At Bose Corporation, we believe sound is the most powerful force on earth — and for over 60 years, we have been a company built on innovation, excellence, and independence. Privately owned, fiercely customer-focused, and driven by our values, we continue to lead industries and transform lives through sound. Today, Bose Corporation is entering an exciting new era. Across multiple global Business Units and Global Functions, we are shaping the future of audio technology, automotive, luxury, and premium experiences. We invite you to join us in this transformation. Job DescriptionCandidates must be available to work full-time (40 hours per week) from July 13 through December 18, 2026. No relocation assistance is available. THE ROLE The goal of the Audio Machine Learning Research team is to develop novel AI-powered audio processing algorithms. The twist is that our algorithms must run in real-time, on physical devices, for applications such as voice pickup, hearing augmentation and ones we haven't even thought of yet. As part of the team, you will work with experts in machine learning (ML), digital signal processing (DSP), software engineering and psychoacoustics to prototype and implement new algorithms.  Bose has a strong history of combining creative thinking with cutting-edge technology in the audio domain. We are looking for candidates passionate about machine learning and audio to help us shape the next chapter in the future of Bose! Responsibilities: - Most of your time will be devoted to prototyping, implementing and evaluating ML algorithms, curating and developing internal resources, and presenting your findings.  - You will integrate your novel solutions into existing systems and platforms to showcase new (proof of concept) solutions. - You will be able to contribute to projects, which will be shipped to Bose customers, apply for patents, and/or submit papers to top-tier AI and signal processing conferences (e.g., NeurIPS, ICASSP, Interpeech, etc.). Education: - Pursuing or recently finished a graduate-level degree in ML, Computer Science, Music Technology or a related field.  Skills: - Practical knowledge of Applied audio ML (TensorFlow/PyTorch, TFLite/ONNX is a plus) and Audio DSP (Python, Matlab and/or C/C++).  - Hands-on experience in at least one of the following research topics: Audio source separation, Speech enhancement, Microphone array signal processing, Tiny ML, Generative audio modelling - Familiarity with methods for spatial sound synthesis and/or room acoustics simulation/analysis is a plus. - Strong communication skills. You will be presenting your work to a large interdisciplinary community. At Bose, you're inspired to be and do your best and are rewarded for your unique talents! Our compensation is thoughtfully tailored to your skills, experience, education, and location, and goes beyond base salary. The hiring range for this position in the primary work location of Framingham, Massachusetts is: $40.00-$51.25 per hour.The hiring range for other Bose work locations may vary. In addition to competitive base pay we offer rewards including bonus programs, comprehensive health and welfare benefits, a 401(k) plan, plus exclusive perks designed to support your wellbeing, and a generous employee discount where you can immerse yourself in our products and experiences. We are a proudly independent company—driven by purpose, guided by our values, and united by a belief in the power of sound. As the world leader in audio experiences, we’re creating what’s next—pushing boundaries and delivering transformative sound experiences for people everywhere. Join us and make your next career move a mic-drop. Let’s Make Waves.‎ Bose is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, genetic information, national origin, age, disability, veteran status, or any other legally protected characteristics. The EEOC’s “Know Your Rights: Workplace discrimination is illegal” Poster is available here: https://www.eeoc.gov/sites/default/files/2023-06/22-088_EEOC_KnowYourRights6.12ScreenRdr.pdf. Bose is committed to providing reasonable accommodations to individuals with disabilities. If you require reasonable accommodation in completing this application, interviewing, completing any pre-employment testing, or otherwise participating in the employee selection process, please direct your inquiries to applicant_disability_accommodationrequest@bose.com. Please include "Application Accommodation Request" in the subject of the email.‎ Our goal is to create an atmosphere where every candidate feels supported and empowered in the interviewing process. Diversity and inclusion are integral to our success, and we believe that providing reasonable accommodation is not only a legal obligation but also a fundamental aspect of our commitment to being an employer of choice. We recognize that individuals may have different needs and requirements based on their abilities, and we provide reasonable accommodations to ensure ideal conditions are met during the application process.

Overview Machine Learning Engineer, AI Platform As a Machine Learning Engineer, you will design, build, and ship AI agents and automation that solve real problems across HealthEdge's engineering, product, and delivery organizations, including customer-facing operations. You'll partner directly with stakeholders across Engineering, Product, and healthcare professionals to understand their workflows, identify high-leverage opportunities, and deliver working solutions end-to-end. Your growing expertise in machine learning and agentic AI will have a direct impact on how HealthEdge builds software, delivers for customers, and operates at scale. Key Responsibilities - AI Platform Development: Develop and implement AI Agents and automation that accelerates internal engineering workflows and customer facing delivery processes, owning the full lifecycle from problem discovery, through prototyping, evaluation, hardening, and production deployment. Contribute reusable libraries, prompt templates, tool-use patterns, and evaluation scaffolding back to the AI Platform. - Integration: Partner with software engineers to integrate AI into the company's existing software infrastructure, supporting seamless functionality and performance. - Collaboration: Work directly with product managers, implementation consultants, engineers, and business operations teams to identify pain points, scope solutions, and iterate toward measurable outcomes. You are the bridge between what AI can do and what the business needs done. - Research and Learning: Stay current with advancements in LLMs, agentic frameworks, machine learning, and healthcare technology, and apply new knowledge to contribute ideas for innovation within the team. - Performance and Reliability: Optimize AI systems for accuracy, latency, cost, and safety, with particular attention to human-in-the-loop design and guardrails appropriate for healthcare. - Documentation: Maintain clear documentation of model development processes, methodologies, and results to ensure transparency and reproducibility. Required Qualifications - Education: Master's degree in Computer Science, Machine Learning, Data Science, or a related field. A Bachelor's degree with relevant experience will also be considered. - Experience: 2–4 years of experience building and deploying ML or AI systems in production. Experience working directly with non-technical stakeholders or in embedded/consulting-style engineering roles is a strong plus. - Technical Skills: Strong proficiency in Python. Experience with LLM APIs, agentic frameworks (LangChain, Strands, etc.), and prompt engineering alongside traditional ML frameworks (PyTorch, scikit-learn, etc.). Solid software engineering fundamentals — version control, testing, CI/CD, and comfort operating across the full development lifecycle. - Healthcare Knowledge: Interest in or familiarity with healthcare data, clinical workflows, and regulatory requirements. Experience working with electronic health records (EHR) or other healthcare datasets is a plus but not required. - Analytical Skills: Strong problem-solving skills and the ability to work with complex datasets to derive actionable insights. - Communication: Excellent verbal and written communication skills, with the ability to explain technical concepts to non-technical stakeholders. - Builder Mindset: Energized by turning ideas into working solutions. You balance speed with quality, thrive in ambiguous problem spaces, and pick up new domains quickly. - Team Player: Ability to work collaboratively in a cross-functional team environment, accept feedback, and contribute to the success of the team. HealthEdge commits to building an environment and culture that supports the diverse representation of our teams. We aspire to have an inclusive workplace. We aspire to be a place where all employees have the opportunity to belong, make an impact and deliver excellent software and services to our customers. Geographic Responsibility: While HealthEdge is located in Boston, MA you may live anywhere in the US Type of Employment: Full-time, permanent Work Environment: The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job: - The employee is occasionally required to move around the office. Specific vision abilities required by this job include close vision, color vision, peripheral vision, depth perception, and ability to adjust focus. - Work across multiple time zones in a hybrid or remote work environment. - Long periods of time sitting and/or standing in front of a computer using video technology. - May require travel dependent on company needs. The above statements are intended to describe the general nature and level of the job being performed by the individual(s) assigned to this position. They are not intended to be an exhaustive list of all duties, responsibilities, and skills required. HealthEdge reserves the right to modify, add, or remove duties and to assign other duties as necessary. In addition, reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions of this position in compliance with the Americans with Disabilities Act of 1990. Candidates may be required to go through a pre-employment criminal background check. HealthEdge is an equal opportunity employer. We are committed to workforce diversity and actively encourage all qualified persons to seek employment with us, including, but not limited to, racial and ethnic minorities, women, veterans and persons with disabilities. #LI-Remote **The annual US base salary range for this position is $130,000 to $165,000. This salary range may cover multiple career levels at HealthEdge. Final compensation will be determined during the interview process and is based on a combination of factors including, but not limited to, your skills, experience, qualifications and education.

• Establish groundbreaking performance benchmarking methodologies and analysis workflows and identify performance issues and opportunities for NVIDIA’s inference ecosystem (e.g. TensorRT/TensorRT-EdgeLLM/Torch-TensorRT) • Contribute features and code to NVIDIA/OSS inference frameworks including but not limited to TensorRT/TensorRT-EdgeLLM/Torch-TensorRT. • Develop new model pipelines for NVIDIA’s inference ecosystem with optimized performance including but not limited to areas like quantization, scheduling, memory management, and distributed inference to set the gold standard for Gen AI performance. • Work with cross-collaborative teams inside and outside of NVIDIA across generative AI, automotive, robotics, image understanding, and speech understanding to set directions and develop innovative inference solutions. • Scale performance of deep learning models across different architectures and types of NVIDIA accelerators.

Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career. About the team Stripe processes over $1T in payments volume per year, which is roughly 1% of the world’s GDP. The tremendous amount of data makes Stripe one of the best places to do machine learning. The ML Infra team builds services and tools that power every step in the ML lifecycle, including data exploration, feature generation, experimentation, training, deploying, serving ML models, and building LLM applications. With the phenomenal developments happening in the field of AI, we are positioned to accelerate the adoption of AI/ML across all parts of the company by building highly scalable and reliable foundational infrastructure. What you’ll do You will work closely with machine learning engineers, data scientists, and product engineering teams to enable seamless end-to-end experience in building solutions across data, analytics, and AI/ML platforms. You will build the next generation of ML Infra services and major new capabilities that substantially improve ML development velocity and MLOps maturity across the company. Responsibilities - Designing and building scalable, reliable, and secure services for notebooks, ML model training, experimentation, serving, and LLM applications across multiple regions. - Creating services and libraries that enable ML engineers at Stripe to seamlessly transition from experimentation to production across Stripe’s systems. - Working directly with product teams and ML engineers to improve their day-to-day productivity. - Taking ownership of and finding solutions for technical and product challenges by working with a diverse set of systems, processes, and technologies. Who you are We’re looking for people with a strong background or interest in building successful products or systems; you’re passionate about solving business problems and making impact, you are comfortable in dealing with lots of moving pieces; and you’re comfortable learning new technologies and systems. You are comfortable working with other Stripe teams across the US and Canada. Minimum requirements - 2+ years of professional software development experience with a solid background on service oriented architecture and large-scale distributed systems - Experience working through the full life cycle of software development, from talking to users, to design and implementation, to testing and deployment, to operations - Experience working on production ML platforms, MLOps solutions, or building LLM applications - Experience running operations for high availability, low latency systems - Experience partnering with other teams to drive business outcomes - A sense of pragmatism: you know when to aim for the ideal solution and when to adjust course Preferred qualifications - Experience building and shipping production AI agents - Familiarity with the LLMs and LLM Frameworks - Experience training and shipping machine learning models to production to solve critical business problems