Job Description

The ML Engineer is responsible for the overall development, deployment, 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 machine learning engineer with excellent business acumen, very strong technical skills, and data modeling / data warehousing expertise. This position is technical and analytical in nature. Duties and Responsibilities

• Work closely with data scientists and IT in the development and implementation of our Enterprise AI platform.
• Build and maintain an industry leading MLOps tech stack.
• Mentor data scientists within the business, ensuring we're building best-in-class models.
• Optimize the scalability, performance, and reliability of our models by implementing best practices and leveraging industry-standard technologies.
• Streamline data ingestion, pre-processing, feature engineering, and model training workflows to improve efficiency and reduce latency.
• Design, build, and maintain a secure and scalable CI/CD framework for data science teams.

Scope

• Staff supervision and development: No
• Decision making: Recommends policy and resolves problems
• Travel: Up to 5%
• Flex Designation: Anywhere

The anticipated salary range for this position is $110,800 - $166,100 depending on location, knowledge, skills, education and experience. This position is also eligible for an annual discretionary bonus. In addition, we offer comprehensive and competitive benefits to Associates (and their families) such as medical, dental, vision, life insurance, short-term and long-term disability. Eligible Associates are able to enroll in our company's 401k plan. Associates will accrue paid time off up to 236 hours per year (inclusive of PTO, floating holidays, and paid holidays). Paid sick time up to 80 hours per year unless otherwise required by law.

Requirements

Education and Experience Education Requirements

• Bachelor's in Computer Science, Mathematics, Statistics, Engineering, or a related field.
• Master's degree or Ph.D. is a plus.

Years of Experience

• 2-4 years experience as ML engineer or data scientist in a Big Data ecosystem, with a desire to assume greater responsibilities as a leader and mentor, while still being hands-on.
• 2-4 years experience developing, tuning, operationalizing, and monitoring enterprise ML models at scale.
• 2-4 years experience with public cloud platforms & systems (AWS, GCP, Azure).

Skills

• 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.
• 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 to 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.

Physical Requirements General office environment requiring ability to:

• Stand, walk, sit for extended periods of time.
• Speak and listen to others in person and over the phone and video conferencing.
• Use keyboard and read from computer screen and reports.
• The ability to lift up to 15 lbs.

Safety

• Must be able to perform this job safely in accordance with standard operating procedures and good manufacturing practices, without endangering the health or safety of self or others.