- Process and refine clickstream data for constructing machine learning models.
- Establish metrics for evaluating ML models both online and offline.
- Collaborate with operations engineers to deploy ML models as microservices.
- Participate in A/B testing, derive insights, and refine the model accordingly.
- Develop data workflows and feature storage solutions for model deployment.
- Play an active role in team decision-making, participate in code reviews to spot errors, and assist in resolving software issues.
- Examine clickstream data to uncover potential improvements for the website.
- Provide insights on data schema / structure enhancements.
- Assist search platform engineers in comprehending the requirements of machine learning models.
- Creation of training data with crowdsourcing.
- Holds a master's degree in computer science or a similar discipline.
- Over three years of experience in machine learning and AI, particularly in search, recommendations, and marketing.
- Demonstrated ability in developing and launching scalable systems.
- Deep understanding of Artificial Intelligence (AI) and Data Science.
- Able to work with little supervision, frequently creating and deploying data science and machine learning models independently.
- Effective in influencing and collaborating across different functions and proficient in utilizing popular cloud platforms.
- Skilled in handling projects of moderate to high complexity and adept at balancing solution accuracy with efficiency.
- Advocates for excellence in software development practices, with a focus on maintainability, version control, and ease of deployment of models.
- Proficient in Python, Pandas, Pytorch/Tensorflow, Huggingface, NLTK etc.
- Basic knowledge on NLP – named entity recognition, classification, generation
- Basic knowledge on deep learning – layers, loss functions, training, etc.
- MS and 3+ years of experience or Ph.D and 0+ years' of experience
- Proven track of record in DL/ML/NLP research.
- Skilled in enhancing search engines to improve user experience.
- Comprehensive understanding of search auto-complete, semantic search, recommendation algorithms, learning-to-rank techniques, and personalization strategies.
- Extensive expertise in applying machine learning to marketing.
- Ability to fine-tune and implement large-scale language models.
- Experienced in designing architecture and frameworks for project deployment, in collaboration with engineering teams.
- Experienced in creating recommender systems for boosting cross-selling.
- Adept at overseeing all aspects of production deployment in AWS.
- Our people: If you thrive in an inclusive, innovative, and fast-paced organization, look no further You will get to work alongside some of the brightest minds - Join a genuinely fun and supportive workplace where we keep our employees consistently engaged through internal communication and corporate events
- Relaxation and Celebrations: Generous PTO, Sick Days, Paid National Holidays, and even more (ask us about this when we connect).
- Health Benefits: We contribute to your medical, dental, vision and short-term/long-term disability plans and have a strong employee assistance program.
- Plan for your Retirement: 401(k) eligible after your first 90 day's employed
- Giving Back: We sponsor multiple events throughout the year to help out our communities. You will receive time off to give back as well.
- Growth: We'll help you take your career to the next level. We want you to be creative and take initiative which will allow you to grow and create within the company. Most importantly, be the best at what matters
- Flexible Work Schedules: With business units and employees across the globe, Material Technologies has embraced a hybrid working model allowing department leaders to decide on the best approach for their respective teams, whether that be remote, in person, or a little of both.
Machine Learning Engineer - New York, United States - Material Bank
Description
Material Bank is a fast-paced, high-growth technology company and created the world's largest material marketplace for the Architecture and Design industry, providing the fastest and most powerful way to start and manage a design project. Learn more about us at or see below.
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Material Bank is looking for talented and driven Machine Learning Engineers to become an integral part of our dynamic team. In this position, you will take charge of developing and overseeing machine learning models, including the creation and transformation of relevant data pipelines, feature storage, and model deployment. Your work will span projects in the realms of e-commerce search, recommendations, marketing, and data analytics, directly contributing to enhancing Material Bank's online customer experience, with measurable impacts on revenue.
What you'll do:
What you'll bring:
Preferred Qualifications:
What you'll get from us:
About Material Bank
Material Bank is the world's largest material marketplace for the architecture and design industry, providing the fastest and most powerful way to search and sample materials. Material Bank connects design professionals to hundreds of manufacturers through facilitating brand discovery, rep engagement, and material sampling.
Material Bank has transformed the way an entire industry discovers and samples materials. By removing the friction that exists in the process, we drive business between architects and designers (members) and our Brand Partners (clients).
Our powerful material database and proprietary robotic distribution facility allow members to order samples until midnight (ET) to be delivered free of charge anywhere in the US, in one box, by 10:30 AM the next morning.
Connect with us and discover your career at Material Bank.
--Material Bank is proud to be an equal opportunity employer. We value diversity, and all applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, age, national origin, veteran or disability status or other status protected under any applicable federal, state or local law.