Senior Advanced ML Engineer

Kforce • Washington, DC

35d • Hybrid

About The Position

Kforce has a client seeking a hybrid Senior Advanced ML Engineer to join their team. The Senior Advanced ML Engineer will provide expert-level technical leadership in the design and development of AI algorithms, models, and systems. They will be responsible for acting as the subject matter expert for technical AI projects and provide direction on exploring and implementing methodologies and best practices. In this role, you will impact critical AI initiatives and drive technical excellence within the organization. This is a unique opportunity to play a key role in shaping the future of AI technology.

Requirements

• MS or Ph.D. in Computer Science, Electrical Engineering, or STEM related fields
• 3+ years of industry experience with Python in a programming intensive role
• 3+ years of experience with one or more of the following machine learning topics: classification, clustering, optimization, deep learning
• 3+ years of industry experience with distributed computing frameworks such as Spark, Kubernetes ecosystem, etc.
• 3+ years of industry experience with popular ML frameworks such as Keras, Tensorflow, PyTorch, HuggingFace Transformers and libraries (like scikit-learn, etc.)
• 3+ years of industry experience with major cloud computing services (AWS, Azure, etc.)
• Prior experience in building data products and established a track record of innovation
• An effective communicator - you shall be an ambassador of AI initiatives and have the ability to explain technical concepts to a non-technical audience

Responsibilities

• Collaborate with colleagues across multiple function groups on unique challenges across different business units
• Develop complicated, scalable and robust analytics solutions to solve business problems
• Leverage distributed training systems to build scalable machine learning pipelines for model training and deployments in IT/OT Products space
• Design and implement solutions to optimize distributed training execution in terms of model hyperparameter optimization, model training/inference latency and system-level bottlenecks
• Ensure ML Model performance, uptime, and scale, maintaining high standards of code quality and thoughtful design quality and monitoring
• Optimize integration between popular machine learning libraries and cloud ML and data processing frameworks

What This Job Offers

• Career Level: Senior
• Industry: Administrative and Support Services
• Education Level: Ph.D. or professional degree
• Number of Employees: 1,001-5,000 employees