BMO U.S.
Senior Artificial Intelligence / Machine Learning Engineer
BMO U.S., New York, New York, us, 10261
Senior Artificial Intelligence / Machine Learning Engineer
Role: Senior ML/AI Engineer on the ARC team. Hybrid role (2 days/week in office). We are seeking a highly analytical and technically proficient Senior ML/AI Engineer to join our ARC team. This role is ideal for someone with a strong foundation in mathematics, statistics, and programming, and a passion for applying AI to solve complex financial problems. You will work to develop AI/ML/DS features for enterprise-wide AI products to develop models, optimize strategies, and contribute to the evolution of our AI-powered financial systems. Responsibilities
Design and develop Machine Learning models (Supervised, Unsupervised, and Reinforcement Learning), AI (Generative models and Agent Orchestration) models, and Deep Learning models (e.g., Neural Networks and autoencoders). Run Machine Learning tests and experiments. Train and retrain systems to prevent drift and optimize results. Solve complex problems with multi-layered data sets, extend existing ML frameworks (Scikit-Learn, XGBoost, TensorFlow) and AI frameworks (Keras, LangChain). Leverage and develop advanced analytics models (network-based, forecasting, rules-based), implement said algorithms, and build tools to apply them. Turn structured, semi-structured and unstructured data into useful information. Develop ML/AI algorithms to analyze large volumes of historical data to derive insights, make decisions, and form predictions. Run tests, perform statistical analysis, and interpret test results. Establish the main functions of the digital foundations: Hypergraph Scenario Engine and network-based methods mapping relationships between entities and simulating cascading scenarios. Exposure to Quant Machine Learning tailored to quantitative finance, driving forecasting, risk modeling, pricing, and portfolio optimization; chatbot capabilities where applicable. Provide guidance (scoring, decisioning) in areas such as multi-objective optimization, safe RL and decision support, network propagation algorithms, entity resolution, and clustering. What you need to succeed
Master’s or Ph.D. in Mathematics, Statistics, Computer Science, Data Science, Physics, AI, Machine Learning or related field. Leadership experience driving AI/GenAI/ML initiatives/assets. Experience in model development (ML/Data Science, AI/GenAI) within financial services or technology sectors. Proficiency in Python and SQL, TensorFlow, PyTorch, XGBoost, Scikit-learn. Strong grasp of Artificial Intelligence and Machine Learning frameworks and stacks. Familiarity with cloud platforms (AWS, Azure, GCP) and CI/CD pipelines is advantageous. Intellectual curiosity and adaptability to emerging AI and quant finance trends. Strong communication skills to explain complex models to non-technical stakeholders. Ability to work independently and collaboratively in a fast-paced, multidisciplinary environment. Attention to detail and a rigorous approach to model validation and testing. Salary and benefits
Salary: $122,400.00 - $228,000.00. Pay Type: Salaried. The above represents BMO Financial Group’s pay range and type. Salaries vary based on location, skills, experience, education, and qualifications. Total compensation may include performance-based incentives, discretionary bonuses, and other perks. Benefits include health insurance, tuition reimbursement, accident and life insurance, and retirement plans. For more details, visit: https://jobs.bmo.com/global/en/Total-Rewards About Us
BMO is an equal employment opportunity employer. We evaluate applicants without regard to race, religion, color, national origin, sex, sexual orientation, gender identity, gender expression, age, veteran status, disability, or any other legally protected characteristics. BMO also provides reasonable accommodations in the employment process upon request. Note to Recruiters: BMO does not accept unsolicited resumes from any source other than directly from a candidate. A recruiting agency must have a valid, written contract to submit resumes.
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Role: Senior ML/AI Engineer on the ARC team. Hybrid role (2 days/week in office). We are seeking a highly analytical and technically proficient Senior ML/AI Engineer to join our ARC team. This role is ideal for someone with a strong foundation in mathematics, statistics, and programming, and a passion for applying AI to solve complex financial problems. You will work to develop AI/ML/DS features for enterprise-wide AI products to develop models, optimize strategies, and contribute to the evolution of our AI-powered financial systems. Responsibilities
Design and develop Machine Learning models (Supervised, Unsupervised, and Reinforcement Learning), AI (Generative models and Agent Orchestration) models, and Deep Learning models (e.g., Neural Networks and autoencoders). Run Machine Learning tests and experiments. Train and retrain systems to prevent drift and optimize results. Solve complex problems with multi-layered data sets, extend existing ML frameworks (Scikit-Learn, XGBoost, TensorFlow) and AI frameworks (Keras, LangChain). Leverage and develop advanced analytics models (network-based, forecasting, rules-based), implement said algorithms, and build tools to apply them. Turn structured, semi-structured and unstructured data into useful information. Develop ML/AI algorithms to analyze large volumes of historical data to derive insights, make decisions, and form predictions. Run tests, perform statistical analysis, and interpret test results. Establish the main functions of the digital foundations: Hypergraph Scenario Engine and network-based methods mapping relationships between entities and simulating cascading scenarios. Exposure to Quant Machine Learning tailored to quantitative finance, driving forecasting, risk modeling, pricing, and portfolio optimization; chatbot capabilities where applicable. Provide guidance (scoring, decisioning) in areas such as multi-objective optimization, safe RL and decision support, network propagation algorithms, entity resolution, and clustering. What you need to succeed
Master’s or Ph.D. in Mathematics, Statistics, Computer Science, Data Science, Physics, AI, Machine Learning or related field. Leadership experience driving AI/GenAI/ML initiatives/assets. Experience in model development (ML/Data Science, AI/GenAI) within financial services or technology sectors. Proficiency in Python and SQL, TensorFlow, PyTorch, XGBoost, Scikit-learn. Strong grasp of Artificial Intelligence and Machine Learning frameworks and stacks. Familiarity with cloud platforms (AWS, Azure, GCP) and CI/CD pipelines is advantageous. Intellectual curiosity and adaptability to emerging AI and quant finance trends. Strong communication skills to explain complex models to non-technical stakeholders. Ability to work independently and collaboratively in a fast-paced, multidisciplinary environment. Attention to detail and a rigorous approach to model validation and testing. Salary and benefits
Salary: $122,400.00 - $228,000.00. Pay Type: Salaried. The above represents BMO Financial Group’s pay range and type. Salaries vary based on location, skills, experience, education, and qualifications. Total compensation may include performance-based incentives, discretionary bonuses, and other perks. Benefits include health insurance, tuition reimbursement, accident and life insurance, and retirement plans. For more details, visit: https://jobs.bmo.com/global/en/Total-Rewards About Us
BMO is an equal employment opportunity employer. We evaluate applicants without regard to race, religion, color, national origin, sex, sexual orientation, gender identity, gender expression, age, veteran status, disability, or any other legally protected characteristics. BMO also provides reasonable accommodations in the employment process upon request. Note to Recruiters: BMO does not accept unsolicited resumes from any source other than directly from a candidate. A recruiting agency must have a valid, written contract to submit resumes.
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