Machine Learning Engineer

<h2>About the Role</h2><p>DataMind AI is building the next generation of AI-powered analytics tools. We are looking for a Machine Learning Engineer who can bridge the gap between research and production, taking ML models from prototype to scalable deployment.</p><p>You will work on challenging problems in natural language processing, recommendation systems, and predictive analytics. Our team publishes research at top conferences and you will have opportunities to contribute to cutting-edge research while building production systems.</p><h2>What You Will Do</h2><ul><li>Design and implement ML pipelines for training, evaluation, and deployment</li><li>Optimize model performance for latency and throughput in production</li><li>Collaborate with research scientists to productionize new models</li><li>Build feature engineering pipelines and data processing systems</li><li>Monitor model performance and implement retraining strategies</li></ul>

<ul><li>MS or PhD in Computer Science, Machine Learning, or related field</li><li>3+ years of experience deploying ML models in production</li><li>Strong proficiency in Python, PyTorch, and scikit-learn</li><li>Experience with MLOps tools (MLflow, Kubeflow, or similar)</li><li>Knowledge of NLP and transformer architectures</li><li>Experience with distributed computing frameworks (Spark, Ray)</li></ul>