AI / ML Engineer, Systematic Equities

Job Title: AI / ML Engineer, Systematic Equities Company: Alpha Alternatives Job Category: Machine Learning Roles & Responsibilities: Key Responsibilities: * Machine Learning Research and Development : Develop predictive models using forecasting, ranking and classification techniques. Evaluate suitable statistical, ensemble and deep\-learning methods for systematic investment applications. * Artificial Intelligence Applications : Build and evaluate AI research tools using natural language processing, large language models, embeddings, retrieval\-augmented generation and document intelligence. Extract relevant information from company filings, earnings transcripts, news and other datasets. * Feature Engineering and Model Evaluation : Develop and select features, design experiments and assess performance on unseen data. Address data leakage, overfitting, model stability and changing data behaviour. * Data and Research Infrastructure : Develop data collection and processing pipelines, reusable Python components, experiment tracking and reproducible research workflows. * Implementation and Monitoring : Support the transition of research into paper trading and production workflows, including model deployment, monitoring and maintenance. * Collaboration and Communication : Work closely with fund managers to translate investment questions into technical research. Communicate findings, model behaviour and limitations clearly through analysis and visualization. Work Location: Mumbai, Maharashtra, India Availability: Full time

Technical Skills : * Strong expertise in applied machine learning, statistics, feature engineering, model selection, hyperparameter tuning and rigorous model evaluation. * Proficiency in Python, Pandas, NumPy, scikit\-learn and SQL; relevant experience with PyTorch, TensorFlow, gradient\-boosting libraries or comparable frameworks. * Hands\-on experience building and evaluating AI applications using NLP, LLMs, embeddings, retrieval\-augmented generation or other modern AI techniques, with attention to accuracy, reliability, latency and cost. * Demonstrated depth in one or more areas such as time\-series forecasting, ranking, tabular ML, deep learning or NLP. Expertise in every technique is not required. * Experience with APIs, Git, reproducible workflows and the deployment or operational use of models. MLOps, cloud platforms, data engineering and agentic AI experience are additional advantages. Experience and Qualifications : * 0 years of experience in applied ML, AI engineering or data science, with substantial hands\-on ownership of complex projects and demonstrated outcomes. Candidates from outside financial services are encouraged to apply. * Bachelor's, master's or PhD in Computer Science, Statistics, Mathematics, Engineering, Data Science or a related quantitative discipline. Strong practical capability and project delivery will be given significant weight. * Strong analytical and problem\-solving skills, the ability to work independently, and clear communication with technical and non\-technical colleagues. * A clear interest in transitioning into quantitative investing as a long\-term career, with a willingness to learn investment concepts and work closely with experienced investment professionals. Key Skills: Machine Learning, Python, TensorFlow, PyTorch, Pandas, NumPy, Feature Engineering, NLP Salary: Not disclosed