Applied AI & ML Engineer

Bose is about better sound, but better sound is just the beginning. We are about inventing new technologies that truly benefit people and creating a culture where innovation and teamwork are highly valued. Working at Bose, you are encouraged to question conventional thinking in the relentless quest to create products and experiences that change people's lives. Data science, ML, and analytics are crucial parts of this mission. These capabilities fuel the creation of new and innovative products, help us to bring the right products to the right customers, and allow us to astonish customers with carefully crafted and personalized experiences.  

The Data and AI organization is seeking an entry-level Applied AI & ML Engineer to join the team. In this role, you will work at the intersection of AI/ML, software engineering, and MLOps, contributing to the development of production-ready AI systems and applications. You will help move models and AI capabilities from experimentation to scalable deployment, while supporting the design and implementation of modern AI solutions, including NLP and Generative AI. 

This role is ideal for candidates who enjoy building, learning new technologies, and applying AI in real-world contexts, rather than purely research-focused work. 

Responsibilities include (but are not limited to):  

• Partner with stakeholders and cross-functional teams to translate business needs into AI/ML and GenAI products. 

• Work with structured and unstructured data (e.g., text, customer feedback) to support model development, evaluation, and insight generation 

• Contribute to building and deploying AI-powered solutions, including LLM-based applications (e.g., RAG, summarization) and predictive models 

• Design and implement data and ML pipelines that enable reliable, scalable processing and integration of AI capabilities into production systems 

• Support MLOps practices by helping to operationalize models and applications (e.g., deployment workflows, monitoring, versioning, and performance tracking) 

Required Qualifications: 

• Bachelor’s degree in a quantitative field such as Computer Science, Statistics, Applied Mathematics, Engineering, Information Science, or a related discipline 

• 0–2 years of experience (internships, co-ops, or projects) in AI, machine learning, data science, or software engineering 

• Proficiency in Python and SQL 

• Experience writing clean, maintainable, and well-documented code 

• Foundational understanding of machine learning concepts and workflows 

• Exposure to NLP and/or Generative AI, including familiarity with LLMs or transformer-based models 

• Basic understanding of software engineering practices (e.g., Git, version control) 

• Strong problem-solving skills and ability to learn new technologies quickly 

• Effective communication skills and ability to work in a collaborative environment 

Preferred Qualifications: 

• Hands-on experience through internships, academic projects, or competitions 

• Familiarity with LLM frameworks and tooling (e.g., OpenAI APIs, LangChain, Hugging Face) 

• Exposure to RAG architectures, semantic search, or text-based AI applications 

• Experience with cloud or data platforms (e.g., Databricks, Snowflake) 

• Basic understanding of MLOps concepts (e.g., MLflow, model deployment, monitoring) 

• Experience building simple applications (e.g., Streamlit or similar frameworks) 

• Familiarity with API development and integration