Software Engineer, Machine Learning

Key Responsibilities

• Collaborate with cross-functional teams (product, design, operations, infrastructure) to build innovative application experiences.
• Implement custom user interfaces using latest programming techniques and technologies.
• Analyze and optimize code for quality, efficiency, and performance, and provide feedback to peers during code reviews.
• Set direction and goals for teams, lead major initiatives, provide technical guidance and mentorship to peers, and help onboard new team members.
• Architect efficient and scalable systems that drive complex applications.
• Identify and resolve performance and scalability issues, and drive large efforts to reduce technical debt.
• Work on a variety of coding languages and technologies.
• Establish ownership of components, features, or systems with expert end-to-end understanding.

Requirements & Tech Stack

• Demonstrated experience driving change within an organization and leading complex technical projects.
• Experience utilizing data and analysis to explain technical problems and provide detailed feedback and solutions.
• Work on a variety of coding languages and technologies.

Qualifications

• Masters degree or PhD in Computer Science or a related technical field (Preferred)
• Experience with frameworks like TensorFlow, PyTorch, or Scikit-learn (Preferred)
• Understanding of information retrieval concepts, such as indexing, querying, and ranking (Preferred)
• Demonstrated grasp of data structures and algorithms, including graph theory and optimization techniques (Preferred)
• Knowledge of NLP techniques, including text preprocessing, tokenization, and sentiment analysis (Preferred)
• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements) (Preferred)
• Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews) (Preferred)
• Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies (Preferred)