Machine Learning Software Engineer 1

About the Role

We work on medium-term machine learning projects (1-6 months) with a high degree of autonomy. The primary strategy of the Toolkit Team is to develop generalizable tools for common problems and facilitate the sharing of code within and between projects. This includes:

• Working within the Data Science Team to define common problems and identify opportunities in the existing codebase to solve current and future problems
• Developing libraries and services to address common requirements for our machine learning products
• Collaborating with data scientists to get their machine learning models from prototype to production
• Championing the use and adoption of Toolkit libraries and services

Responsibilities

• Executing tasks to achieve a project’s overarching technical vision, with responsibilities varying across the development lifecycle—from supporting client intake conversations and conducting data exploration for new projects to ongoing feature development and bugfixes for mature machine learning products
• Effectively executing tasks for assigned project(s) with some direction and support, ensuring code quality reflects the team's standards
• Recognizing and appropriately escalating risks within a finance and accounting firm, and supporting assigned mitigations
• Supporting team members' growth through pair programming, code review, and knowledge sharing
• Upholding Crowe’s values of Care, Trust, Courage, and Stewardship, and acting ethically and with integrity at all times

Requirements

• Programming experience: Proficiency in coding, primarily in Python; familiarity with another lower-level language (C/C++, Go, etc.) is a plus
• Software engineering experience: Comfort with algorithm design, data structures, Linux-based systems, and Docker for developing and delivering RESTful APIs. Additional experience in cloud computing, distributed systems, or CI/CD is beneficial
• Capacity for autonomy: Ability to manage time between research and tool development with minimal supervision
• Strong communication skills: Ability to adjust discussions about software engineering projects for technical and non-technical audiences, including teammates, collaborators, and business stakeholders
• Adaptability: Ability to context-shift across different areas of computer science and machine learning, and adjust to new problems or requirements
• Detail-oriented: Focus on developing tools that "just work," including identifying edge cases, writing maintainable code with clear documentation, and creating comprehensive test cases

Skills to Stand Out

• Enthusiasm for coding and learning new technologies
• Excitement about exploring or improving libraries to solve problems
• Commitment to lifelong engineering and continuous learning
• Curiosity about machine learning, including learning algorithms, data preprocessing strategies, or other relevant areas
• Unique background in software engineering, computer science, or related fields (educational, research, or hobbyist) that provides distinctive skills for approaching problems

Pay

A reasonable estimate of the current range is $62,000 - $100,000 per year. The wage range takes into account factors such as skill sets, experience, training, licensure, certifications, and business needs.

Benefits

Crowe offers a comprehensive total rewards package as part of an exceptional people experience. Benefits include:

• Career growth opportunities in an inclusive culture that values diversity
• Consistent support from a Career Coach to guide professional goals and aspirations