Senior ML Engineer
New
Based in the United StatesFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 6+ years
- Required Skills
- AWSDockerPythonKubernetesMachine LearningDeep LearningNLPMLOps
Requirements
- 6+ years of experience building and deploying ML/AI systems in production environments.
- Strong proficiency in Python.
- Experience building and scaling RAG-based systems and working with vector databases.
- Solid understanding of deep learning, NLP, and generative AI models (including LLMs).
- Experience designing and maintaining scalable ML pipelines and MLOps workflows.
- Familiarity with microservices architecture.
- Experience working with cloud environments (AWS preferred) and containerization tools like Docker and Kubernetes.
- Knowledge of data processing frameworks and relational or low-latency databases.
- Strong communication skills.
- Ability to balance research experimentation with production reliability.
Responsibilities
- Design, train, fine-tune, and evaluate ML, deep learning, and generative AI models including LLMs and advanced NLP systems.
- Build and maintain scalable ML pipelines for training, evaluation, and real-time/batch inference.
- Architect and optimize data pipelines for large-scale structured and unstructured datasets.
- Integrate AI models into production microservices with a focus on latency, scalability, and reliability.
- Develop robust evaluation frameworks covering model performance, bias mitigation, alignment, and safety guardrails.
- Optimize models and systems for cost, latency, and efficiency.
- Collaborate cross-functionally with backend, frontend, and product teams.
- Provide technical leadership through code reviews and architectural guidance.
- Mentor junior engineers.
- Contribute to AI roadmap discussions.
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