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AI/ML Engineer

Summary

Design, build, and deploy scalable AI/ML models using TensorFlow/PyTorch, lead cross-functional teams, and optimize performance for production systems.

  • Lead the design, development, and deployment of AI and ML models and systems, focusing on scalability, reliability, and performance.
  • Collaborate with cross‑functional teams, including data scientists, software engineers, and product managers, to deliver end‑to‑end AI/ML solutions.
  • Design, implement, and maintain advanced machine learning algorithms (supervised, unsupervised, reinforcement learning, etc.) to solve complex problems across various domains.
  • Utilize deep learning frameworks (such as TensorFlow, PyTorch, Keras, etc.) and apply them to real‑world applications.
  • Work with large‑scale datasets, preprocess and clean data, and ensure efficient data pipelines to support machine learning models.
  • Continuously evaluate and optimize the performance of deployed models using A/B testing, cross‑validation, and other methods.
  • Contribute to the development of AI/ML best practices, standards, and methodologies.
  • Provide technical leadership and mentorship to junior team members.
  • Stay current with the latest advancements in AI/ML technologies and research to incorporate into solutions and drive innovation.
  • Communicate technical findings, strategies, and progress to stakeholders, including non‑technical teams.

Required Qualifications

  • 10+ years of professional experience in AI/ML software development, with at least 5 years in a leadership or senior technical role.
  • Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field (Master’s or PhD preferred).
  • Proven experience with machine learning algorithms and frameworks (e.g., TensorFlow, Keras, PyTorch, Scikit-learn).
  • Expertise in deep learning techniques and frameworks (CNNs, RNNs, Transformers, etc.).
  • Strong programming skills in Python (preferred), Java, C++, or similar languages.
  • Extensive experience in developing, training, and fine‑tuning large‑scale machine‑learning models.
  • Proficiency in cloud computing platforms such as AWS, GCP, or Azure, especially related to AI/ML services.
  • Hands‑on experience with big data technologies (e.g., Hadoop, Spark, SQL, NoSQL).
  • In‑depth knowledge of data preprocessing, feature engineering, and model evaluation techniques.
  • Ability to work in a collaborative and agile environment, contributing to all stages of the development lifecycle.

Preferred Qualifications

  • Familiarity with natural language processing (NLP), computer vision, and reinforcement learning.
  • Experience with AI/ML deployment frameworks such as TensorFlow Serving, TorchServe, or Kubeflow.
  • Familiarity with DevOps practices and CI/CD pipelines.
  • Previous experience with AI/ML‑driven products in production at scale.
  • Strong understanding of statistics, mathematics, and optimization techniques.

Excellent communication and problem‑solving skills

See also

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