Senior ML Engineer / MLOps Engineer

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    "ExternalQualificationsStr": "<p><span>Strong experience in <strong>ML Engineering / MLOps</strong> with demonstrated delivery of end-to-end ML solutions in production environments. Proficiency in <strong>Python and advanced SQL</strong>, along with hands-on experience in ML frameworks such as <strong>Scikit-learn, TensorFlow, and PyTorch</strong>. Solid understanding of <strong>machine learning algorithms, evaluation techniques, performance metrics, and validation strategies</strong>. Hands-on expertise in <strong>cloud platforms (AWS or GCP)</strong>, containerization (Docker), orchestration (Kubernetes), and CI/CD tools (Jenkins, GitHub Actions). Familiarity with <strong>MLflow, Feast, Prometheus, Grafana</strong>, and modern model monitoring practices including <strong>data and model drift detection</strong>.</span></p>\n<p><span>Strong problem-solving, communication, and stakeholder management skills with the ability to work independently in fast-paced environments. Bachelor’s degree in computer science, Engineering, or a related field preferred.</span></p>\n<p><span><strong>Nice-to-have:</strong> Experience with <strong>real-time ML serving frameworks (KFServing, Seldon, Ray Serve)</strong>, A/B testing, and experimentation platforms. Exposure to <strong>media, subscription, or recommender systems</strong>, along with knowledge of <strong>experiment design and causal inference</strong>, will be an added advantage.</span></p>",
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