Machine Learning Engineer

About the role

We’re looking for a skilled and pragmatic Machine Learning Engineer to help us build intelligent systems that power our products. In this role, you’ll design, deploy, and maintain ML models in production—working closely with data scientists, engineers, and product teams to turn prototypes into scalable, reliable services.

This position is ideal for someone who enjoys solving real-world problems with applied machine learning and cares deeply about model performance, efficiency, and impact.

Key responsibilities

What you’ll be doing

• Build, train, evaluate, and deploy machine learning models for a range of applications

• Collaborate with data scientists to productionize research and prototypes

• Optimize model performance for speed, accuracy, and scalability

• Integrate ML services into backend systems or APIs

• Monitor model behavior in production and implement tools for logging and retraining

• Write clean, modular, and tested code that fits into a shared codebase

• Contribute to architecture and infrastructure improvements for ML pipelines

• Stay current with advances in the ML and MLOps ecosystem

Requirements

What you’ll need to succeed

• 3+ years of experience in machine learning engineering or applied ML development

• Proficiency in Python and ML libraries (e.g., scikit-learn, PyTorch, TensorFlow)

• Solid understanding of data structures, algorithms, and software engineering principles

• Experience deploying ML models into production environments

• Familiarity with cloud platforms (AWS, GCP, or Azure) and containerization tools (e.g., Docker, Kubernetes)

• Ability to write production-quality code and collaborate in a team setting

• Strong debugging, performance profiling, and optimization skills

Preferred qualifications

These would be a plus

• Experience with real-time inference, stream processing, or edge ML

• Background in MLOps, feature stores, model versioning, and CI/CD for ML

• Familiarity with big data tools (Spark, Kafka, Airflow, etc.)

• Understanding of data governance, model fairness, and ethical AI

• Graduate degree in computer science, machine learning, or related field

How to apply

Let’s build smarter systems together

To apply, please send us:

• Your resume or LinkedIn profile

• A short note about why this role interests you

• Links to projects, GitHub repositories, or technical writing that showcase your work (optional)

We aim to respond to qualified applicants within one week. Our hiring process includes a technical interview, a practical ML case exercise, and final conversations with the engineering team.