Applied Scientist II
$155,000–$203,500 year
HybridReston, Virginia, United States
Job Summary
Address product challenges using Large Language Models, Deep Learning, and Data Science approaches while publishing research papers. Work within a multidisciplinary team to research, implement, evaluate, optimize, and maintain cutting-edge machine learning models that meet the demands of rapidly growing business needs. Stay current on latest developments to present findings to the broader community and collaborate closely with engineers and product managers on design reviews and requirement definitions. Contribute to the Conversational AI, NLP, and Data Science technology roadmap by designing and building Agentic AI systems to solve complex customer challenges.
Required Qualifications
- Bachelors and Ph.D in Computer Science or related fields
- Solid understanding of machine learning fundamentals and tool ecosystem
- 3+ years of combined academic and industrial research experience in machine learning, NLP, information retrieval, deep learning or a related field
- Experience with Agentic AI systems, including design, development, and rigorous evaluation of agent performance
- Deep learning implementation expertise (TensorFlow, PyTorch etc)
- Excellent command of at least one modern programming language (preferably Python)
- Deep understanding of machine learning model life cycle management
- Depth in one or more of the following: Natural Language processing, information retrieval, speech processing, deep learning, reinforcement learning, etc
- Knowledge of or experience in building production quality and large scale deployment of applications related to machine learning
- Comfortable working in a fast paced, highly collaborative, dynamic work environment
- Experience in machine learning systems (e.g. SageMaker, MLFlow), and deep learning frameworks (e.g. TensorFlow, PyTorch, MXNet etc)
- Preference for a publication record in top-tier ML and NLP conferences (e.g. NeurIPS, ICML, SIGIR, ICLR, ACL, EMNLP, etc)
Desired Qualifications
- Leverage your deep knowledge of artificial intelligence (AI) principles, including machine learning, natural language processing, computer vision, and reinforcement learning
- Use your understanding of both supervised and unsupervised learning techniques, and their applications in building intelligent systems
- Develop and optimize algorithms for building scalable and efficient GenAI applications
- Tackle challenging problems in creative ways, leveraging generative models to address real-world use cases and drive innovation
- Use effective communication skills to articulate technical concepts to non-technical stakeholders and gather requirements for GenAI application development
- Passion for leveraging cutting-edge AI technology to create innovative GenAI applications that have a meaningful impact on businesses, industries, and society
- Commitment to developing GenAI applications that adhere to ethical standards and promote positive societal impact while minimizing potential risks
- Drive to push the boundaries of what's possible with AI, and to contribute to the advancement of the field through research, experimentation, and collaboration
- Willingness to stay updated with the latest advancements in AI research and technology, and to continuously learn and adapt to new methodologies and best practices
- Agility to pivot and iterate on GenAI applications based on feedback, emerging trends, and changing business requirements
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