AI Scientist (Embedded Applications)

Posted 3 Days Ago
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Waterloo, IA
Mid level
Sports
The Role
The AI Scientist role at Trek involves leading AI projects focused on implementing multimodal generative AI methods on embedded hardware products. Responsibilities include collaborating with engineers to define performance targets, developing and optimizing AI models, deploying models, and providing R&D support for product development teams. The role emphasizes the use of large language models and machine learning techniques to derive consumer insights and improve products.
Summary Generated by Built In

A bit about us 

Trek is an awesome place to work, with amazing benefits for all employees. We build only products we love, provide incredible hospitality to our customers, and change the world by getting more people on bikes. When you’re on our team, you’re taken care of, encouraged to learn and grow, and given lots of opportunities to do so. Give us your best, and we’ll give it right back. Sound pretty sweet? Then come join us!
 

Job Description

Advanced Technologies at Trek is seeking a driven AI Scientist to spearhead AI projects. This role involves pioneering the implementation of cutting-edge multimodal generative AI methods on hardware products, guiding engineers and product development teams to uncover valuable product engineering insights. Additionally, they will work with various departments across the company to identify consumer behavior insights that drive the company’s growth.

Responsibilities

  • Collaborate with the Director of Advanced Technologies to translate business objectives into technical project requirements.
  • Partner with embedded hardware engineers to define performance targets, size, and computational demands for embedded AI models.
  • Partner with embedded systems engineer to develop and optimize AI models on hardware using embedded C/C++ . Create methods to handle and process data in real-time, ensuring low latency and high throughput for embedded AI applications.
  • Develop and deploy AI models to specified locations and create quantitative test methods to evaluate model performance.
  • Stay updated with the latest research and advancements in AI, and the ability to apply these innovations to practical applications by experimenting with the latest large language models, small language models, visual language models, and speech-to-speech models.
  • Provide tools and support to product development teams for R&D and product development, identifying the best machine learning and deep learning methods for their goals.
  • Empower product development teams with examples and demonstrations of methods they can integrate into their processes.
  • Lead data education initiatives among product development teammates.

Skillsets

  • Python, SQL
  • Popular foundation models such as GPT, Llama, Gemini
  • RAG
  • PyTorch, TensorFlow
  • Classical ML and Deep-learning (Computer vision, NLP) techniques
  • Spark-ml, Databricks
  • Vector database, graph database
  • Enterprise IT ecosystem such as Azure, AWS, Google Cloud

Competencies - Must-Have’s

Working experience with Large Language Models/Small Language Models

  • Demonstrated knowledge of end-to-end model fine-tuning pipeline including deployment onto the destination server or hardware. Have a strong comprehension of model performance optimization, pruning, and quantization
  • Experience deploying small scale model (less than 10B parameters) onto an edge device. Posses an excellent understanding of processing unit and memory requirements on edge devices
  • Demonstrated knowledge of constructing an AI-application that incorporates RAG. Ability to choose the proper model that enhances the end-user experience with accommodation of RAG.
  • Working knowledge of VLM and NLP-based applications is highly desirable. An understanding of the underlying NLP principles, and resource optimization for large-scale deployment

Advanced Statistical and Mathematical Knowledge for classical Machine learning and Deep learning projects

  • Graduate-level advanced mathematics & statistics of underlying principles machine learning algorithms, deep-learning methods and libraries of that enables one to choose best methods or model for specific projects.
  • Working knowledge of modeling using methods such as regression, scenario analysis, clustering, data mining, decision trees, neural networks
     

Data Management

  • Experience in basics of data engineering: data cleaning and pre-processing
  • SQL and NoSQL databases and query methods
  • Working knowledge of vector database and graph database
  • Knowledge of data warehousing, ETL tools, and data governance

Competencies – Nice-to-have’s

  • Azure Cloud Knowledge: hands-on experience with Azure Machine Learning and other fundamental building blocks of service deployments in Azure.
  • Basics of software engineering: Demonstrated knowledge of designing robust experiments, A/B testing and understanding causal inference
  • Big Data Technologies: experience with Spark, Databricks
  • Additional programming languages: C++, Java, node, Go, or Javascript
  • Experience in cross-functional projects: Experience constructing technical project requirements with domain experts, recurring technical and non-technical documentation and reporting and status updates.

Education/Training

  • Master’s or PhD from top institutions with strong data science and AI programs
  • 5-10 years of experience working in diverse fields and applications
  • Work experience at startup or fast-paced organization is highly valued.
  • Domain knowledge in outdoor/fitness consumer product development is a plus.

Attributes of a successful candidate

  • A resilient and resourceful problem solver with a strong focus on execution.
  • A dependable teammate who fosters a positive work environment through humility and compassion.
  • Demonstrates honesty, self-reflection, and a commitment to continuous learning and growth.
  • Skilled in formulating sound hypotheses and assessing risks for ambitious ideas.
  • Proficient in developing and nurturing talent.

Travel

  • 1-2 per year travels are expected for this position.

Work Authorization

  • Authorized to work in the USA.

Trek Benefits:

• Flexible and fun company culture
• Competitive health care
• PPO & HDHP medical plan options, Dental insurance, Vision insurance
• Flexible Spending Accounts (FSA)
• Free life insurance & optional term life insurance
• Competitive vacation package
• 401(k) with match and Employee Stock Ownership Plans (ESOP)
• 12 weeks of maternity leave with 100% pay
• Flexible holiday schedule – 10 company holidays
• Tuition Reimbursement up to $15,000! (Undergraduate & Masters programs)
• Employee discounts on all product
• Deep partner retail discounts





We are an Equal Employment Opportunity (“EEO”) Employer. Trek strictly prohibits discrimination on the basis of race, color, creed, religion, gender, gender identity, pregnancy, marital status, partnership status, sexual orientation, age, national origin, veteran or military status, disability, medical condition, genetic information, or any other characteristic prohibited by federal, state and/or local laws. This policy applies to all aspects of employment, including hiring, promotion, demotion, compensation, training, working conditions, transfer, job assignments, benefits, layoff, and termination.



We are an E-Verify employer.

For more information, please click on the following links:
E-Verify Participation Poster: English / Spanish
E-Verify Right to Work Poster: English | Spanish

Top Skills

Python
The Company
HQ: Waterloo, WI
3,388 Employees
On-site Workplace
Year Founded: 1976

What We Do

Trek is a place where you’re valued for being you. If you’re really into bikes, that’s great. If you’re not (yet), that’s great too. Because there’s a lot more to Trek than bikes. Every person has a unique history and life experience to bring to the table. We respect that. It’s what makes us who we are.

At Trek, there's only one standard you have to meet - love.

Learn more of why Trek is a Great Place to Work: trekbikes.com/careers

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