Director, ML Ops Engineering - Remote

at  Harbor Freight Tools USA Inc

The Director – ML Ops is responsible for the overall design, development, and support of our machine learning operations Harbor Freight. This includes the architecture and implementation of tools for model training, model monitoring, feature stores, model deployments, and model maintenance.
This role requires working with multiple levels of the organization, data science teams, application teams, security, software engineering, and business partners. It requires an experienced hands-on manager with excellent business acumen, very strong technical skills, and data modeling / data warehousing expertise.
This position is managerial, technical, and analytical in nature. The expectation is that the candidate can lead long term infrastructure projects, create strategic roadmaps, and successfully lead, grow, and hire a team of ML Engineers.

Duties and Responsibilities

• Work closely with data scientists and IT in the design, development, and implementation of our Enterprise AI platform.
• Design, build, and maintain an industry leading MLOps tech stack.
• Mentor data scientists within the business, ensuring we’re building best-in-class models.
• Design, build, and maintain a secure and scalable CI/CD framework for data science teams.
• Implement roadmaps and design plans to facilitate teams moving from on-prem to cloud.
• Project management experience – schedule management, resource management, issue management, etc.
• Establish and maintain regular written and in-person communications with leadership, department heads, and end users regarding pertinent department activities.

Scope (Required)

• Staff supervision and development — yes or no
• Decision making-
• Creates policy and resolves problems
• Provide data for decision support
• Provide consultation or expert advice
• Participate in planning business objectives
• Travel – less than 10%
• Location— Remote
• Flex Designation – Remote Anywhere

REQUIREMENTS

Education preferred

• Bachelor’s Degree in Computer Science, Engineering or a related Field

Skills (Required)

• The ideal candidate will have strong organizational skills and the ability to manage a diverse workload in a fast-paced environment
• Strong knowledge of distributed computing, data structures, data mapping, data warehouse, data mining, business analytics, software development, replication, and distributed/relational databases.
• Strong technical expertise in scripting (Python) database languages (SQL), and PySpark for model development.
• Experience in performing a variety of complicated tasks while leading and mentoring a team and working in a team-oriented, collaborative environment.
• Excellent time management and planning skills, organized with the ability to multi-task, exceptional follow-up skills and able to meet deadlines.
• Excellent written, oral, and interpersonal communication skills, with ability to communicate effectively.
• Experience in tracking projects and goals to successful completion (with visible metrics).
• Ability to stay abreast of significant technological developments that may impact the business.
• Equipped to effectively prioritize, collaborate, and excel in a fast-paced, high-pressure environment.
• Highly self-motivated, self-directed, and attentive to detail, with an emphasis on accuracy, detail, and timeliness.
• Understanding and experience with project management methodologies.
• Ability to manage multiple projects concurrently

Experience (Required)

• 7+ years experience as ML engineer or lead data scientist in a Big Data ecosystem, with a desire to assume greater responsibilities as a leader and mentor, while still being hands-on.
• 5+ years experience developing and operationalizing enterprise ML models at scale.
• 5+ years experience with public cloud platforms & systems (AWS, GCP, Azure).

• Work closely with data scientists and IT in the design, development, and implementation of our Enterprise AI platform.
• Design, build, and maintain an industry leading MLOps tech stack.
• Mentor data scientists within the business, ensuring we’re building best-in-class models.
• Design, build, and maintain a secure and scalable CI/CD framework for data science teams.
• Implement roadmaps and design plans to facilitate teams moving from on-prem to cloud.
• Project management experience – schedule management, resource management, issue management, etc.
• Establish and maintain regular written and in-person communications with leadership, department heads, and end users regarding pertinent department activities