AI Engineer – INTL India

Job Overview

• AI Solution Engineering:
  Design, build, and deploy AI/ML solutions leveraging LLMs, NLP, forecasting, personalization, and generative AI use cases.
• Translate business problems into technical designs, model architectures, and scalable services.

• Implement and train deep learning models (e.g., transformers, sequence models) using PyTorch/Tensor Flow.
• Run experiments, hyperparameter tuning, and evaluation; document results and recommendations.

• Work with ML Ops to operationalize models through CI/CD, model registries, and repeatable training pipelines.
• Develop APIs and batch scoring jobs; ensure performance, latency, and cost targets.

• Apply responsible AI practices: bias assessment, explainability where needed, and model risk documentation.
• Ensure compliance with data privacy, security, and internal standards.

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances.

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• 5–8+ years of hands-on experience in AI/ML engineering or applied machine learning.
• Expert Python and strong software engineering practices (testing, packaging, code review).
• Expertise with NLP/LLMs.
• Experience deploying models to production (batch and/or real-time) in cloud environments (Azure preferred).
• Strong understanding of model evaluation, monitoring concepts, and data/feature quality.

• Experience with Azure Machine Learning, Databricks, MLflow, and vector databases.
• Experience building retrieval-augmented generation (RAG) systems and prompt evaluation.
• Strong communication skills with ability to explain technical concepts to business stakeholders.