Machine Learning/Deep Learning Engineer

Terms of Employment
W2 Contract, 4 months
This position is remote.
Candidates must be local to Chicago, Philadelphia, Washington D.C., Baltimore, or Delaware.

Overview
Our client is seeking a Machine Learning/Deep Learning Engineer with expertise in neural network development, GenAI technologies, and cloud-native deployment on Azure. This role is instrumental in designing, training, and deploying advanced AI models across text, image, and audio domains, as well as managing scalable cloud infrastructure and APIs.

Responsibilities
Design and implement deep learning models using TensorFlow, PyTorch, and transformer architectures.
Fine-tune pre-trained models for domain-specific tasks using text, image, or audio datasets.
Optimize and deploy models on NVIDIA GPU hardware (e.g., A100, H100) for high-performance inference.
Develop LLMOps context-aware pipelines for chat applications using Python frameworks.
Collaborate with data scientists and product teams to integrate models into production systems.
Develop and maintain RESTful and gRPC APIs for model serving and data access.
Manage the full API lifecycle, including versioning, documentation, and security.
Integrate APIs with internal and external applications using FastAPI or similar Python frameworks.
Create and manage Azure Container Apps, Container Registries, and Docker images.
Deploy and monitor Azure Web Apps for hosting AI services and dashboards.
Automate CI/CD pipelines using GitHub Actions for seamless deployment and updates.

Required Skills & Experience
At least 5+ years of industry/corporate experience with a focus on Python development and deep learning.
Hands-on experience with transformers, Hugging Face, and custom model training.
Proven track record of deploying models on GPU-based infrastructure.
Strong understanding of API design principles and microservices architecture.
Experience with Azure cloud services, Docker, and GitHub Actions.
Excellent problem-solving skills.
Ability to independently identify and drive work to achieve objectives/milestones.
Great communication skills.

Preferred Skills & Experience
Master's degree in Computer Science/Data Science.
Experience with multi-modal models or generative AI applications.
Familiarity with MLOps tools and practices.
Contributions to open-source AI projects or publications in relevant fields.
Previous experience in the utility industry is preferred but not required.