ML Engineer

1 month ago


Atlanta, United States JobRialto Full time
Job Overview:

We are seeking a skilled Machine Learning Engineer to join our team. The ideal candidate will leverage distributed training systems to build scalable machine learning pipelines for model training and deployments in the ITOT Products space. This role involves designing and implementing solutions to optimize distributed training execution, researching and implementing state-of-the-art LLM models, and ensuring high standards of code quality and monitoring.

Key Responsibilities:

• 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 while 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.

Required Skills and Qualifications:

• 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 systems, 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 a track record of innovation.

• Effective communicator, able to explain technical concepts to a non-technical audience and act as an ambassador for Machine Learning engineering at external forums.

Preferred Qualifications:

• Proficient Python/PySpark coding experience.

• Proficient in containerization services.

• Proficient in Azure ML to deploy the models.

• Experience with working in a CI/CD 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.

Education: Bachelors Degree
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