India Job Openings
Uniphore
Machine Learning Operations Engineer
Bengaluru
FULL TIME
September 1, 2024
Uniphore infuses AI into every part of the enterprise that impacts the customer. We deliver the only multimodal architecture centered on customers that combines Generative AI, Knowledge AI, Emotion AI, workflow automation and a co-pilot to guide you. We understand better than anyone how to capture voice, video and text and how to analyze all types of data.
As AI becomes more powerful, every part of the enterprise that impacts the customer will be disrupted. We believe the future will run on the connective tissue between people, machines and data: all in the service of creating the most human processes and experiences for customers and employees.
About the role
- Take prototypes developed by the AI team and drive them into production, ensuring smooth deployment and management of ML models on cloud at scale.
- Collaborate with platform engineers to effectively manage cloud compute resources for ML model deployment, monitoring, and performance optimization.
- Monitor real-time performance of deployed models, analyse performance data, and proactively identify and address performance issues to ensure optimal model performance.
- Work in a highly collaborative and diverse team environment, actively contributing to team goals, participating in fast development cycles, and adapting to evolving project requirements.
- Collaborate with the wider team to develop and implement best practices for MLOps, including CI/CD pipelines, version control, model versioning, and automated model deployment.
- Stay up-to-date with the latest advancements in MLOps technologies and best practices, and provide expertise in recommending and implementing new tools and techniques to improve the efficiency and effectiveness of ML model deployment and management processes.
- Troubleshoot and resolve production issues related to AI model deployment, performance, and scalability in a timely and efficient manner.
- Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field.
- Minimum of 3 years of hands-on experience in MLOps, deploying and managing machine learning models in production environments, preferably in cloud-based environments.
- Hands-on experience with any of the MLOPs frameworks (Sagemaker, Deep Speed, Seldon, DVC, etc.)
- Strong experience with tools and technologies such as Git, Docker, Kubernetes, Jenkins, CI/CD pipelines, monitoring and logging frameworks, and cloud platforms (e.g., AWS, GCP, Azure).
- Solid understanding of machine learning concepts and workflows, and familiarity with popular machine learning frameworks and libraries (e.g., Tensor Flow, Py Torch) (e.g., scikit-learn).
- Familiarity with multiple LLMs and optimization techniques (PEFT, Lo RA, etc.)
- Experience with deployment and management of natural language processing (NLP) models, question answering (QA) systems, or chatbot applications is highly desirable.
- Strong problem-solving and analytical skills, with the ability to troubleshoot and resolve complex technical issues related to ML model deployment and performance.
- Excellent teamwork and collaboration skills, with the ability to work effectively in cross-functional teams, adapt to fast iteration cycles, and contribute to team goals.
- Strong communication skills, with the ability to communicate complex technical concepts to both technical and non-technical stakeholders.
Location preference:
Uniphore is an equal opportunity employer committed to diversity in the workplace. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, disability, veteran status, and other protected characteristics.
For more information on how Uniphore uses AI to unify—and humanize—every enterprise experience, please visit www.uniphore.com.
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