Machine Learning Engineer - Generative Ai & Ml Operations

Description

SAIC is a premier technology integrator solving our nation’s most complex modernization and readiness challenges. Our robust portfolio of offerings across the defense, space, civilian, and intelligence markets includes high-end solutions in engineering, IT, and mission solutions. Using our expertise and understanding of existing and emerging technologies, we integrate the best components from our own portfolio and our partner ecosystem to deliver innovative, effective, and efficient solutions.
Position Overview
SAIC invites applications from exceptional candidates for the position of Machine Learning Engineer in our AI Innovation Factory. This is a full-time remote opportunity that can be worked anywhere within the United States.
As a member of our new independent research and development (IRAD) group, you will collaborate with your colleagues to explore emerging trends and advancements in generative AI research and technologies. Under the guidance of experienced engineers, you will contribute to developing Machine Learning solutions using best practices in MLOps. Most importantly, you will contribute to solving complex problems for our government and public sector customers.
Responsibilities

• Assist senior team members to seamlessly integrate Machine Learning innovations into new and existing user-facing systems.
• Contribute to the development of proofs of concept, delivering value to both internal and external customers.
• Collaborate with your team to explore emerging ML research and technologies.
• Learn from industry trends, advances, and tool sets in generative AI and MLOps to expand your knowledge and fuel innovation.
• Assist in the technical assessment of emerging commercial and open-source solutions to ensure their applicability.
• Contribute to our organization's knowledge base by creating documentation and training materials focused on advanced AI techniques.
• Collaborate with team members to establish best practices for generative AI development.

Qualifications

Required Qualifications:

• Must be a U.S. Citizen.
• A Bachelor’s degree in Computer Science, Mathematics, Statistics, Engineering or a related field with two or more years of experience. In lieu of a degree, four additional years of professional experience will be considered.
• Experience with Python programming language and popular Machine Learning libraries and frameworks such as PyTorch, Keras, TensorFlow, or scikit-learn.
• Excellent communication skills to collaborate effectively with cross-functional teams and non-technical stakeholders.
• Ability to learn and adapt quickly in a fast-paced, dynamic environment.

Desired Qualifications:

• Familiarity with common LLM abstraction layers like LangChain, DSPy, or LlamaIndex.
• Experience working with multi-stage reasoning or open-ended agent frameworks.
• Knowledge of open source vector databases, such as ChromaDB or Milvus.
• Familiarity with document chunking and retrieval methods in the context of retrieval-augmented generation (RAG) systems.
• Experience using model lifecycle management tools like MLflow, Neptune, or Amazon SageMaker; serving tools like Seldon Core or TensorFlow Serving; and monitoring and observability tools such as Arize, WhyLabs, or Fiddler.
• Proficiency in using the native services of cloud providers, including Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform (GCP).
• Previous collaboration with teams following software development methodologies like Agile.