AI/ML Architect - Virginia, United States - Leidos

Leidos Virginia, United States

2 weeks ago

Description

At Leidos, we are driven by innovation.

We believe that by applying the highest standards of business ethics and visionary thinking, we can achieve everything and so can you as a Leidos employee.

Leidos values your skills, training, and experience.

The Health and Civil Sector (HCS) Capability Integration (CI) team reporting to the HCS CTO at Leidos is looking for an AI/ML Architect.

This is an exciting opportunity to use your experience and your AI/ML skills by helping the Health and Civil Sector AI/ML capability development and integration efforts.

The ideal candidate is passionate about a broad range of projects from research & development to prototype development, culminating in deployment of our products to customers.

We are on the cutting edge, inserting AI into health and civil systems, delivered through our AI Capability Integration in partnership with our business areas.

We are seeking a seasoned Artificial Intelligence (AI) Lead Architect with over 8+ years of extensive experience in designing and implementing AI solutions across various domains.

The ideal candidate will possess deep technical expertise in artificial intelligence, machine learning, and related technologies, coupled with proven track record of leading successful AI initiatives in complex environments.

As an AI/ML Architect, you will play a crucial role in designing and implementing robust, scalable, and efficient AI/ML solutions for our diverse range of projects.

In this role, you will:

Collaborate closely with cross-functional teams across the Health and Civil Sector and conduct comprehensive assessments of business processes, data ecosystems, and technology landscapes to identify AI opportunities and develop implementation plans.

Collaborate with data scientists and other AI professionals in the Office of Technology to augment digital transformation efforts by identifying and piloting use cases.

Discuss the feasibility of use cases along with architectural design with business teams and translate the vision of business leaders into realistic technical implementation.

At the same time, bring attention to misaligned initiatives and impractical use cases.

Align technical implementation with existing and future requirements by gathering inputs from multiple stakeholders — business users, data scientists, security professionals, data engineers and analysts, and those in IT operations — and developing processes and products based on the inputs.

Play a key role in using/defining the AI architecture and selecting appropriate technologies from a pool of open-source and commercial offerings.

Select cloud, on-premises or hybrid deployment models, and ensure new tools are well-integrated with existing data management and analytics tools.

Audit AI tools and practices across data, models and software engineering with a focus on continuous improvement. Ensure a feedback mechanism to assess AI services, support model recalibration and retrain models.

Work closely with security and risk leaders to foresee and overturn risks, such as training data poisoning, AI model theft and adversarial samples, ensuring ethical AI implementation and restoring trust in AI systems.

Remain acquainted with upcoming regulations and map them to best practices.

Minimum Qualifications:
Bachelor's with 10-12 years of relevant experience

5+ years of hands-on experience in architecting and implementing AI solutions, with strong focus on machine learning, deep learning, and natural language processing.

Large Language Model Expertise:

Experience in working with and fine-tuning Large Language Models (LLMs), including the design, optimization of NLP systems, frameworks, and tools.

Application Development with LLMs:

Experience in building scalable applications using LLMs, utilizing frameworks such as LangChain, LlamaIndex, etc and productionizing machine learning and AI models.

Language Model Development:
Utilize off-the-shelf LLM services, such as Azure OpenAI, to integrate LLM capabilities into applications.

Expertise in designing and deploying AI models and algorithms in production environments, using frameworks/libraries such as TensorFlow, PyTorch, scikit-learn, or Spark ML.

Proficiency in programming languages such as Python, Java, or Scala, and experience with cloud platforms (e.g. AWS) and containerization of technologies (e.g. Docker, Kubernetes).
Solid understanding of software architecture principles, including microservices, even-driven architecture, and distributed computing

Excellent communication and collaboration skills, with ability to interact effectively with technical and non-technical stakeholders at all levels of the organization.

Strong problem solving and analytical abilities with track record of translating business requirements into scalable, efficient, and innovative AI solutions.

Advanced certifications in artificial intelligence, machine learning, or related fields (e.g. AWS Certified Machine Learning Specialty, Google Cloud Professional Machine Learning Engineer).
Experience in designing AI-powered products or platforms in industries such as healthcare, transport, supply chain or climate.
Knowledge of advanced AI techniques, such as reinforcement learning, generative adversarial networks (GANs), or federated learning.

Original Posting Date:

While subject to change based on business needs, Leidos reasonably anticipates that this job requisition will remain open for at least 3 days with an anticipated close date of no earlier than 3 days after the original posting date as listed above.

Pay Range:
Pay Range $122, $220,900.00

The Leidos pay range for this job level is a general guideline onlyand not a guarantee of compensation or salary.

Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.

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