Machine Learning Engineer

We are hiring a Machine Learning Engineer on behalf of our client. This role involves designing, building, and deploying machine learning models into production systems at scale. It's a great opportunity for someone who enjoys turning research and data into real-world, impactful products, and who's comfortable working across the full ML lifecycle from experimentation to deployment.

Role & responsibilities

• Design, build, and optimize machine learning models for production use cases
• Develop and maintain ML pipelines for data preprocessing, training, and deployment
• Collaborate with data scientists to transition models from research to production
• Build and manage MLOps infrastructure (model versioning, CI/CD, monitoring)
• Optimize model performance for latency, scalability, and accuracy
• Work with large-scale datasets and distributed computing frameworks
• Deploy models as APIs/microservices and integrate with existing systems
• Monitor deployed models for drift, performance degradation, and retraining needs
• Collaborate with product, engineering, and data teams to define ML-driven solutions
• Stay current with the latest ML/AI research, tools, and best practices

Preferred candidate profile

• 0 to 2 years of experience in machine learning engineering or related role
• Bachelor's/Master's degree in Computer Science, Data Science, Engineering, or related field
• Strong programming skills in Python (experience with Java/Scala a plus)
• Hands-on experience with ML frameworks (TensorFlow, PyTorch, Scikit-learn)
• Solid understanding of ML algorithms (supervised/unsupervised learning, deep learning, NLP, computer vision as relevant)
• Experience deploying models using Docker, Kubernetes, and cloud platforms (AWS/GCP/Azure)