Summary
Join causaLens as a Machine Learning Engineer specializing in Causal AI and make a significant impact in advancing our Causal AI platform. Collaborate with a talented team, leverage cutting-edge technologies, and be part of the forefront of research and development in Causal AI. This role offers the opportunity to grow professionally, regardless of your seniority level, and contribute to groundbreaking solutions that push the boundaries of machine learning and causality. We are looking for a motivated and high-achieving individual.
This is a full-time placement based in London.
What You Will Do
- Collaborate closely with software engineers and scientists to enhance and expand our Causal AI platform.
- You will contribute to feature engineering and the development of machine learning models with a focus on causality.
- Utilizing Python, Cython, Numpy, Torch, and other relevant technologies, you will build robust causal algorithms for time series and/or tabular data.
- Collaborate with cross-functional teams to ensure seamless integration of the Causal AI platform within our infrastructure.
- You will participate in code reviews, provide feedback, and help maintain code quality.
Stay updated with the latest advancements in Causal AI, actively sharing knowledge and driving innovation within the team. Contribute to documentation efforts, including research findings, methodologies, and technical specifications. Embrace a continuous learning mindset, seeking opportunities to expand your data science and software engineering skills.
Requirements
- Bachelor's or master's degree in Computer Science, Engineering, Mathematics, or a related field with a solid understanding of statistical concepts and machine learning principles. Familiarity with causal inference or Ph.D. is a plus.
- Experience in developing and implementing machine learning algorithms and models and familiarity with machine learning libraries and frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
- Proficiency in Python, with the ability to translate advanced machine learning algorithms into code.
- An in-depth understanding of computer architecture, including knowledge of languages such as C, C++, or Cython, is preferable.
- Familiarity with software development best practices, version control systems, and agile methodologies is desired.
- Highly capable, self-motivated, collaborative, and personable, with a drive for integrity and excellence.
- Natural curiosity, creativity, and effective problem-solving skills, with a passion for tackling cutting-edge challenges.
- Excellent written and verbal communication skills, with a high level of business acumen.
- Ability to work independently and thrive in a fast-moving environment.
- Based in London or willing to relocate.