Senior AI Engineer

2 days ago

Vienna, Virginia, United States eSolutionsFirst Full time
Lead Groundbreaking AI Innovation with Your Expertise.
As a Senior AI Engineer with a PhD, you will be at the forefront of our AI initiatives, driving innovation through deep technical expertise and hands-on development. You will not only design and architect advanced AI systems but also actively contribute to their implementation, pushing the boundaries of what's possible. Your ability to translate complex research concepts into practical, scalable solutions will be critical to our success.As a Senior AI Engineer, you'll be a hands-on technical leader, architecting, developing, and deploying cutting-edge AI solutions that directly impact our business. You'll bridge the gap between complex AI concepts and real-world applications, working closely with cross-functional teams to solve challenging problems and drive tangible results. You'll not only design the architecture but also dive deep into the code, ensuring the performance, scalability, and reliability of our AI systems.
Responsibilities:
  • Hands-on AI Development & Deployment: Design, develop, and deploy scalable AI models and systems, including machine learning, deep learning, and natural language processing solutions. Write efficient, robust code in Python and leverage big data technologies like PySpark, Databricks, and AWS AI services (SageMaker, Bedrock).
  • Data Architecture & Pipeline Engineering: Architect and implement data infrastructure solutions for AI applications, including data ingestion pipelines, data warehousing, and data processing. Optimize data pipelines for performance and scalability.
  • Cloud-Native AI Solutions: Architect and implement highly available, scalable, and resilient cloud environments, with a primary focus on AWS. Deploy and manage production AI applications in the cloud, ensuring seamless integration with existing systems.
  • Model Training & Optimization: Train, tune, and optimize machine learning models for specific business use cases. Evaluate model performance and implement strategies for continuous improvement. Experience in training LLMs is highly desired.
  • Technical Leadership & Mentorship: Provide technical guidance and mentorship to junior engineers. Lead code reviews, enforce coding standards, and promote best practices for AI development.
  • Problem Solving & Innovation: Troubleshoot complex technical issues, identify performance bottlenecks, and implement innovative solutions. Stay up-to-date with the latest advancements in AI and contribute to the development of new AI capabilities.
  • Collaboration & Communication: Collaborate closely with data scientists, product managers, and other stakeholders to translate business requirements into technical solutions. Effectively communicate complex technical concepts to both technical and non-technical audiences.
  • Security & Compliance: Ensure that AI systems and data pipelines comply with security and compliance requirements.
You Have:
  • 10+ years of experience in software development, with a strong focus on AI and machine learning.
  • 5+ years of hands-on experience developing and deploying AI solutions using Python and relevant libraries (e.g., TensorFlow, PyTorch, scikit-learn).
  • Extensive experience with big data technologies such as PySpark, Databricks, Hive, or similar.
  • Deep expertise with the AWS AI product tool suite, including SageMaker Studio and Bedrock.
  • Proven experience architecting and deploying production AI applications in AWS cloud environments.
  • Strong understanding of data architecture principles and experience designing data pipelines for AI applications.
  • Experience with model training, tuning, and optimization techniques.
  • Excellent problem-solving and debugging skills.
  • Strong communication and collaboration skills.
  • Bachelor's degree in Computer Science, Engineering, or a related field.
  • Ability to obtain and maintain a Public Trust or Suitability/Fitness determination based on client requirements.
Nice If You Have:
  • Experience training LLMs.
  • Experience with GCP or Microsoft Azure.
  • Knowledge of security and compliance requirements for cloud-based solutions.
  • Security, Cloud, or Software Development Certifications, including AI, ML, Computer Vision, Deep Learning, or NLP certifications.
  • Experience providing technical guidance to architects and engineers.

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