Machine Learning Engineer

2 weeks ago

Bengaluru, India Infiniti Research Full time

About Quantzig : .

Quantzig is a global analytics and advisory firm with offices in the US, UK, Canada, China, and India.

we have assisted our clients across the globe with end-to-end advanced analytics, visual storyboarding, Machine Learning, and data engineering solutions implementation for prudent decision making.

We are a rapidly growing organization that is built and operated by high-performance champions If you have what it takes to be the champion with business and functional skills to take ownership of an entire project end-to-end, help build a team with great work ethic and a drive to learn, you are the one we're looking for.

The clients love us for our solutioning capability, our enthusiasm and we expect you to be a part of our growth story.

Please find the job description below :

Experience : 4 to 5 Yrs.

Notice Period : Immediate Joiner.

Role : Machine Learning Engineer.

Responsibilities :

- Design and maintain engineering infrastructure to support enterprise machine learning systems in Azure cloud.

- Support model development, with following industry best practices on auditability, versioning, and data security.

- Facilitate development and deployment of proof-of-concept machine learning solutions.

- Collaborate with Data Scientists to take offline machine learning model solutions and deploy them into production system.

- Very good hands-on experience in deploying end-to-end ML solutions as a ML DevOps Engineer, or Data Engineer.

- Manage stakeholders and drive timely execution of projects using agile methodologies.

- Build reliable and scalable solutions in a fast-paced work environment.

- Knowledge sharing with other team members on technical skills and best practices.

Desired Skillset :


- University degree in Computer Sciences or a similar field of studies.

- At least 3 to 5 years of relevant experience in deploying ML solutions into production systems.

- Exposure to machine learning frameworks and best practices.

- Deep knowledge in Python, T SQL, database systems.

- Ability to translate business needs into technical requirements.

- Familiarity with data-oriented workflow orchestration frameworks such as AirFlow, KubeFlow etc.

- Very high data affinity and strong analytical skills

(ref:hirist.tech)

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