Lead ML Engineer — Production ML, Cloud & Mentorship (Remote)

Wiraa; United States; Hybrid; USD 132,000 - 238,000; Full time

Benefits offered by this job

Competitive salary

Health benefits

401(k) with company match

Employee discount

Paid time off

Flexible work arrangements

Career development

Job summary

Target in the Data Sciences team is seeking a Lead Machine Learning Engineer to design, implement, and optimize production ML solutions for merchandising. You will collaborate with data scientists, software engineers, and product managers to build scalable, high-performance ML systems in a cloud environment.

This leadership role includes mentoring, setting engineering standards, and communicating complex concepts to stakeholders.

Qualifications

• Bachelor's degree in a quantitative field or equivalent experience.
• Master's degree in CS, Applied Mathematics, Statistics, Physics, or equivalent ML experience.
• 5+ years of end-to-end ML development with data pipelines, model optimization, deployment, and API design.
• Extensive experience with distributed ML systems at scale.
• Highly proficient in Python programming.
• Strong understanding of CI/CD practices for ML systems and ML Ops principles.
• Hands-on experience with Google Cloud Vertex AI and cloud-based ML ecosystems.
• Knowledge of testing frameworks and containerization technologies such as Docker and Kubernetes.
• Experience leading development of agentic AI solutions integrating data, tools, APIs, and business rules.
• Demonstrated expertise in REST API design and development.
• Extensive understanding of Big Data technologies including Hadoop, Spark, and Kafka.
• Proven ability to collaborate cross-functionally with data scientists, engineers, and product managers.
• Excellent communication skills with the ability to present data-driven insights through visualizations and storytelling.
• Ability to mentor and guide engineering teams on standards, architecture patterns, and best practices for AI/ML and cloud-native development.
• Self-driven, results-oriented, and able to meet tight deadlines.
• Motivated team player who thrives in a collaborative, global environment.

Responsibilities

• Design, develop, and optimize machine learning models and pipelines supporting merchandising applications.
• Implement scalable, maintainable, and well-tested production ML codebases with relevant documentation.
• Lead code reviews and enforce software engineering best practices within the team.
• Collaborate with cross-functional teams including data scientists, software engineers, and product managers to deliver end-to-end ML solutions.
• Leverage cloud-based ML platforms such as Google Cloud Vertex AI for model training, deployment, and monitoring.
• Develop and maintain RESTful APIs to support ML-driven services.
• Apply CI/CD and ML Ops principles to automate deployment and monitoring of ML models.
• Mentor and provide technical leadership to engineering teams, establishing standards and best practices.
• Conduct training sessions and present technical work to both technical and non-technical audiences.
• Stay current with emerging trends in machine learning, AI, and big data technologies to continuously improve solutions.
• Contribute to strategic planning by aligning technical solutions with business priorities and goals.

Skills

Python

Machine Learning

CI/CD for ML

ML Ops

Distributed systems

Communication

Mentoring

Education

Bachelor's in quantitative field

Master's in CS/Math/Stats or equivalent

Tools

Google Cloud Vertex AI

Docker

Kubernetes

Hadoop

Spark

Kafka

REST APIs

Job description

Target in the Data Sciences team is seeking a Lead Machine Learning Engineer to design, implement, and optimize production ML solutions for merchandising. You will collaborate with data scientists, software engineers, and product managers to build scalable, high-performance ML systems in a cloud environment.

This leadership role includes mentoring, setting engineering standards, and communicating complex concepts to stakeholders.