Machine Learning Engineer
2 days ago
RAND Corporation is seeking a highly skilled Machine Learning Engineer to join our research team. As a Machine Learning Engineer, you will work closely with researchers and analysts to develop and maintain custom applications and data pipelines featuring generative AI, natural language processing, and other foundation models.
Key Responsibilities:- Develop and maintain custom applications and data pipelines using machine learning and AI techniques
- Collaborate with researchers and analysts to design and implement AI solutions
- Train and fine-tune machine learning models using TensorFlow and/or PyTorch
- Build and maintain machine learning pipelines that leverage LLMs and other foundation models
- Stay up-to-date with the latest advancements in machine learning and AI research
- Strong knowledge of deep learning and generative artificial intelligence
- High-level proficiency in Python
- Experience with TensorFlow and/or PyTorch
- Experience with LangChain, LlamaIndex, or similar frameworks
- Experience with techniques like fine-tuning and retrieval augmented generation
- Background in natural language processing algorithms
- Cloud computing experience
- At least 2 years of relevant experience required. At least 5 years of relevant experience preferred.
- At least 1 year of experience in generative AI required.
- BA/BS in Computer Science, Engineering, Statistics, or related quantitative field required.
- MA/MS in Computer Science, Engineering, Statistics, or related quantitative field strongly preferred.
Ability to obtain and maintain at least a Secret U.S. government security clearance is required. U.S. citizenship is required for a U.S. government security clearance.
Location:Santa Monica, CA; Washington DC; or Pittsburgh, PA
Salary Range:$85,700 - $152,400
Level II: $85,700 - $127,500
Level III: $100,100 - $152,400
RAND considers a variety of factors when formulating an offer, including but not limited to, the specific role and associated responsibilities; a candidate's work experience, education/training, skills, expertise; and internal equity.
Equal Opportunity Employer: race/color/religion/sex/sexual orientation/gender identity/national origin/disability/vet
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