InterviewGIG
AI Engineer/Lead AI Engineer Salesforce
InterviewGIG, San Francisco, California, United States, 94199
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.
#J-18808-Ljbffr
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.
#J-18808-Ljbffr