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Senior Machine Learning Engineer – Foundational Models and Agentic Systems
Not specifiedFull-timeAI & Machine LearningEnterprise Software
Join a generative AI engineering team developing scalable models and customer-facing solutions. The role combines model architecture, optimization, deployment, evaluation, and data pipeline development across cross-functional teams.
Responsibilities
- Design and build generative AI systems for inference, quantization, optimization, fine-tuning, and evaluation
- Develop and refine generative AI models and architectures with product managers, data scientists, and engineers
- Automate, deploy, monitor, and improve generative AI solutions
- Work with varied data sources to refine features and build end-to-end data pipelines
- Explore advanced AI technologies and apply them to customer-focused products
- Communicate technical results to peers and organizational leaders
Requirements
- Experience with LLM tools and frameworks such as LangChain, vLLM, and Hugging Face
- Proficiency in Python and machine learning tools such as Spark
- Experience with AWS and container technologies including Docker and Kubernetes
- Familiarity with Kubeflow or MLflow
- Experience designing and developing generative AI architectures
- Knowledge of classification, regression, clustering, and model training, validation, and testing
- Experience with relational, NoSQL, or stream-processing systems
- Knowledge of distributed computing technologies such as Spark and Hive
- Production software engineering experience with Git and GitHub
- Strong foundations in data structures, algorithms, performance, complexity, and computer architecture
- Knowledge of linear algebra, calculus, and probability
- Bachelor’s, master’s, or doctoral degree in computer science or a related field, or equivalent practical experience
Benefits
- Competitive compensation package
- Performance-based rewards
- Potential cash bonus
- Potential equity rewards
- Benefits according to applicable plans and programs