Machine Learning (ML) Engineer

Who We’re Looking For

We’re looking for a Machine Learning Engineer who’s passionate about building real-world, scalable ML solutions. This role is for someone who’s not just into experimenting with models—but making sure they work in production and actually make an impact.

What You’ll Be Doing

• Designing and building ML pipelines using Airflow and Dagster
• Creating predictive models with TensorFlow, PyTorch, or Scikit-learn
• Deploying models on AWS SageMaker and Google Vertex AI
• Monitoring ML systems using Prometheus and Grafana
• Collaborating with cross-functional teams to ship models into production
• Setting up and managing CI/CD workflows with GitHub Actions, Jenkins, or GitLab

What You Bring

• Strong Python skills and hands-on experience with modern ML frameworks
• Proficiency with Airflow, Dagster, and cloud platforms like AWS and Vertex AI
• Experience using Prometheus and Grafana for monitoring
• Familiarity with CI/CD practices and automation tools

Bonus Points for Certifications

• AWS Certified Machine Learning – Specialty
• Google Professional Machine Learning Engineer
• Microsoft Certified: Azure AI Engineer Associate
• Certified Kubernetes Administrator (CKA)
• Any relevant certification in MLOps, DevOps, or Cloud Architecture

What Makes You Stand Out

• You think systematically and understand the full ML lifecycle
• You can explain complex technical concepts to non-technical people
• You collaborate well across functions and value feedback
• You’re globally minded and can work across cultures and time zones
• You communicate clearly and consistently with your team, raising issues early and keeping everyone informed

What We Offer

• Meaningful, high-impact projects with top-tier clients
• A collaborative, innovation-driven environment
• Continuous learning and support for certifications
• Flexible work options and a people-first team culture