Key Responsibilities
Machine Learning and AI Development
- Design, implement, and deploy state-of-the-art models, including LLMs and Generative AI frameworks.
- Perform model optimization for performance, scalability, and accuracy.
- Leverage leading libraries like TensorFlow, PyTorch, and Hugging Face for experimentation and production.
- Utilize common AI development frameworks such as LangChain, LlamaIndex, and others to build and optimize AI applications.
- Write clean, maintainable, and highly optimized code while following advanced Git workflows like Gitflow.
- Build and optimize machine learning pipelines with tools like AWS SageMaker, Airflow, or Prefect.
- Containerize applications using Docker and deploy them to cloud platforms.
- Implement robust CI/CD pipelines for seamless machine learning deployments.
- Design and optimize SQL queries and database schemas for efficient data retrieval.
- Develop and manage scalable feature engineering pipelines.
- Architect scalable, fault-tolerant machine learning systems.
- Drive engineering excellence through best practices in clean, modular code and system design.
Team Leadership
- Mentor and guide junior data scientists, fostering a culture of learning and innovation.
- Conduct code reviews and ensure adherence to best practices in software engineering and AI development.
- Establish and enforce standards and best practices for data science workflows.
- Influence stakeholders beyond the data science team, driving organizational alignment on DS/ML standards.
Operational Excellence
- Establish and maintain streamlined, scalable processes for data science solution development.
- Align with company standards to ensure consistency and scalability in AI deployments.
Business Impact
- Collaborate with stakeholders to define problems, metrics, and data-driven solutions.
- Translate complex technical insights into actionable business strategies that deliver measurable value.
Qualifications
Experience and Education
- 5+ years of experience in data science, including deploying AI/ML products at scale.
- Bachelor’s or Master’s degree in Mathematics, Computer Science, or a related field (or equivalent experience).
Technical Expertise
- Mastery of Python for data manipulation, machine learning, and software development.
- Proficiency in ML frameworks like TensorFlow, PyTorch, and scikit-learn.
- Proficiency with AI/ ML frameworks like scikit-learn, LangChain, and Llamaindex.
- Knowledge of software engineering principles and best practices, including version control, code optimization, modular design, and testing methodologies.
- Experience with tools like Docker, AWS SageMaker, and Airflow for pipeline optimization.
- Proficiency in SQL, Spark, and ETL processes.
- Familiarity with Generative AI, LLMs, NLP frameworks, and vector databases.
- Hands-on experience with cloud platforms like AWS.
Soft Skills
- Craft detailed design documents and technical white papers.
- Translate technical concepts into business-friendly language.
- Lead cross-functional discussions and align diverse viewpoints.
- Deliver polished presentations to senior stakeholders.
- Exhibit exceptional problem-solving and leadership abilities.