At Groq. We believe in an AI economy powered by human agency. We envision a world where AI is accessible to all, a world that demands processing power that is better, faster, and more affordable than is available today. AI applications are currently constrained by the limitations of the Graphics Processing Unit (GPU), a technology originally developed for the gaming market and soon to become the weakest link in the AI economy.
Enter Groq's LPU™ AI Inference Technology. Specifically engineered for the demands of large language models (LLMs), the Language Processing Unit outpaces the GPU in speed, power, efficiency, and cost-effectiveness. The quickest way to understand the opportunity is to watch the following talk – groq.link/scspdemo.
Why join Groq? AI will change humanity forever, and we believe preservation of human agency and self determination is only possible if AI is made affordably and universally accessible. Groq’s LPUs will power AI from an early stage, and you will get to leave your fingerprint on civilization.
Engineering Lead, MultiModal
Mission: We are looking for an experienced and hands-on Engineering Leader for our MultiModal Team. You have a passion and fundamental understanding of multi modal generative ai models. You have existing experience building, running, optimizing or implementing non trivial adaptations of multi modal models (speech detection, speech generation, visual question answering and image generation). You will work collaboratively with cross-functional teams to create innovative solutions that drive our cloud-based AI initiatives.
Responsibilities & opportunities in this role:
- Model Development: Design, implement, and optimize multimodal machine learning models to enhance GroqCloud’s capabilities.
- Data Processing: Develop efficient data preprocessing pipelines for various modalities, ensuring high-quality input for model training.
- Collaboration: Work closely with data scientists, software engineers, and product managers to align multimodal solutions with business objectives and user needs.
- Performance Optimization: Analyze and fine-tune model performance, scalability, and efficiency, leveraging Groq’s unique hardware architecture.
- Prototyping and Testing: Build prototypes and conduct experiments to evaluate the effectiveness of multimodal approaches, iterating based on findings.
- Documentation and Reporting: Maintain comprehensive documentation of model architectures, processes, and results, and communicate findings to stakeholders.
- Stay Current: Keep abreast of the latest developments in multimodal AI and contribute to Groq’s research and innovation efforts.
Qualifications:
- Education: Bachelor’s or Master’s degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field.
- Experience: 10+ years of experience in machine learning, with a focus on multimodal models and applications.
- Leadership: 6+ years experience with a proven track record of building high performance teams and code.
- Technical Skills:
- Proficiency in programming languages such as Python, C++, and familiarity with libraries like TensorFlow, PyTorch, and OpenCV.
- Strong understanding of machine learning frameworks and methodologies, including deep learning architectures.
- Experience with data processing and feature extraction for text, images, and audio.
- Analytical Skills: Strong problem-solving abilities with a data-driven approach.
- Communication: Excellent verbal and written communication skills, with the ability to convey complex concepts to non-technical stakeholders.
Preferred Qualifications:
- Experience with cloud platforms and services (e.g., AWS, Google Cloud, Azure).
- Familiarity with containerization technologies (e.g., Docker, Kubernetes).
- Knowledge of emerging trends in multimodal AI and their practical applications.
Attributes of a Groqster:
- Humility - Egos are checked at the door
- Collaborative & Team Savvy - We make up the smartest person in the room, together
- Growth & Giver Mindset - Learn it all versus know it all, we share knowledge generously
- Curious & Innovative - Take a creative approach to projects, problems, and design
- Passion, Grit, & Boldness - no limit thinking, fueling informed risk taking
If this sounds like you, we’d love to hear from you!
Compensation: At Groq, a competitive base salary is part of our comprehensive compensation package, which includes equity and benefits. For this role, the base salary range is $240,000 to $420,400, determined by your skills, qualifications, experience and internal benchmarks.
Location: Groq is a geo-agnostic company, meaning you work where you are. Exceptional candidates will thrive in asynchronous partnerships and remote collaboration methods. Some roles may require being located near our primary sites, as indicated in the job description.
At Groq: Our goal is to hire and promote an exceptional workforce as diverse as the global populations we serve. Groq is an equal opportunity employer committed to diversity, inclusion, and belonging in all aspects of our organization. We value and celebrate diversity in thought, beliefs, talent, expression, and backgrounds. We know that our individual differences make us better.
Groq is an Equal Opportunity Employer that is committed to inclusion and diversity. Qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, gender, sexual orientation, gender identity, disability or protected veteran status. We also take affirmative action to offer employment opportunities to minorities, women, individuals with disabilities, and protected veterans.
Groq is committed to working with qualified individuals with physical or mental disabilities. Applicants who would like to contact us regarding the accessibility of our website or who need special assistance or a reasonable accommodation for any part of the application or hiring process may contact us at: talent@groq.com. This contact information is for accommodation requests only. Evaluation of requests for reasonable accommodations will be determined on a case-by-case basis.