Deep Learning Engineer, Recommender System

Rosetta.ai helps fashion e-commerce uncover consumer's shopping preferences and provide personalized shopping experiences to consumers. We're making e-commerce merchants have enterprise-level AI backup on day 1.

We are seeking Deep Learning Engineers, dedicated to Recommender System, to join our data science team. The ideal person will have industry experience working on a range of classification and optimization problems, e.g.click-through rate prediction, recommendation systems, or search ranking. The position will involve taking these skills and applying them to some of the most exciting and massive shopping data and prediction problems that exist on the web. You will bring the ability to own the whole ML life cycle, define projects, and drive excellence across teams.

Responsibilities:

• Develop and implement deep learning algorithms to build personalized fashion product recommendation systems.
• Work closely with data engineers, data annotators, and product managers to define and extract relevant data features from our fashion e-commerce platform.
• Design and implement scalable data pipelines for training and evaluating deep learning models.
• Experiment with different deep learning architectures to optimize the recommendation system performance.
• Analyze and interpret model results to identify areas for improvement and optimize model performance.
• Collaborate with software engineers to integrate recommendation models into our SaaS platform.
• Stay up to date with the latest developments in deep learning and recommendation systems research and apply the latest techniques to improve our recommendation system.

Benefits:

• Healthcare Subsidy (Medical, Dental, Vision)
• Retirement savings or 401(K)
• Extended Paid Annual time off (The first year: 10 days, by proportion)
• Paid Maternity/Paternity leave
• Life insurance

Perks:

• Tuition reimbursement and training
• Personal facilities (Laptop, Screen)
• Free health screening
• Free snacks and drinks
• Open and creative environment
• Irregular dinner/outing, happy hours
• Paid time off to volunteer every month (Birthday, Menstrual, Funeral)
• Paid sick leave: 2 days every month
• Flexible schedules and working time
• Remote working optionally
• Employee stock ownership plan (ESOP)

Culture/6 Core Values:

Grit - We thrive outside of our comfort zone, pushing ourselves to go even further. We think long-term and constantly strive to be better, even if things don’t always go as expected.

Trust - We earn that trust by listening to each other, following through with our commitments, and keeping our words. We exercise transparency within the company, our customers, and our community.

Humility - We learn from everyone and everywhere, and we approach each new challenge knowing that we may not have all the answers.

Empathy - We craft our intention to keep curious about the industry, business, and practical scenarios that we purify the insights and forge the approaches.

Candor - We are open and honest. We give each other praise and criticism because we believe each team member is as important as the other.

Craftsmanship - We simplify, innovate, perfect, and start over until everything we touch enhances each life it touches.

Contact:

• Email to [email protected]
• Or, send us on CakeResume

Remarks:

Rosetta.ai is an Equal Employment Opportunity employer. Rosetta.ai conducts all employment-related activities without regard to race, religion, color, national origin, age, sex, marital status, sexual orientation, disability, citizenship status, genetics, or any other characteristic protected by law.

[Minimum Qualifications]

Background & Skills:

• Master or Ph.D. degree in Computer Science, Statistics, or related fields.
• Strong knowledge of deep learning frameworks such as PyTorch or TensorFlow.
• Experience in building and deploying recommendation systems using deep learning techniques.
• Proficiency in Python and SQL.
• Familiarity with big data technologies such as Hadoop, Spark, or Hive.
• Excellent problem-solving skills and ability to work independently in a fast-paced environment.
• Strong communication skills and ability to collaborate with cross-functional teams.

Working Style:

• Excellent communication and collaborative skills.
• Strong problem-solving and conceptual thinking skills.
• Flexibility and comfort working in a dynamic, team environment with a possible remote organization with minimal documentation and process.

[Preferred Qualifications] (Optionally; the more, the better)

Background & Skills:

• MS degree in Computer Science or related quantitative field with 2-3+ years of deep learning-related work or research.
• Knowledge in natural language processing or computer vision.

Experiences:

• Experience with cloud services, such as AWS, S3, EC2, Beanstalk, and Redis.
• Experience with filesystems, server architectures, and distributed systems.
• Experience with Elasticsearch.

Reputations:

• Publications in top conferences, including but not limited to ACL, EMNLP, CVPR, ECCV, RecSys, WWW, ICML, IJCAI, and AAAI.

1. CV screening
2. Culture fit interview
3. Assignment project
4. Professional interview
5. Trial days