOps

Kubernetes

Docker

SQL

Scikit-learn

PyTorch

TensorFlow

XGBoost

MLflow

AWS

Azure

GCP

Kubeflow

KServe

Airflow

Job Title: Senior Machine Learning Engineer

Key Skills: Machine Learning, Python, PySpark, Databricks, MLOps, Kubernetes

Experience: 5+ YOE.

Location: Colombia

Mode: Remote.

About the role

We at Coforge are hiring Senior Machine Learning Engineer (#15311-1-5) with the following skill set.

Key Responsibilities

· Lead the design and implementation of scalable, production-grade Machine Learning systems in cloud environments.

· Architect and deliver end-to-end ML solutions, from data ingestion and feature engineering to deployment and monitoring.

· Design and manage containerized ML workloads using Docker and Kubernetes for model training, batch inference, and real-time serving.

· Oversee large-scale data pipelines processing multi-terabyte datasets and ensure reliability and performance.

· Lead experimentation strategies, including A/B testing, model validation, and lifecycle management using platforms such as MLflow and Databricks.

· Drive continuous model improvement through automated retraining, model monitoring, bias mitigation, and performance optimization.

· Evaluate and prototype emerging AI/ML technologies, frameworks, and architectures.

· Collaborate with Product, Engineering, Data, and Leadership teams to define and execute ML initiatives aligned with business goals.

· Establish engineering standards, code quality practices, and technical documentation.

· Mentor engineers and provide technical leadership across Machine Learning initiatives.

Required Skills & Qualifications

· Bachelor’s or Master’s degree in Computer Science, Machine Learning, Data Science, or a related field, or equivalent practical experience.

· 5+ years of industry experience building, deploying, and scaling Machine Learning systems.

· Deep expertise in Python, SQL, and PySpark for distributed data processing.

· Hands-on experience with machine learning frameworks such as Scikit-learn, PyTorch, TensorFlow, and XGBoost.

· Proven experience designing and managing production ML pipelines using MLflow or similar tools.

· Experience deploying and operating ML solutions in cloud environments such as AWS, Azure, GCP, or Databricks.

· Strong understanding of end-to-end ML lifecycles, including data ingestion, training, evaluation, deployment, and monitoring.

· Hands-on experience with Docker, Kubernetes, and containerized ML workloads.

· Excellent communication skills and the ability to influence cross-functional teams.

Preferred Skills

· Experience working with healthcare datasets, including claims, eligibility, pharmacy, or EHR data.

· Advanced degree (M.S. or Ph.D.) in Computer Science, Data Science, Machine Learning, or a related field.

· Strong understanding of MLOps practices, including CI/CD for Machine Learning, model versioning, and automated retraining.

· Experience with deep learning techniques for time series forecasting, sequential data, or hierarchical modeling.

· Experience designing model evaluation frameworks, experimentation protocols, and performance metrics.

· Familiarity with Kubernetes-native ML platforms such as Kubeflow, KServe, or Airflow on Kubernetes.

· Experience working in fast-paced, high-growth environments with multiple concurrent priorities.

Posted On: 09-10-2026

Legal

At Coforge, we hire professionals based solely on their skills and qualifications and do not discriminate based on age, disability, religion, gender, sexual orientation, socioeconomic status, or nationality.

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