AI Engineer/Lead AI Engineer

Salesforce; Bengaluru, Hyderabad; On-site; INR 4,000,000 - 8,000,000; Full time

Job summary

Salesforce in Bengaluru seeks a senior data scientist to design, implement, and productionize ML/AI models at scale. You will lead end-to-end ML pipelines, collaborate with cross-functional teams, and mentor junior data scientists.

The role requires strong Python, TensorFlow/PyTorch, and cloud platform experience, with a track record of deploying AI products and driving business impact.

Qualifications

• 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).
• Mastery of Python for data manipulation, machine learning, and software development.

Responsibilities

• Design, implement, and deploy state-of-the-art models, including LLMs and Generative AI frameworks.
• Perform model optimization for performance, scalability, and accuracy.
• Leverage libraries like TensorFlow, PyTorch, and Hugging Face for experimentation and production.
• Build and optimize ML pipelines with AWS SageMaker, Airflow, or Prefect.
• Containerize applications using Docker and deploy to cloud platforms.
• Design and optimize SQL queries and database schemas for data retrieval.
• Architect scalable, fault-tolerant machine learning systems.
• Drive engineering excellence through clean, modular code and system design.

Skills

Python

TensorFlow

PyTorch

scikit-learn

LangChain

LlamaIndex

SQL

Spark

NLP

Leadership

Education

Bachelor’s/Master’s in Mathematics or Computer Science

Tools

Docker

AWS SageMaker

Airflow

Git

ETL

Spark

Job description

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.