Senior Advisor - Machine Learning Engineer

Sr Advisor ML Engineer

Data Science is all about breaking new ground to enable businesses to answer their most urgent questions. Pioneering massively parallel data-intensive analytic processing, our mission is to develop a whole new approach to generating meaning and value from petabyte-scale data sets and shape brand new methodologies, tools, statistical methods and models. What’s more, we are in collaboration with leading academics, industry experts and highly skilled engineers to equip our customers to generate sophisticated new insights from the biggest of big data.

Join us to do the best work of your career and make a profound social impact as a Sr Advisor on our Machine Learning Engineer Team in Bangalore.

What you’ll achieve

The AI ML Ops Engineer will play a critical role in harnessing the power of our AI initiatives. This role involves a combination of responsibilities from the realms of data science ( ML and DL ), software engineering, and operations. The individual will work on developing, deploying, maintaining, and innovating AI/ML systems in production. The role demands expertise in Generative AI models, Large Language Models (LLMs), and container orchestration technologies like Docker and Kubernetes. An in-depth understanding of MLOps principles and practices is essential, along with a capacity to thrive in a fast-paced, dynamic environment. The AI ML Ops Engineer will also be required to take part in strategic planning, roadmap development, and technical leadership.

You will:

•Develop, deploy, and maintain AI/ML models into production environment.

•Apply knowledge of machine learning, deep learning, statistics, optimization, software engineering, and data engineering to produce code for testing, operationalizing, and governing software-integrated machine learning models.

•Work closely with various stakeholders, including business owners, software engineers, data scientists, and data engineers to align and execute end-to-end solutions. These solutions should begin with data collection and management, extend through machine learning methodologies and efficiencies in software engineering, and culminate in the governance of machine learning model performance.

•Implement MLOps (Machine Learning Operations) strategies to automate and enhance the ML lifecycle.

Take the first step towards your dream career
Every Dell Technologies team member brings something unique to the table. Here’s what we are looking for with this role:

Essential Requirements

•Bachelor's or Master's degree in Computer Science, Information Technology, AI, Machine Learning, or a related field.

•7- 10 years of experience as an AI/ML Ops Engineer or similar role in an AI/ML environment.

•In-depth understanding of Generative AI models and Large Language Models (LLMs).

•Solid background in Data Science and Software Engineering.

•Experience with containerization technologies like Docker and orchestration systems like Kubernetes.

•Proficiency in implementing MLOps processes, methodologies, and tools.

Desirable Requirements

•Certifications in AI, ML, Kubernetes, or cloud environments are a plus.

•Experience with CI/CD pipelines, Jenkins, Git, or similar tools..

Who we are

We believe that each of us has the power to make an impact. That’s why we put our team members at the center of everything we do. If you’re looking for an opportunity to grow your career with some of the best minds and most advanced tech in the industry, we’re looking for you.

Dell Technologies is a unique family of businesses that helps individuals and organizations transform how they work, live and play. Join us to build a future that works for everyone because Progress Takes All of Us.

Application closing date: 30 April 2024

Dell Technologies is committed to the principle of equal employment opportunity for all employees and to providing employees with a work environment free of discrimination and harassment. Read the full Equal Employment Opportunity Policy here.

Dell’s Flexible & Hybrid Work Culture

At Dell Technologies, we believe our best work is done when flexibility is offered.

We know that freedom and flexibility are crucial to all our employees no matter where you are located and our flexible and hybrid work style allows team members to have the freedom to ideate, be innovative, and drive results their way. To learn more about our work culture, please visit our locations page.