Machine Learning Software Engineer bridging machine learning research and production deployment at Mobileye. Developing robust solutions and managing scalable production systems.
Responsibilities
Your role will include developing production deployment systems for classical and machine learning algorithms from research and building robust, scalable inference pipelines.
You will develop primarily in Python and infrastructure tools (Kubernetes, Docker, etc.), taking part in both maintaining existing deployment systems and developing new production capabilities.
Finally, you will need to learn and implement new deployment technologies and best practices that can address emerging production challenges as they arise, while staying current with the latest MLOps and inference optimization techniques.
Requirements
B.Sc. in Computer Science, Software Engineering, or related technical field.
2+ years of experience in production software development, preferably in ML deployment.
Strong problem-solving skills and ability to tackle complex, real-world production challenges.
Proficiency in Python and experience with containerization and orchestration technologies (Docker, Kubernetes)- advantage.
Hands-on experience with model serving frameworks and inference optimization- advantage.
Background in distributed systems and cloud infrastructure- advantage.
Designing and operating cloud - based MLOps capabilities supporting analytical and generative AI models. Collaborating with data science and business teams for high - impact AI solutions.
Machine Learning Engineer analyzing data structures and developing ML models for customer profiling in Azerbaijan. Collaborating on probabilistic modeling and data quality improvement.
Machine Learning Engineer at HackerRank working on integrity systems to improve model quality. Collaborating on strategies for new signals like audio analysis and behavioral anomalies.
Machine Learning Engineer developing integrity systems for assessing model quality at HackerRank. Collaborating on multimodal signal processing and improving model performance.
Architect designing enterprise - grade AI/ML architectures for Quantiphi. Leading AI applications and ML strategy with a focus on scalability, security, and integration.
Software Engineer for ML Infrastructure at Slack, architecting systems to support large scale AI deployment and reliability. Engage in deep systems engineering focusing on ML lifecycle and infrastructure scalability.
Machine Learning Engineer at Winnow developing AI solutions for food waste reduction. Collaborate with cross - functional teams and leverage cutting - edge technologies in food recognition.
Senior Engineer developing AI/ML solutions to enhance patient care at Edwards Lifesciences. Collaborating with cross - functional teams to deliver impactful technologies in healthcare.
Machine Learning Engineer designing and deploying machine learning models for DXC Technology. Collaborating with data scientists and optimizing solutions for impactful results.
Senior Machine Learning Engineer at APS leading MLOps initiatives and collaborating across teams. Designing and implementing scalable machine learning solutions with a focus on real - time decision - making.