machine learning engineer

$104,000 - $115,440/Yr

Randstad - Atlanta, GA

Full-time - Mid Level

Atlanta, GA

Administrative and Support Services

About the position

The Machine Learning Engineer position is a contract role based in Atlanta, Georgia, offering a competitive hourly wage of $50 to $55.50. The ideal candidate will possess a postgraduate degree in Computer Science, Software Engineering, Electrical Engineering, or a related field, along with a minimum of three years of industry experience in a programming-intensive role, particularly with Python. The role requires expertise in machine learning topics such as classification, clustering, optimization, recommendation systems, graph mining, and deep learning, with at least two years of experience in these areas. Additionally, candidates should have substantial experience with distributed computing frameworks like Spark and Kubernetes, as well as familiarity with popular machine learning frameworks including Spark MLlib, Keras, TensorFlow, PyTorch, and HuggingFace Transformers. The successful candidate will be responsible for leveraging distributed training systems to build scalable machine learning pipelines for model training and deployments in the ITOT Products space. They will design and implement solutions to optimize distributed training execution, focusing on model hyperparameter optimization, training/inference latency, and system-level bottlenecks. The role also involves researching and implementing state-of-the-art LLM models for various business use cases, ensuring ML model performance and uptime, and maintaining high standards of code quality and thoughtful design. Furthermore, the engineer will optimize integration between popular machine learning libraries and cloud ML and data processing frameworks, and build deep learning models and algorithms with optimal parallelism and performance on CPUs and GPUs.

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, 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.

Requirements

• 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 machine learning topics: classification, clustering, optimization, recommendation systems, graph mining, deep learning.
• 3 years of industry experience with distributed computing frameworks such as Spark and Kubernetes.
• 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.
• 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.

Nice-to-haves

• Proficient Python/PySpark coding experience.
• Proficient in containerization services.
• Proficient in Azure ML to deploy the models.
• Experience with working in CI/CD framework.
• Motivation to make downstream modelers work smoother.
• Experience in designing scalable services controller architecture using FastAPI.

Benefits

• Health insurance coverage.
• 401K contribution.
• Incentive and recognition program.