Lead Software Engineer - ML Platform

Adobe; California; On-site; USD 80,000 - 150,000; Full time

Job summary

An innovative company is seeking a skilled software developer to lead the design and optimization of cloud-based AI/ML platforms. In this role, you will collaborate with data scientists and engineers to enhance customer experiences through cutting-edge technology. Your expertise in programming languages and cloud platforms will be crucial in developing scalable, secure, and efficient solutions. Join a team that values creativity and is committed to pushing the boundaries of digital experiences. If you're passionate about technology and eager to make an impact, this opportunity is perfect for you.

Qualifications

• 5+ years of software development experience in enterprise-scale SaaS applications.
• Strong knowledge of cloud platforms and relational/non-relational databases.

Responsibilities

• Design and maintain cloud-based platforms for AI/ML products.
• Lead engineers to deliver high-quality features and functionalities.

Skills

Python

Go

Java

Analytical Skills

Communication Skills

Problem-Solving

Education

BS in Computer Science

MS in Computer Science

Tools

Flask

Django

Gin

Spring

AWS

Azure

Postgres

MySQL

Cassandra

MongoDB

Job description

Our Company

Changing the world through digital experiences is what Adobe’s all about. We give everyone—from emerging artists to global brands—everything they need to design and deliver exceptional digital experiences! We’re passionate about empowering people to create beautiful and powerful images, videos, and apps, and transform how companies interact with customers across every screen.

We’re on a mission to hire the very best and are committed to creating exceptional employee experiences where everyone is respected and has access to equal opportunity. We realize that new ideas can come from everywhere in the organization, and we know the next big idea could be yours!

Help build innovative ML/GenAI platform to serve and scale Adobe's enterprise ML services. Work with data scientists, engineers, ML researchers, and product managers to optimize the customer experience.

The candidate will have a proven history of leading and developing top-notch enterprise services and solutions. Familiarity with MLOps and ML system development would be helpful.

What you’ll do

• Design, develop, optimize, and maintain cloud-based platform to serve various AI/ML products and services.
• Lead junior to mid-level engineers to collectively execute and deliver time-sensitive features and functionalities with high quality and robust observability.
• Work directly with ML engineers, engineering managers, product managers, and enterprise customers to gather technical requirements and understand the use-case difficulties to provide pragmatic architecture, objective timeline, delivery milestones, and tasks distribution.
• Drive innovation by staying ahead of the latest industry trends and technologies.

What you need to succeed

• BS or MS in Computer Science or related fields, or equivalent experience; 5+ years of software development experience.
• Proven ability and extensive experience in owning, crafting, and developing enterprise-scale platform focused SaaS applications.
• Expertise in one or more programming languages such as Python, Go, Java, etc. and related frameworks (e.g., Flask, Django, Gin, Spring, etc).
• Industry experience in designing, building, and maintaining highly available, secure, and scalable RESTful API and micro-services.
• Strong knowledge of public cloud platforms (e.g., AWS, Azure, etc.) and experience in developing applications on these.
• Sound understanding of relational (e.g., Postgres, MySQL) and/or non-relational (e.g., Cassandra, MongoDB) and their internals.
• Strong analytical and quantitative problem-solving ability in a constantly evolving domain.
• Excellent communication skills and a phenomenal teammate.

Preferred Qualifications

• Experience with MLOps and ML system development.
• Familiarity with RAG pipeline and Agentic applications.
• Understanding of GenAI fundamentals, including foundation models, fine-tuning, etc.
• Knowledge of modern ML operationalization frameworks, including Ray, MLFlow, etc.