Machine Learning Engineer

We are hiring a ML Engineer , who would build, deploy, and maintain production-ready ML and GenAI solutions that solve real business problems. Own the end-to-end ML lifecycle from model development and deployment to monitoring, optimization, and scalability while collaborating closely with engineering and business teams to deliver measurable impact.

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We are a global digital product development firm that helps growth-stage companies gain the technology sophistication and maturity of leading modern digital businesses. We differentiate ourselves by delivering exceptional quality at scale and speed with our thinkstack accelerators. We started with the vision of being able to build amazing software fast. A new way to build software without any of the compromises that currently plague software development. A new way to focus on the outcomes instead of the tech, tools, methodologies, processes and vanity artifacts.

Why is thinkbridge a great place to work?

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thinkbridge is a place where you can:

1. Think bigger – because you have the time, opportunity, and support it takes to dig deeper and tackle larger issues.

2. Move faster – because you’ll be working with experienced, helpful teams who can guide you through challenges, quickly resolve issues, and show you new ways to get things done.

3. Go further – because you have the opportunity to grow professionally, add new skills, and take on new responsibilities in an organization that takes a long-term view of every relationship.

We live by five core values:

Experience Level:

Role Overview:

What You'll Do

• Architect end-to-end ML/AI solutions that actually work in production

• Build and maintain production-grade systems with proper monitoring, alerting, and continuous improvement.

• Make strategic technical decisions on approach, tools, and implementation

• Translate complex AI concepts into business value for clients

• Set technical direction for project teams through architecture and best practices

• Stay current with AI research and identify practical applications for client problems

What We're Looking For

Must-Haves:

• Strong Python proficiency with production ML experience.

• Hands-on experience deploying AND maintaining ML systems in production.

• Experience with both GenAI (LLMs, RAG systems) and classical ML techniques.

• Understanding of ML monitoring, drift detection, and model lifecycle management.

• Cloud deployment experience (Azure knowledge helpful; AWS experience highly valued)

• Containerization and basic MLOps practices.

Nice-to-Haves:

• Experience fine-tuning open-source models to match/beat proprietary models

• Advanced MLOps (CI/CD for ML, A/B testing, feature stores)

• Published work (papers, blogs, open-source contributions)

• Experience with streaming/real-time ML systems

Benefits;

What We Offer

• Dedicated Learning & Development Budget: Fuel your growth with a budget dedicated solely to learning.

• Cutting-Edge Projects: Work on exciting projects with the latest technologies

• Employee-Friendly Leave Policy: Recharge with ample leave options designed for a healthy work-life balance.

Work Environment

• Remote-First Culture: At thinkbridge, we all work from wherever we choose but come together during set hours to collaborate. Using simple online tools, we stay connected and get great work done.

• Leave & Time-off – All leaves taken are paid leaves. And all the leave and time off are likely pre-approved leaves intended for planned vacations, personal commitments, or any other needs requiring prior approval.

• Comprehensive Medical & Term Insurance: Full coverage for you and your family peace of mind.

• Work-From-Workweek (WWW): Twice or thrice a year, we come together for One-week sprints to collaborate in person, foster stronger team bonds, and align on goals. All travel expenses are covered in the form of allowance which is called as work week allowance.

• We organize city-wise, company-sponsored local meetups—fun-filled day outings with your colleagues!

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• We embrace diversity and ensure equal opportunity for everyone, fostering an inclusive workplace where all voices are valued.

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