Use the latest cutting edge technologies such as LLMS, multimodal models to handle complex problems.
Work with large datasets, perform data preprocessing, and engineer relevant features to enhance model performance.
Build frameworks that allow us to iterate and evaluate model versions (ranking, accuracy, latency).
Deploy Models at Scale: Collaborate with software engineers to deploy machine learning models into production, ensuring seamless integration with existing systems.
Monitoring and Maintenance: Implement monitoring solutions to track model performance in real-time and perform regular maintenance and updates as needed.
Collaboration: Work closely with cross-functional teams, including data scientists, software developers, and business analysts, to understand requirements and deliver impactful solutions.
Research and Innovation: Stay abreast of the latest advancements in machine learning and contribute to the research and development of innovative solutions.

Requirements

3+ years of experience in similar role, focus on developing and deploying ML models in production environments
Experience with optimizing models for size, cost, and latency is a plus.
Proficient in designing, developing, and operating fine-tuning pipelines in production environments
Experience with large-scale data processing and distributed systems
Strong programming skills in Python, and proficiency in machine learning libraries such as PyTorch, Tensorflow etc.

Benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

machine learningdata preprocessingfeature engineeringmodel evaluationmodel deploymentmodel monitoringmodel maintenancePythonPyTorchTensorFlow

Soft Skills

collaborationcommunicationproblem-solvinginnovation