5+ years developing production-ready software systems
Prior experience in financial services is a plus
Expertise in end-to-end machine learning operations
Proficient with Python and machine learning libraries (e.g., NumPy, Pandas, Scikit-Learn, PyTorch)
Experience with SQL databases
Familiarity with containerization and cloud infrastructure technologies.
Responsibilities
Develop high-impact machine learning products
Translate complex project requirements into technical solutions
Collaborate with data scientists and engineers to build and deploy software
Monitor and maintain machine learning solutions in production
Drive adoption of best practices in software development
Ensure rigor in modeling and solution delivery
Integrate solutions with production data pipelines and APIs.
Benefits
Collaborative work environment on cutting edge projects
Opportunity to work alongside experienced data scientists and engineers
Focus on operational growth and technological innovation
Commitment to core values like excellence and integrity
Chance to directly impact investment decision-making processes.
Full Job Description
About the Team:
On the Valor Labs Team, we develop cutting edge machine learning models to derive proprietary investment insights and build software applications to augment the Firm's investment decision making process. As a small team of software engineers and data scientists with diverse backgrounds, we work collaboratively on wide-ranging problems to deliver high-impact products for the Firm.
About the Role:
As a Software Engineer on our data science and machine learning team, you will contribute directly to the development of high-impact products. Working together with data scientists, engineers, and stakeholders, you will translate complex project requirements into actionable technical solutions and work collaboratively to build, deploy, monitor, and maintain those solutions in production. Your technical expertise and commitment to excellence will help drive the adoption of best practices and ensure the highest level of rigor in everything we do.
About You:
B.S. in Computer Science or related field
5+ years of experience developing production-ready software systems
Although not necessary, prior work experience in financial services is highly valued
Expertise in end-to-end machine learning operations: model deployment, monitoring, and retraining, supporting integration with production data pipelines and API services.
Proficient with Python, especially machine learning libraries like NumPy, Pandas, Scikit-Learn, and PyTorch
Proficient with SQL, including transactional (e.g., PostgreSQL) and analytical (e.g., BigQuery) databases
Professional experience with most, if not all, of the following:
Containerization (e.g., Kubernetes and Docker)
Data processing (e.g., Prefect, Airflow, and dbt)
Parallel processing (e.g., Ray, Dask, and Spark)
Cloud infrastructure (e.g., Google Cloud Platform)
