Machine Learning Specialist
Role details
Job location
Tech stack
Job description
carefully crafted end-to-end and unit test cases for models and related sub-components. Prepare structured and unstructured data to use as features for maximum model performance. Deploy and monitor models in a cloud environment, prioritizing scalability, low latency, and A/B testing methodologies. Stay at the forefront of AI advancements, continuously researching and applying the latest in deep learning and machine learning techniques. What You Bring Proven expertise in Python programming, with deep knowledge of data structures and algorithms. Excellent command over statistical reasoning. In-depth understanding of predictive modeling techniques, time series analysis, anomaly detection, and clustering Proficiency with data visualization, statistical modeling and data analysis frameworks such as scikit-learn, SciPy and matplotlib. Hands-on experience with Pytorch and deep learning model architectures, such as Transformers, VAE, state space and diffusion models. Experience in fine tuning
Requirements
models using LoRA or similar methods. Experience in model testing, optimization and feature engineering, with the ability to source and integrate diverse data sets to improve performance.. Cloud deployment expertise, including Kubernetes, Docker and/or cloud ML platforms such as Amazon SageMaker. Exceptional attention to code quality and emphasis on adhering to established software design patterns. 4+ years of hands-on experience developing and deploying production-grade ML models in one or more of the above areas. Experience in the financial services industry, specifically investment management, is a huge plus. MSc in Mathematics, Statistics, Data Science, Physics or a related quantitative field. 5 years of professional experience in workplace setting. Whilst we spend a lot of our time working remotely, we believe there's no substitute (yet) for in-person collaboration, so we strongly encourage you to be in our London office on a weekly basis to spend time with your colleagues. CAIS is consistently recognized as a Best Place to Work, and our culture is at the heart of our success. We are committed to fostering an inclusive environment where employees can be their most authentic selves and feel inspired and supported to bring their voice forward to drive community, growth, and innovation. We are an equal opportunity employer, and do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. Learn more about our culture, benefits, and people at https://www.caisgroup.com/our-company/careers.