Senior Machine Learning Ops Engineer

Key Skills

Amazon Simple Storage Service (S3), AWS, AWS Sagemaker, Deep Learning, Docker, HuggingFace, Large Language Models - LLMs, Machine learning techniques, MLOps tools, Natural Language Processing (NLP), Postgres, PyTorch, Seldon, TensorFlow

Job Description

Uniphore is one of the largest B2B AI-native companies—decades-proven, built-for-scale and designed for the enterprise. The company drives business outcomes, across multiple industry verticals, and enables the largest global deployments. 

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.

Uniphore is looking for a senior Machine Learning Engineer (MLE) who is passionate about developing MLOps platform for LLMs. You will develop platform services to design, optimize and deploy generative AI models by developing pipelines for their data, prompts, optimizations and serving. In this role as a senior technical staff, you will be expected to guide colleagues on project planning and execution, multitask effectively across several projects, teams and groups, and expand the sphere of influence beyond the immediate team to influence solutions. You will collaborate with AI scientists and platform engineers to come up with innovative and cross-disciplinary solutions to infuse LLM technology within the Uniphore products. You will be one of the go-to persons within the company with extensive technical expertise on LLM optimizations and serving. You should be knowledgeable of Conversational AI artifacts, IVR menus, Digital menus, Chat, App menus, Call Transcripts. You will be the LLM evangelist to demonstrate generative capabilities within the Uniphore platform and enable engineering organisation to develop generative AI products.

The ideal candidate has deep industry experience using MLOPs frameworks in model versioning, model deployment and model optimizations.

Skills & Responsibilities

• Minimum of a Master’s degree including Computer Science, Engineering, Statistics & Applied Mathematics, or related fields.
• Hands-on experience in developing production-ready ML services and operationalizing model life-cycle management.
• In-depth knowledge of LLM optimization and service techniques (PEFT, LoRA, etc.)
• In-depth knowledge of deep learning and expertise in PyTorch/TensorFlow.
• Expertise in developing and packaging models to services.
• Familiar with Transformers, and used Huggingface library and LLMs to solve NLP problems.
• Worked with large amounts of data and developed approaches to address quality issues, and ability to interpret data with a focus on business goals.
• Solid expertise in Python programming.

Relevant Technologies

• ML: Hugging Face, PyTorch.
• MLOPs: Sagemaker, DeepSpeed, Seldon, DVC
• Deployment: Docker, AWS.
• Datastores: Postgres, S3

Who You Are

• You hold a Masters with 3 to 5 years of experience in MLOPs or 7 - 10 years of relevant industry experience.
• You have demonstrated experience in designing and executing MLOPs solutions at scale in real-world applications.
• You have handled large real-world data and developed data pipelines to work with large, not-so-clean datasets.
• You have demonstrated collaboration and teamwork to solve hard problems.
• You have the ability to learn new skills and share know-how to team members to empower and elevate.

Benefits

• Uniphore offers a competitive offer and premium benefits, including insurance, leave and other perks

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.