Senior ML Engineer - R12162 at Oportun

Oportun is seeking a Senior Machine Learning Engineer to lead the development of its ML infrastructure. The ideal candidate will play a pivotal role in elevating the company's ML capabilities, responsible for conceiving and implementing a state-of-the-art machine learning infrastructure.

The Senior Machine Learning Engineer will actively contribute to architectural decisions, mentor junior ML engineers, and collaborate closely with diverse teams, including data scientists and engineers, to deliver high-quality ML solutions. This role offers the opportunity to lead the technology effort for large initiatives, from technical requirements gathering to the final successful delivery of the ML solution.

Responsibilities:

• Lead the implementation of a cutting-edge ML infrastructure.
• Provide technical leadership, mentoring, and guidance to machine learning engineers.
• Take ownership of critical projects and initiatives.
• Collaborate with data scientists to translate model requirements into optimized data pipelines.
• Spearhead the establishment of best practices for model versioning, experiment tracking, and model evaluation.
• Architect and execute model deployment strategies, harnessing containerization (Docker) and orchestration (Kubernetes).
• Engineer automated CI/CD pipelines that facilitate seamless model deployment, monitoring, and continuous optimization.
• Define and refine performance benchmarks and optimize models and infrastructure.
• Remain at the forefront of industry trends and emerging technologies.

Requirements:

• Requires 6+ years of related experience with a Bachelor's degree in Computer Science; or a Master's degree with an equivalent combination of education and experience.
• Extensive experience orchestrating the development of end-to-end machine learning infrastructure.
• Proven record of transformative leadership.
• Proven track record of delivering sophisticated ML solutions with high quality.
• Exceptional problem-solving and analytical skills.
• Solid understanding of data structures, algorithms, and software design principles.
• Profound mastery of machine learning frameworks such as TensorFlow, PyTorch, or equivalent, coupled with Python programming.
• Deep expertise in containerization (Docker) and orchestration (Kubernetes).
• Thorough comprehension of software engineering principles, version control (Git), and collaborative development workflows.
• Adeptness with cloud platforms (AWS or Azure).
• Track record of successfully integrating DevOps practices, continuous integration, and continuous deployment (CI/CD) pipelines.
• Excellent communication and interpersonal skills.