Senior Machine Learning Engineer

Responsibilities
Developing data pipelines to collect, process, and analyze diverse datasets at scale.
Designing and implementing deep learning architectures capable of processing large volumes of
data.
Analyzing model performance by conducting experiments and tests to evaluate effectiveness and
identify opportunities for improvement.
Building and managing agentic workflows to support scalable and efficient AI/ML solutions.
Optimizing and fine-tuning existing machine learning models to improve performance and
effectiveness.
Building and maintaining pipelines to monitor, manage, and continuously improve production
machine learning and deep learning models.

Qualifications

A bachelor’s, master’s, or PhD degree , with at least 2–6 years of relevant experience.
Experience training, building, and deploying large-scale deep learning models is required.
Experience designing and implementing sequence and time-series models is required.
Expertise in Python, with hands-on experience using deep learning frameworks such as PyTorch
or TensorFlow.
Experience with Git, CI/CD pipelines, and MLOps practices for automating model deployment
and managing production machine learning workflows.
Working knowledge of Linux, SQL, Git, and Bash scripting.