Senior Machine Learning Engineer

As a Machine Learning Engineer at Appnext, you will play a crucial role in building end-to-end machine learning pipelines that operate at a massive scale. Your responsibilities will include handling data investigation, ingestions, model training, deployment, monitoring, and continuous optimization to ensure measurable impact through experimentation and high-throughput inference. This job combines 70% machine learning engineering and 30% algorithm engineering and data science. Responsibilities: - Build ML pipelines that train on real big data and perform on a massive scale. - Handle a massive responsibility by advertising on lucrative placements like Samsung appstore, Xiaomi phones, TrueCaller. - Train models that make billions of daily predictions and impact hundreds of millions of users. - Optimize and discover the best solution algorithm for data problems, including implementing exotic losses and efficient grid search. - Validate and test everything using AB testing for each step. - Utilize observability tools to own your experiments and pipelines. - Be frugal and optimize the business solution at minimal cost. - Advocate for AI and be the voice of data science and machine learning to address business needs. - Build future products involving agentic AI and data science to impact millions of users and handle massive scale. Requirements: - MSc in CS/EE/STEM with at least 5 years of proven experience (or BSc with equivalent experience) as a Machine Learning Engineer, with a focus on MLOps, data analytics, software engineering, and applied data science. - Excellent communication skills with the ability to work with minimal supervision and maximal transparency, providing efficient and honest progress updates. - Strong problem-solving skills and the ability to drive projects from concept to production, owning features end-to-end. - Deep understanding of machine learning, important ML models, and methodologies. - Proficiency in Python and at least one other programming language (C#, C++, Java, Go) with flawless SQL skills. - Strong background in probability and statistics, experience with ML models, conducting A/B tests, and using cloud providers and services (AWS). - Experience with Python frameworks like TensorFlow/PyTorch, Numpy, Pandas, SKLearn (Airflow, MLflow, Transformers, ONNX, Kafka are a plus). - Ability to independently hold all AI/LLMs skills and effectively use AI transparently. Preferred: - Deep knowledge in ML aspects including ML Theory, Optimization, Deep learning tinkering, RL, Uncertainty quantification, NLP, classical machine learning, and performance measurement. - Prompt engineering and Agentic workflows experience. - Web development skills. - Publications in leading machine learning conferences and/or medium blogs.,