Machine Learning Engineer – Work From Home

We are seeking a talented and self-motivated Machine Learning Engineer to join the growing data science efforts. You will work in a collaborative team with the potential to deliver significant contributions through data-driven insights and by providing high-quality research tools enabling reproducible and well-tested research to take place across the firm. Company culture emphasizes teamwork and focuses on continuous integration and test-driven development. Company will relocate candidates! This is a 100% Remote opportunity.

The ideal candidate will be responsible for designing, developing, and enhancing the Python data science tools and frameworks. This includes working collaboratively with multiple trading teams, conducting alpha research, identifying new trading opportunities, and managing the full Machine Learning Operations (MLOps) stack from data collection to training, deploying, and monitoring models in production.

Responsibilities:

– Develop predictive models and use data-driven insights to maximize strategy performance and identify new trading opportunities.
– Design and implement robust and scalable CI/CD data pipelines.
– Translate machine learning algorithms into code.
– Support current strategies and help develop new strategies utilizing our proprietary software.
– Stay up to date on best practices in software engineering for machine learning applications and keep informed on cutting-edge machine learning techniques.

Qualifications

– Bachelors in mathematics, physics, computer science, or a related quantitative field with at least 4 years of relevant work experience.
– Masters/PhD in mathematics, physics, computer science, or a related quantitative field with at least 2 years of relevant work experience.
– Strong GPA (3.5 or higher).
– Strong knowledge of probability, statistics, and machine learning for time-series data.
– Excellent programming skills in Python (C++ familiarity is a plus).
– Experience with software engineering best practices including TDD and CI/CD.
– Experience with distributed computing.
– Prior experience developing on a Linux stack.
– Effective prioritization while being mindful of long-term objectives.
– Able to take ownership of projects in a fast-paced collaborative environment.
– Strong attention to detail.
– Outstanding communication skills to collaborate with different stakeholders across multiple geographical locations.

Preferred Experience:

– Practical experience applying machine learning techniques for trading applications.
– Machine Learning Operations (MLOps) experience designing well-tested, versioned, and reproducible machine learning pipelines.
– Experience with High-Performance Computing (HPC) environments such as SLURM.
– Familiarity with cloud computing infrastructure (e.g., AWS, GCP).
– Experience with orchestration and containerization tools (e.g., Singularity, Docker, Airflow, Prefect, etc.).

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