Product Engineer

Role:
Product Engineer – Machine Learning

Experience:

5+ Years

Employment Type:

Full-time

About Us

We are a global technology company building a unified platform for customer-facing experiences, enabling organizations to deliver human, consistent, and scalable customer interactions across modern digital channels. Our products power some of the world’s most complex enterprise use cases, operating at massive scale and impact.

We believe in building technology that blends AI, data science, and product engineering to create meaningful customer experiences—and we’re just getting started.

Role Overview

As a Product Engineer – Machine Learning, you will design and deliver next-generation machine learning solutions for digital customer experience applications. This role is highly collaborative, combining deep technical expertise with product thinking to build scalable, production-grade ML systems.

What You Will Do

- Work closely with a collaborative team of machine learning engineers and data scientists.
- Build solutions across multiple ML disciplines including:
- Deep Learning
- Reinforcement Learning
- Computer Vision
- Natural Language Processing
- Speech Processing
- Partner with Product Management and Design teams to define scope, priorities, and delivery timelines.
- Collaborate with ML leadership to define and implement technology and architectural strategies.
- Take partial ownership of the technical roadmap, including:
- Planning and scheduling
- Milestones and delivery
- Risk identification and mitigation
- Technical trade-offs and course correction
- Design, deliver, and maintain high-quality, scalable ML systems in a cost-effective and timely manner.
- Identify opportunities to apply cutting-edge research to real-world product use cases.
- Stay current with industry trends, emerging technologies, and data science advancements, and integrate relevant innovations into workflows.

What Makes You Qualified

- Bachelor’s or Master’s degree in Computer Science or a related quantitative field (Tier-1 institute background preferred).
- 5+ years of hands-on experience in Deep Learning, with a strong track record in fast-paced, technically complex projects.
- Experience working with Large Language Models such as GPT-style models, BERT, Transformers, etc.
- Strong hands-on experience with deep learning frameworks like Tensor Flow or PyTorch.
- Familiarity with cloud-native deployment technologies such as Docker and Kubernetes.
- Solid understanding of software engineering best practices, including:
- Coding standards
- Code reviews
- Source control (SCM)
- CI/CD pipelines
- Testing and production operations
- Strong communication skills with experience collaborating across engineering, product, and business teams.

Nice to Have

- Experience managing or mentoring high-caliber ML engineers or data scientists.
- Exposure to multi-modal machine learning and Generative AI use cases.
- Strong interest in the ethical and societal impact of AI technologies.
- A genuine passion for AI and applied machine learning.