Mindlance
Position Details
Rate:
PR:$65.62/hr
Duration:
6 months with a high chance of extension
Location:
Fully remote as long as located near an Exelon satellite in Chicago, Philadelphia, Washington D.C., Baltimore, Delaware, etc.
Work hours:
Full-time — 9am to 5pm EST or 8am to 4pm EST
Education preference:
MS in Computer Science/Data Science
Experience:
5+ years of industry/corporate experience preferred
Target start date:
10/27 or best
Industry profile:
Previous experience in utility industry is preferred but not required
Key qualities:
Great communication skills and the ability to independently identify and drive work to achieve objectives/milestones
Job Description Position Overview: We are seeking a highly skilled and motivated Machine Learning/Deep Learning Engineer with expertise in neural network development, GenAI technologies, and cloud-native deployment on Azure. This role will be instrumental in designing, training, and deploying advanced AI models across text, image, and audio domains, while also managing scalable cloud infrastructure and APIs.
Key Responsibilities
Deep Learning & Neural Networks
Design and implement deep learning models using TensorFlow, PyTorch, and transformer architectures.
Fine-tune pre-trained models for domain-specific tasks involving 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.
API Development & Integration
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.
Azure Cloud Engineering
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 Qualifications
5+ years of experience in Python development with a focus on 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 and ability to work in a fast-paced, collaborative environment.
Preferred Qualifications
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.
EEO:
Mindlance is an Equal Opportunity Employer and does not discriminate in employment on the basis of – Minority/Gender/Disability/Religion/LGBTQI/Age/Veterans.
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PR:$65.62/hr
Duration:
6 months with a high chance of extension
Location:
Fully remote as long as located near an Exelon satellite in Chicago, Philadelphia, Washington D.C., Baltimore, Delaware, etc.
Work hours:
Full-time — 9am to 5pm EST or 8am to 4pm EST
Education preference:
MS in Computer Science/Data Science
Experience:
5+ years of industry/corporate experience preferred
Target start date:
10/27 or best
Industry profile:
Previous experience in utility industry is preferred but not required
Key qualities:
Great communication skills and the ability to independently identify and drive work to achieve objectives/milestones
Job Description Position Overview: We are seeking a highly skilled and motivated Machine Learning/Deep Learning Engineer with expertise in neural network development, GenAI technologies, and cloud-native deployment on Azure. This role will be instrumental in designing, training, and deploying advanced AI models across text, image, and audio domains, while also managing scalable cloud infrastructure and APIs.
Key Responsibilities
Deep Learning & Neural Networks
Design and implement deep learning models using TensorFlow, PyTorch, and transformer architectures.
Fine-tune pre-trained models for domain-specific tasks involving 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.
API Development & Integration
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.
Azure Cloud Engineering
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 Qualifications
5+ years of experience in Python development with a focus on 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 and ability to work in a fast-paced, collaborative environment.
Preferred Qualifications
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.
EEO:
Mindlance is an Equal Opportunity Employer and does not discriminate in employment on the basis of – Minority/Gender/Disability/Religion/LGBTQI/Age/Veterans.
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