Staff Machine Learning Engineer (PhD)

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Job Overview

The position at Jerry.ai for a Staff Machine Learning Engineer (PhD) is a unique opportunity for professionals passionate about utilizing machine learning to enhance the car ownership experience. This role places you at the forefront of innovating automotive technology, contributing to a super app designed to simplify vehicle management for drivers across the United States.

Company Background

Jerry.ai is recognized as America’s first and only super app aimed at reassessing and streamlining car ownership. With a massive user base of 5 million customers and an outstanding 4.7-star rating on the App Store, the company's innovative solutions have garnered attention in several publications, including the Harvard Business Review and Forbes. Founded in 2017, Jerry.ai has so far raised over $240 million in funding, signifying strong investor confidence in its vision to revolutionize the automotive industry.

Role Responsibilities

As a Staff Machine Learning Engineer, you will report directly to the cofounder/CTO and will have the opportunity to:

• Develop and architect complex machine learning models to solve critical business challenges.

• Take ownership of the entire modeling process, from ideation through to deployment and maintenance of the models.

• Perform data preparation and analysis to ensure the quality of the input data used in modeling tasks.

• Collaborate with cross-functional teams, including Product and Data Engineering, to integrate these models into production systems.

• Tackle significant company projects that address challenges previously unexplored by Jerry.ai.

This is not just a job—it is an opportunity to make a substantial impact in a quickly growing sector of technology.

Required Skills

Candidates interested in this role should possess:

• A PhD in Physics or a related field.
• A minimum of 5 years’ experience building and deploying machine learning models from scratch, demonstrating deep expertise in machine learning algorithms and techniques.
• Strong analytical skills and a proven ability to translate complex business requirements into actionable solutions.
• A desire to focus on practical applications of machine learning, aiming to make a significant impact through large-scale business initiatives.

Compensation Structure

The salary range for this position is between $180,000 to $240,000, which will be determined based on job-related factors such as experience and skills. The total compensation package may include opportunities for equity grants, and Jerry.ai offers a comprehensive benefits package to full-time employees that includes:

• Health, dental, and vision coverage
• Paid time off and parental leave
• A 401(K) plan with employer matching
• Wellness benefits

It is important to note that specific benefits may not be available for part-time, contract, or freelance roles.

Workplace Environment

Jerry.ai emphasizes a culture that promotes quick decision-making, constant testing, and iteration, allowing employees to own their projects right from the conceptual stage through to execution. Team members are encouraged to collaborate and innovate across disciplines, enhancing not only individual careers but also the overall success of the company.

Equal Opportunities and Inclusivity

Jerry.ai is committed to maintaining a diverse workplace and is proud to be an Equal Employment Opportunity employer. The company abides by strict guidelines to prevent discrimination based on various characteristics, ensuring an inclusive and supportive work environment for all employees. Reasonable accommodations will also be provided for individuals with disabilities during the application process.

Conclusion

The role of Staff Machine Learning Engineer at Jerry.ai represents a profound opportunity for candidates equipped with the necessary qualifications and dedication to push the boundaries of technology in the automotive sector. Candidates seeking a position where they can make a measurable impact and work alongside skilled and passionate colleagues in a high-energy environment should consider applying.

This job offer was originally published on himalayas.app