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AI Architect

exl Service.com (India) Private Limited
Three Rivers, USA
Full-time
Mid · 4+ years experience
Hybrid
Discovered 3 days ago

Full Job Posting

Qualifications

  • Bachelor’s or master’s degree in Computer Science, Engineering, Data Science, Statistics, Mathematics, Artificial Intelligence, Machine Learning, or a related quantitative discipline.
  • 4+ years of hands-on experience in AI/ML, data science, or machine learning engineering, with experience building analytical or AI-enabled solutions that support measurable business outcomes.
  • Experience working with structured and unstructured data and applying machine learning, NLP, deep learning, or Generative AI techniques to solve practical business problems.
  • Experience supporting model deployment, productionization, monitoring, or MLOps activities will be strongly preferred.
  • Exposure to healthcare, insurance, disability claims, financial services, or other regulated industries will be preferred.
  • Strong analytical thinking, engineering discipline, and structured problem-solving ability.
  • Strong written and verbal communication skills, with the ability to explain analytical findings, model outputs, risks, and recommendations to both technical and business stakeholders.
  • Ability to work in a fast-paced, continuously evolving environment and take ownership of challenging AI/ML delivery tasks.
  • Ability to collaborate effectively across cultures and work with clients and teams across geographies.

Responsibilities

  • Strong hands-on proficiency in Python and common AI/ML libraries such as Scikit-learn, XGBoost, LightGBM, TensorFlow, PyTorch, Hugging Face, LangChain, or similar frameworks.
  • Solid understanding of machine learning and statistical modeling techniques, including classification, regression, clustering, survival analysis, anomaly detection, feature engineering, model selection, andhyperparameter tuning.
  • Hands-on experience with NLP, deep learning, and document analytics use cases such as text classification, entity extraction, semantic search, summarization, information extraction, and document understanding.
  • Practical exposure to Generative AI and Large Language Models, including prompt engineering, embeddings, Retrieval-Augmented Generation, vector databases, LLM evaluation, hallucination control, and responsible AI guardrails.
  • Working knowledge of MLOps and production ML practices, including experiment tracking, model registry, CI/CD for ML, model deployment, monitoring, drift detection, retraining, and tools such as MLflow, Airflow,
  • Docker, Kubernetes, Git, or cloud-native ML platforms.
  • Strong SQL and data manipulation skills, with the ability to work with large structured, semi-structured, and unstructured datasets.
  • Good understanding of relational databases, data modeling concepts, data pipelines, APIs, and data architecture fundamentals.
  • Exposure to cloud platforms such as Azure, AWS, or GCP and familiarity with scalable AI/ML solution development in cloud environments.
  • Ability to evaluate model performance using appropriate metrics, explain model outputs, identify bias or drift, and communicate limitations clearly to technical and non-technical stakeholders.
  • Understanding of responsible AI, model governance, data privacy, security, and compliance considerations in regulated domains.
  • Exposure to group insurance, healthcare, disability insurance, claims analytics, or other regulated business domains will be preferred.
  • Basic understanding of insurance data structures such as policies, insured members, coverages, claims, benefits, providers, medical records, and related entities will be an advantage.
  • Strong problem-solving skills, ownership mindset, and ability to design scalable, reusable, and maintainable AI/ML solution components.

Preferred Qualifications

  • Experience supporting model deployment, productionization, monitoring, or MLOps activities will be strongly preferred.
  • Exposure to healthcare, insurance, disability claims, financial services, or other regulated industries will be preferred.

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