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Senior Applied ML Engineer

Summary

Senior Applied ML Engineer

Location-Remote

Job Summary

We are seeking a Senior Applied ML Engineer to develop, deploy, and optimize machine learning and AI solutions that solve real-world business problems. The ideal candidate will have strong expertise in machine learning, deep learning, data engineering, and MLOps, with experience in deploying scalable AI applications in production.

Key Responsibilities

Design, build, and deploy machine learning models for production environments.
Develop AI/ML solutions using supervised, unsupervised, and deep learning techniques.
Fine-tune and optimize Large Language Models (LLMs) and Generative AI applications.
Build and maintain end-to-end ML pipelines for data preprocessing, training, evaluation, and deployment.
Collaborate with data scientists, software engineers, and product teams to deliver AI-powered solutions.
Implement MLOps practices for model versioning, monitoring, and continuous deployment.
Evaluate model performance and continuously improve accuracy, scalability, and efficiency.
Conduct experiments and prototype new AI capabilities using the latest research and technologies.
Ensure AI solutions meet security, privacy, and governance requirements.
Mentor junior engineers and contribute to technical best practices.

Required Skills

Strong proficiency in Python and ML frameworks such as PyTorch, TensorFlow, or Scikit-learn.
Experience with Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and prompt engineering.
Knowledge of NLP, computer vision, or recommendation systems.
Experience with vector databases and embedding models.
Hands-on experience with cloud platforms (AWS, Azure, or Google Cloud Platform).
Experience with MLOps tools such as MLflow, Kubeflow, SageMaker, Vertex AI, or Azure ML.
Familiarity with Docker, Kubernetes, CI/CD, and Git.
Strong SQL and data engineering fundamentals.
Excellent problem-solving, analytical, and communication skills.

Preferred Qualifications

Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related field.
Experience deploying scalable AI applications in production.
Knowledge of distributed computing frameworks such as Spark or Ray.
Familiarity with AI evaluation, model monitoring, and responsible AI practices.
Experience with AI agents, multi-agent systems, or workflow orchestration frameworks is a plus.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

Dice Id: 10513292
Position Id: 73329-12895-1785784527
Posted 3 hours ago

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