Machine Learning Specialist

5 years

0 Lacs

Posted:1 day ago| Platform: Linkedin logo

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Work Mode

On-site

Job Type

Full Time

Job Description

About Impetus


Impetus Technologies is a digital engineering company focused on delivering expert services and products to help enterprises achieve their transformation goals. We solve the analytics, AI, and cloud puzzle, enabling businesses to drive unmatched innovation and growth.

Founded in 1991, we are cloud and data engineering leaders providing solutions to fortune 100 enterprises, headquartered in Los Gatos, California, with development centers in NOIDA, Indore, Gurugram, Bengaluru, Pune, and Hyderabad with over 3000 global team members. We also have offices in Canada and Australia and collaborate with a number of established companies, including American Express, Bank of America, Capital One, Toyota, United Airlines, and Verizon.



Looking for a ML Architect to define the end-to-end architecture of our ML systems—from data ingestion and model training to deployment and monitoring. The ML architect will strategize and implement scalable, secure, and maintainable architectures that meet business goals.


Roles & Responsibilities


Key Responsibilities

Design comprehensive ML system architectures, including MLOps workflows

Oversee data pipeline integration, training workflows, and CI/CD processes

Define model deployment strategies, versioning, monitoring, and scaling

Design Deep learning solutions for Audio and Videos

Partner with data scientists, engineers, and DevOps to bridge development and operations

Ensure compliance, governance, and performance benchmarks are met

Evaluate new ML tools and platform technologies to improve architecture

Stay up to date with the latest advancements in the fields of AI

Qualifications

Bachelor’s or Master's in CS, Software Engineering, or related field

Extensive experience (5+ years) in ML system architecture and MLOps

Experience with Deep learning solution development

Experience in designing and deploying GenAI/LLM based applications.

Proficiency in cloud platforms (AWS, GCP, Azure) and ML orchestration (e.g., Kubeflow)

Strong in software architecture, data engineering, and CI/CD best practices

Excellent communication skills and ability to drive technical consensus

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