Machine Learning Engineer

Role - ML Engineer

Location - Atlanta, GA Onsite

Contract

Job Description

• Leverage distributed training systems to build scalable machine learning pipelines for model training and deployments in ITOT 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.
• Research and implement state-of-the-art LLM models for different business use cases including fine-tuning and serving the LLMs.
• 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.
• Build Deep Learning models and algorithms with optimal parallelism and performance on CPUs and GPUs.
• Your background and who you are:
• MS or PhD in Computer Science, Software Engineering, Electrical Engineering or related fields.
• 3 years of industry experience with Python in a programming-intensive role.
• 2 years of experience with one or more of the following machine learning topics: classification, clustering, optimization, recommendation system, graph mining, 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 Spark MLlib, Keras, Tensorflow, PyTorch, HuggingFace Transformers and libraries like scikit-learn, spacy, gensim, CoreNLP, etc.
• 3 years of industry experience with major cloud computing services.
• Background or experience in building and scaling Generative AI Applications specifically around frameworks like Langchain, PGVector, Pinecone, AzureML.
• Prior experience in building data products and established a track record of innovation would be a big plus.
• An effective communicator; you shall be an ambassador for Machine Learning engineering at external forums and have the ability to explain technical concepts to a non-technical audience.

Preferred Qualifications

• Proficient Python/PySpark coding experience.
• Proficient in containerization services.
• Proficient in Azure ML to deploy the models.
• Experience with working in CICD framework.
• Motivation to make downstream modelers work smoother.
• Background or experience in building and scaling Generative AI Applications specifically around frameworks like Langchain, PGVector, Pinecone, AzureML.
• Industry experience with popular ML frameworks such as Spark MLlib, Keras, Tensorflow, PyTorch, HuggingFace Transformers and libraries like scikit-learn, spacy, gensim, CoreNLP, etc.
• Experience in designing scalable services/controller architecture using FastAPI.

Skills

Machine Learning - Python