Machine Learning Engineer - Cloud Services

Machine Learning Engineer – Cloud Services - Python, AWS, SageMaker

Location: Hyderabad, India (Hybrid – 3 days office / 2 days remote)
Requires 25% overlap with US ET

About Nasuni

Nasuni is the unstructured data foundation for enterprise teams—and the AI that supports them. We manage, protect, and activate the world’s unstructured data so organizations can work smarter, spend wisely, and create safely without limits. As a Vista-backed SaaS data infrastructure company, Nasuni is transforming how enterprises manage file data with a next-generation, AI-ready platform—turning massive file stores into secure, actionable, and AI-ready data for intelligent automation, analytics, and global collaboration.

Why Work at Nasuni (Hyderabad / India)

With Vista Equity Partners’ backing, our Hyderabad team benefits from access to a global ecosystem of software leaders—cross-portfolio learning, leadership programs, and AI innovation communities—combining the pace of a fast-growing company with the scale and resources of a global technology investor. You’ll innovate at the intersection of cloud, AI, and enterprise data infrastructure, collaborate with talented teams, and build modern platforms trusted by enterprises worldwide. Join us in Hyderabad and help shape the future of intelligent, AI-ready data management.

Role Overview

We are hiring a Machine Learning Engineer to help design, build, and maintain ML-powered capabilities within Nasuni’s Cloud Services platform.

This role is ideal for engineers who:

• Have hands-on experience building enterprise production ML solutions
• Want to grow in production ML software product systems
• Enjoy solving data and modeling problems in a cloud environment
• Thrive in collaborative software product engineering teams

This is a hands-on implementation role focused on delivering reliable ML features and improving existing systems.

Level & Scope Definition

• Implement and enhance ML pipelines within defined product areas.
• Contribute to system design discussions while receiving architectural guidance from senior engineers.
• Deploy and monitor models in production with support from platform teams.
• Responsible for quality and reliability of assigned ML components.
• Collaborate with product, data, and cloud engineering teams to deliver practical ML solutions.

Key Responsibilities

• Build and maintain ML pipelines including data preprocessing, feature engineering, model training, evaluation, and deployment.
• Build ML systems using AWS, Python, SageMaker. 
• Implement supervised learning models such as classification, regression, ranking, or time-series.
• Integrate foundation model APIs (e.g., embeddings, prompt-based workflows) into internal tools or features.
• Assist in developing RAG-style workflows or AI-assisted features under guidance.
• Monitor model performance and participate in debugging and optimization.
• Conduct exploratory data analysis and improve data quality.
• Support A/B tests and evaluation experiments.
• Document implementations and contribute to engineering best practices.

Must-Have Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or related field.
• 3-5 years of hands-on experience building ML solutions beyond academic projects.
• Strong programming skills in Python.
• Strong working experience in SQL.
• Experience with at least one cloud platform (AWS, Azure, or GCP).
• Experience deploying models or services in cloud environments.
• Practical experience with supervised machine learning techniques.
• Exposure to foundation models or generative AI via APIs.
• Experience contributing to production ML systems.

Preferred Qualifications

• Familiarity with containers (Docker) and CI/CD workflows.
• MLflow (ML lifecycle platform), Amazon SageMaker (managed ML service), DVC – Data Version Control (data and model versioning tool), or similar MLOps tools.
• Experience working in SaaS Product Companies or cloud-based environments.

Ideal Qualifications

• Contributed to an ML feature used by external customers.
• Experience improving model performance in production.
• Exposure to RAG or AI assistant workflows.
• Experience collaborating with distributed teams.

Experience Guidelines

• 3-5 years of hands-on experience building ML solutions beyond academic projects.
• Academic-only experience does not meet minimum requirements.

Why Work at Nasuni – Hyderabad?

As part of our commitment to your well-being and growth, Nasuni offers competitive benefits designed to support every stage of your life and career:

• Competitive compensation programs
• Flexible time off and leave policies
• Comprehensive health and wellness coverage
• Hybrid and flexible work arrangements
• Employee referral and recognition programs
• Professional development and learning support
• Inclusive, collaborative team culture
• Modern office spaces with team events and perks
• Retirement and statutory benefits as per Indian regulations

To all recruitment agencies: Nasuni does not accept agency resumes. Please do not forward resumes to our job boards, Nasuni employees or any other company location. Nasuni is not responsible for any fees related to unsolicited resumes.

Nasuni is proud to be an equal opportunity employer. We are committed to fostering a diverse, inclusive, and respectful workplace where every team member can thrive. All qualified applicants will receive consideration for employment without regard to race, religion, caste, color, sex, gender identity or expression, sexual orientation, disability, age, national origin, or any other status protected by applicable laws in India or the country of employment. We celebrate individuality and are committed to building a workplace that reflects the diversity of the communities we serve. If you require accommodation during the recruitment process, please let us know.