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 initiative supports the Data Science Team's strategic imperative of fostering a "Culture of reuse: tools, products, and processes."

Responsibilities

• Work within the Data Science Team to define common problems and identify opportunities in the existing codebase to solve current and future problems.
• Develop libraries and services to address common requirements for our machine learning products.
• Collaborate with data scientists to transition their machine learning models from prototype to production.
• Champion the use and adoption of Toolkit libraries and services.
• Execute tasks to achieve a project’s overarching technical vision, including supporting client intake conversations, conducting data exploration, feature development, and bug fixes.
• Recognize and appropriately escalate risks while supporting assigned mitigations within a finance and accounting firm.
• Support team members' growth through pair programming, code review, and knowledge sharing.
• Uphold Crowe’s values of Care, Trust, Courage, and Stewardship, 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. Experience with cloud computing, distributed systems, or CI/CD is beneficial.
• Capacity for autonomy: Ability to manage time effectively between research and tool development.
• Strong communication skills: Ability to adjust discussions about software engineering projects for technical and non-technical audiences.
• Adaptability: Ability to context-shift across different areas of computer science and machine learning, adjusting to new problems or requirements.
• Detail-oriented: Focus on developing tools that are robust, including identifying edge cases, writing maintainable code, clear documentation, and 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, or other relevant areas.
• Unique background in software engineering, computer science, or related fields that provides distinctive skills for approaching problems.

Pay

A reasonable estimate of the current range is $62,000 - $100,000 per year, taking into account skill sets, experience, training, licensure, certifications, and other business and organizational needs.

Benefits

Crowe offers a comprehensive total rewards package, including:

• An inclusive culture that values diversity and provides equitable access to career growth and leadership opportunities.
• Consistent career coaching and guidance to support professional goals and aspirations.
• Investment in innovative ideas, such as AI-enabled insights and technology-powered solutions.