Ai/Ml Engineer

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
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