Machine Learning Engineer

As an experienced professional with over 2 years of experience, you will be responsible for designing, developing, and deploying Machine Learning / Artificial Intelligent models to address real-world challenges within our software products. Your role will involve collaborating with product managers, developers, and data engineers to establish AI project objectives and specifications. Additionally, you will be tasked with cleaning, processing, and analyzing extensive datasets to uncover valuable patterns and insights. Your expertise will be utilized in implementing and refining models using frameworks like TensorFlow, PyTorch, or Scikit-learn. You will also play a crucial role in creating APIs and services to seamlessly integrate AI models into production environments. Monitoring model performance and conducting retraining as necessary to uphold accuracy and efficiency will be part of your regular duties. It is essential to keep yourself abreast of the latest developments in AI/ML and assess their relevance to our projects. To excel in this role, you should hold a Bachelor's or Master's degree in Computer Science, Data Science, AI/ML, or a related discipline. A strong grasp of machine learning algorithms, including supervised, unsupervised, and reinforcement learning, is imperative. Proficiency in Python and ML libraries such as NumPy, pandas, TensorFlow, Keras, and PyTorch is required. Familiarity with NLP, computer vision, or time-series analysis will be advantageous. Experience with model deployment tools and cloud platforms like AWS, GCP, or Azure is preferred. Knowledge of software engineering practices, encompassing version control (Git), testing, and CI/CD, is also essential. Candidates with prior experience in a product-based or tech-driven startup environment, exposure to deep learning, recommendation systems, or predictive analytics, and an understanding of ethical AI practices and model interpretability will be highly regarded. This is a full-time position requiring you to work during day shifts at our in-person work location.,