Tech Stack
AWSCloudPythonPyTorchTensorflow
About the role
- Lead and manage a team of 5-10 engineers, providing mentorship and fostering a collaborative team environment;
- Drive the roadmap for machine learning projects aligned with business goals;
- Coordinate cross-functional efforts with product, data, and engineering teams to ensure seamless delivery;
- Design, develop, and fine-tune LLMs and other machine learning models to solve business problems;
- Evaluate and implement state-of-the-art LLM techniques for NLP tasks such as text generation, summarization, and entity extraction;
- Stay ahead of advancements in LLMs and apply emerging technologies;
- Expertise in multiple main fields of ML: NLP, Computer Vision, RL, deep learning and classical ML;
- Architect and manage scalable ML solutions using AWS services (e.g., SageMaker, Lambda, Bedrock, S3, ECS, ECR, etc.);
- Optimize models and data pipelines for performance, scalability, and cost-efficiency in AWS;
- Ensure best practices in security, monitoring, and compliance within the cloud infrastructure;
- Oversee the entire ML lifecycle, from research and experimentation to production and maintenance;
- Implement MLOps and LLMOps practices to streamline model deployment and CI/CD workflows;
- Debug, troubleshoot, and optimize production ML models for performance;
- Conduct regular code reviews and ensure engineering standards are upheld;
- Facilitate professional growth and learning for the team through continuous feedback and guidance;
- Communicate progress, challenges, and solutions to stakeholders and senior leadership.
Requirements
- Proven experience with LLMs and NLP frameworks (e.g., Hugging Face, OpenAI, or Anthropic models)
- Strong expertise in AWS Cloud Services
- Strong experience in ML/AI, including at least 2 years in a leadership role
- Hands-on experience with Python, TensorFlow/PyTorch, and model optimization
- Familiarity with MLOps tools and best practices
- Excellent problem-solving and decision-making abilities
- Strong communication skills and the ability to lead cross-functional teams
- Passion for mentoring and developing engineers
- Familiarity with Amazon Bedrock would be considered a significant plus