Staff Applied Scientist - Remote USA (*eligible states)

About The RoleThe Staff Applied Scientist will set the technical direction of their team to build and deploy machine learning solutions. They will work closely with Product and Engineering partners in the development of the solution.
*States Not Eligible: AK, AR, DE, KS, MS, ND, SD, WY

What You Get To Do Everyday

• Lead the design, development and deployment of Machine Learning models to solve business problems.

• Develop and maintain clean, efficient, and scalable code that meets industry standards.

• Analyze large datasets to extract actionable insights and make informed decisions.

• Employ state-of-the-art Machine Learning methodologies and frameworks to develop robust and scalable models.

• Influence technical direction and take ownership of key components of systems and solutions, ensuring that they meet the needs of the business.

• Collaborate with key stakeholders in the development of data-driven solutions and deployable products. 

• Mentor and guide team members to help establish team domain expertise.

• Contribute to the company’s intellectual property and technical leadership through patents and publications at top-tier conferences and journals.

What You Bring To The Role

Minimum Requirements:

• 7+ years of industry experience in applied Machine Learning

• Graduate Degree in CS/ML or a related field

• 5+ years experience in building, deploying, and managing machine learning and deep learning models in production environments at scale

• Deep understanding of ML best practices (A/B testing, training/serving pipelines, feature engineering etc), algorithms/techniques (gradient boosting, deep neural networks, optimization, regularization), and experiment design

• Experience in at least two of these domains: price estimation, personalization, recommender systems, natural language processing, computer vision, fraud detection and authentication marketing

• Extensive experience in scientific libraries in Python (numpy, pandas) and Machine Learning tools and frameworks (Scikit-Learn, Tensorflow, Keras, PyTorch)

• Strong data engineering skills and experience working with large scale datasets

• Experience with big data tools (Apache Beam, Apache Kafka, Spark)

• Experience with cloud technologies AWS, GCP or Azure

• Fluency in Python, SQL

Preferred Requirements:

• Masters Degree or PhD preferred (CS, ML, AI or related field)

• Background in applying ML techniques to solve real-world business problems in the retail sector.

• Familiarity with MLOps tools and pipelines.

• Impact-focused and passionate about delivering high-quality models.

• Demonstrated leadership experience, with the ability to lead and inspire a team.

Compensation, Benefits, + Perks

• Employee Stock Purchase Plan

• 401K with Company Match

• Medical, Dental & Vision Insurance

• Paid Parental Leave

• 9 Paid Company Holidays

• Flexible Time Off (With Manager Approval)

• Find out more about our Benefits here.

The expected salary range for this role is $200,000.00-$225,000.00. To determine starting pay we carefully consider a variety of factors, including primary work location and an evaluation of a candidate’s skills, experience, market demands, and internal parity. Additionally, salary is just one component of TRR’s total rewards package. Depending on role, employees may also be eligible for a bonus program, incentive pay and benefits.

The RealReal is the world’s largest online marketplace for authenticated, resale luxury goods, with 37 million members. With a rigorous authentication process overseen by experts, The RealReal provides a safe and reliable platform for consumers to buy and sell their luxury items. We have hundreds of in-house gemologists, horologists, and brand authenticators who inspect thousands of items each day. As a sustainable company, we give new life to pieces by thousands of brands across numerous categories—including women's and men's fashion, fine jewelry and watches, art, and home—in support of the circular economy. We make selling effortless with free virtual appointments, in-home pickup, drop-off, and direct shipping. We handle all of the work for consignors, including authenticating, using AI and machine learning to determine optimal pricing, photographing and listing their items, as well as shipping and customer service.