Machine Learning Platform Engineer

$160,000 - $170,000/Yr

ML Enterprise Corporation - New York, NY

Full-time - Mid Level

New York, NY

Clothing, Clothing Accessories, Shoe, and Jewelry Retailers

About the position

The Machine Learning Platform Engineer at MoneyLion will be responsible for managing the development, deployment, and optimization of a high-revenue data product. This role involves collaborating with data scientists and engineers to enhance the ML Ops infrastructure, ensuring that the platform supports efficient workflows and rapid experimentation. The position is ideal for individuals interested in both software engineering and machine learning solutions, contributing to innovative data products and infrastructure components.

Responsibilities

• Take ownership of a high-revenue data product, managing its development, deployment, and optimization.
• Lead the development and management of additional data products, ensuring scalability and alignment with business goals.
• Collaborate with data scientists and engineers to ensure the products meet business needs and support efficient workflows.
• Contribute to major changes in the ML Ops platform, working closely with the Tech Lead.
• Help build and maintain infrastructure components, including data pipelines, version control, and CI/CD systems.
• Work closely with data scientists to understand their needs and improve platform support for rapid experimentation and deployment.

Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field.
• 4-6 years of experience in building, deploying, and maintaining data-driven products or machine learning models.
• Strong understanding of software engineering principles and object-oriented programming.
• Proficiency in Python, with experience in key data science libraries such as Pandas, NumPy, scikit-learn, etc.
• Familiarity with infrastructure tools (e.g., Docker, Kubernetes, Datadog, AWS, Github Actions, etc.) is preferred.
• Strong problem-solving skills and ability to collaborate effectively with data scientists, engineers, and other stakeholders.

Nice-to-haves

• Experience with cloud platforms such as AWS or Azure.
• Knowledge of machine learning frameworks like TensorFlow or PyTorch.

Benefits

• Competitive salary packages and bonuses
• Comprehensive medical, dental, vision and life insurance benefits
• Equity based compensation
• Wellness perks
• Paid parental leave
• Unlimited Paid Time Off
• Learning and Development resources
• Flexible working hours