AI/ML Engineer - Data Modeling

Key Responsibilities Model Development & Optimization :

- Independently design and train robust, reusable AI/ML models using frameworks like

Kubeflow, PyTorch, TensorFlow, or HuggingFace.

- Apply advanced techniques in deep learning, NLP, computer vision, and classical ML, ensuring

models are explainable and scalable.

- Optimize models for accuracy, speed, and resource efficiency, and collaborate with Data Engineers on deployment readiness.

AI/ML System Design :

- Translate business use cases into scalable AI model architectures, including design of pre-

processing strategies and feature engineering approaches.

- Ensure alignment between data characteristics, model architecture, and expected system

behavior in production.

- Collaborate on integration patterns with Data Engineers to embed AI models in downstream workflows.

Documentation & Standards :

- Write clear documentation on model assumptions, architecture choices, evaluation criteria, and recommended usage.

- Contribute to the standardization of model development guidelines within the AI team to ensure reproducibility and traceability.

Stakeholder Collaboration & Delivery :

- Support scoping and delivery of AI features and enhancements within broader data product initiatives.

- Partner with domain experts, business stakeholders, and functional analysts to iterate on model design and results interpretation.

- Adapt solutions based on feedback and performance monitoring, ensuring business value is realized.

Innovation & Capability Building :

- Stay up to date on emerging AI/ML methods, tools, and frameworks, and explore how these can improve our modeling practices.

- Share findings and contribute to team learning sessions, playbooks, or prototyping initiatives.

Security & Compliance in AI :

- Design models with appropriate data privacy, access control, and bias mitigation considerations.

- Ensure models meet compliance, governance, and interpretability standards relevant to the business context.

Mentoring & Community :

- Mentor junior AI engineers on modeling approaches, model evaluation, and development best practices.

- Contribute to a knowledge-sharing culture across the AI, data science, and engineering teams.

Required Qualifications :

- Bachelors or Masters degree in Computer Science, Artificial Intelligence, Data Science, or a related field.

- 3 - 5 years of experience designing and implementing AI/ML models in production.

- Strong Python development skills, with deep familiarity with ML/DL libraries (e.g., Kubeflow, PyTorch, TensorFlow, scikit-learn).

- Demonstrated success with real-world AI use cases, including agents, vision, or forecasting.

- Understanding of model lifecycle, versioning, monitoring, and deployment-readiness (in

coordination with MLOps/ML Engineers).

- Strong ability to collaborate in cross-functional teams and communicate modeling choices to technical and non-technical audiences.

Preferred Skills :

- Experience with transformers, embedding techniques, image recognition, or reinforcement

learning.

- Understanding of data governance and AI ethics principles.

- Ability to collaborate effectively across distributed teams (Europe, US, and India).

- Familiarity with the Cloud, Google Cloud is preferred.

- Understanding of database technologies (OLTP vs OLAP vs graphs vs blob storage vs .) and

experience working with some of them.

What We Offer :

- Opportunities to contribute to high-impact AI initiatives in a growing global data organization.

Whats In It For You :

- A family atmosphere , people-centric culture, where your emotional and physical well-being matters.

- A competitive salary , medical insurance for family , retirement benefits.

- Healthy work life balance.

- Internal career opportunities, professional development, including access to LinkedIn Learning and many in-house/external training courses.

- Job security working for a global company with strong presence & commitment in India.

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