Senior Machine Learning Engineer - Machine Learning Infrastructure
FlipFull Time
Senior (5 to 8 years)
Candidates should possess experience with building infrastructure for training and fine-tuning large machine learning models, demonstrate intellectual curiosity and a strong interest in solving difficult problems, and exhibit exceptional programming skills with proficiency in identifying performance bottlenecks. Prior experience with the Python scientific stack and DL libraries such as PyTorch and TensorFlow is desired, along with familiarity with hardware accelerators.
The Research Engineer will partner with the research team to understand future research directions and build the next generation of highly scalable infrastructure for alpha, signal, and portfolio construction, incorporate advancements in machine learning, hardware accelerators, and high-performance computing to optimize research workflows, maintain, develop, and re-imagine the extensive internal research stack, and optimize models for inference and use in real-time trading systems.
Quantitative asset management and algorithmic trading
PDT Partners focuses on quantitative asset management by developing models that identify inefficiencies in financial markets and predict market movements. The firm uses sophisticated trading algorithms that analyze large amounts of market data to find patterns and execute trades accurately. Unlike many competitors, PDT Partners has a long history in algorithmic trading, having been a pioneer in the field since the 1990s. The company serves institutional clients, such as hedge funds and pension funds, helping them optimize their investment strategies through data-driven insights. PDT Partners aims to foster a collaborative environment where its team can continuously explore and innovate, ensuring that all ideas are carefully validated before implementation.