Software Development Engineer II (Machine Learning)

SDE II – Machine Learning Location: Bangalore Experience: 3–6 years About Media.net Media.net is a global leader in ad tech, powering billions of ad impressions across web and mobile formats. Our proprietary contextual advertising and machine learning technologies serve major global publishers and advertisers. We focus on building intelligent systems that solve complex optimization and targeting problems at scale. If you thrive in a fast-paced, data-driven environment and are excited to work on innovative solutions that drive business results, this role is for you. As a Software Development Engineer II (Machine Learning), you will be responsible for designing, developing, and deploying machine learning models that drive business outcomes. This includes developing and maintaining large-scale machine learning systems, collaborating with cross-functional teams to integrate machine learning models into our ad tech platform, and working with data scientists to develop and deploy new machine learning models. You will also be responsible for ensuring the quality and reliability of our machine learning models, and collaborating with other teams to identify and prioritize new features and improvements. Requirements: Bachelor's degree in Computer Science, Engineering, or related field; 3-6 years of experience in software development, preferably in machine learning or related field; Strong programming skills in languages such as Python, Java, or C++; Experience with machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn; Strong understanding of data structures, algorithms, and software design patterns; Experience with cloud-based technologies such as AWS or Google Cloud; Strong analytical and problem-solving skills; Excellent communication and collaboration skills; Ability to work in a fast-paced environment and prioritize tasks effectively. Benefits: Competitive salary and benefits package; Opportunity to work on cutting-edge machine learning technologies; Collaborative and dynamic work environment; Professional development opportunities; Flexible work arrangements; Access to cutting-edge tools and technologies; Recognition and rewards for outstanding performance.