Software Engineer 2

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 in computer science or a related field, 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.