Work Mode: Hybrid
Location: Hybrid - 3 days/week onsite in either Palo Alto, CA or New York City, NY

OPPORTUNITY

Kohler Ventures is an independent company wholly owned by Kohler Co., global leader in the manufacture of kitchen and bath products, tile and home interiors, and an international host to award-winning hospitality and world-class golf destinations. Our mission is to build new digital businesses that empower consumers to lead healthier lives. We explore how familiar experiences can be enhanced and innovations developed through the integration of leading-edge technology, science, and design.
Come join us as we build a best-in-class global multi-disciplinary team across artificial intelligence, machine learning, design, advanced software and hardware engineering, strategy, venture investments, sales, marketing, and partnerships. Our locations are Palo Alto, CA US, New York City, NY US, Kohler, WI US, Seoul, Korea, and Tel Aviv, Israel. We are seeking a Machine Learning Engineer who is passionate about applying machine learning to consumer products. The candidate should also have a desire to execute and guide model development through all phases of the product development life cycle. The ideal candidate will have a successful track record as a machine learning engineer, taking models from design to proof-of-concept and launch.

REQUIRED QUALIFICATIONS:

• 5+ years of experience working on commercial deep learning projects and have an appreciation for, and a vision to implement, a well-organized deep learning infrastructure.
• 3+ years hands on experience in building and maintaining data science applications and AWS Sagemaker ML pipelines
• Experience with AWS CDK
• Experience with CI/CD pipelines set up and configuration
• Strong skills in one or more languages: Typescript (Preferred), JavaScript, Python
• A solid understanding of Machine Learning workflows including ingesting, analyzing, transforming data, and evaluating results to make meaningful predictions
• Experience with Kubernetes (EKS, ECS), ArgoCD, AWS native systems such as Lambda functions, Step Function, Load Balancers etc.
• Bachelor’s degree (B.S.) and/or postgraduate degree or higher involving machine learning, computer science, statistics, or another STEM field
• Experience with large data sets, distributed computing, and cloud computing platforms.
• Grasp of classical statistics, such as fitting regression models, inference testing & sampling.
• Understanding of data structures, data modelling and software engineering best practices.
• Experience in electronics, connected or smart home devices experience preferred
• Demonstrating deep understanding of and ability to teach concepts, tools, features, functions, and benefits of different approaches to apply them.
• Availability to work outside of standard business hours as needed to be able to collaborate with teams across multiple time zones
• Ability to travel 10% of time both domestically and internationally

PREFERRED QUALIFICATIONS:

• Experience with safety and compliance standards related to health/wellness technology
• Experience with ML frameworks such as Pytorch, tensorflow
  

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ABOUT US

It is Kohler’s policy to recruit, hire, and promote qualified applicants without regard to race, creed, religion, age, sex, sexual orientation, gender identity or expression, marital status, national origin, disability or status as a protected veteran. If, as an individual with a disability, you need reasonable accommodation during the recruitment process, please contact kohlerjobs@kohler.com. Kohler Co. is an equal opportunity/affirmative action employer

• Build and maintain ML pipelines to perform complex statistical analyses and architect/train ML models on large data sets of unique data
• Design, build, automate, deploy and maintain machine learning production pipelines.
• Implement machine learning model lifecycle management framework.
• Build model performance tracking tools, to monitor month over month model performance, identify drivers and provide recommendations for model performance improvement
• Support the development of start-to-finish data product solutions from requirements gathering and ideation, through interface design and implementation.
• Participate in product discussions and roadmap exercises to understand business use cases
• Author technical documentation and reports to communicate process and results
• Communicate applied machine learning and statistic strategy to project sponsors, business leaders, and development teams across Kohler Ventures
• Support development of the overall product strategy via understanding of the competitive landscape, available and upcoming third-party integrations, and industry practices
• Collaborate with Engineering teammates to deploy models into production
• Collaborate with regulatory team to develop intended use and regulatory strategy
• Collaborate with advance research team to design and implement data science applications.