Senior Machine Learning Engineer I, AI Governance
New
Based in the United StatesFull-TimeSenior
SalaryCompetitive salary and performance-based bonus opportunities.
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Job Details
- Experience
- 4+ years of experience designing, developing, and deploying production machine learning solutions
- Required Skills
- DockerPostgreSQLPythonKubernetesMachine LearningPyTorchTensorflowPrompt Engineering
Requirements
- Bachelor's or Master's degree in Computer Science, Mathematics, Statistics, or a related technical discipline.
- 4+ years of experience designing, developing, and deploying production machine learning solutions.
- Strong expertise in Python and experience with machine learning frameworks such as TensorFlow, PyTorch, Hugging Face, Keras, MXNet, or scikit-learn.
- Practical experience with both traditional machine learning techniques and modern LLM technologies, including prompt engineering, RAG, semantic search, and model fine-tuning.
- Ability to write scalable, production-quality software with strong software engineering best practices.
- Familiarity with search, information retrieval, ranking systems, and AI evaluation methodologies.
- Strong analytical, problem-solving, and communication skills with the ability to collaborate effectively across teams.
- Experience with SaaS applications, Node.js, TypeScript, Docker, Kubernetes, distributed systems, or cloud platforms such as AWS or Azure is considered an advantage.
- Curiosity, adaptability, and a continuous learning mindset with a passion for building customer-focused AI solutions.
Responsibilities
- Design, develop, deploy, and maintain end-to-end machine learning and AI-powered product features with a focus on quality, scalability, and performance.
- Build intelligent applications using modern AI techniques such as Retrieval-Augmented Generation (RAG), prompt engineering, fine-tuning, semantic search, few-shot learning, and other LLM-based approaches.
- Collaborate closely with cross-functional teams including product management, design, and engineering to deliver customer-focused solutions.
- Write clean, maintainable, and well-tested production code while creating clear technical documentation and architectural designs.
- Troubleshoot software issues, optimize model performance, and continuously improve reliability and maintainability.
- Stay informed on emerging AI and machine learning technologies, evaluating new tools and methodologies for future product enhancements.
- Contribute to Agile development processes while working with technologies such as Python, JavaScript, Node.js, Docker, PostgreSQL, Kubernetes, and related platforms.
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