Staff Machine Learning Engineer

Sequoia; Bengaluru; On-site; INR 4,000,000 - 6,500,000; Full time

Job summary

Sequoia in Bengaluru seeks a Staff Machine Learning Engineer to lead architecture, development, and scaling of enterprise-grade ML and Generative AI platforms. You will drive AI strategy, establish best engineering practices, and mentor senior ML engineers.

You will collaborate with Product, Engineering, Data, and Business stakeholders to deliver measurable business outcomes and shape Sequoia's AI roadmap, building intelligent products impacting thousands of businesses globally.

Qualifications

• 12+ years of experience in Machine Learning, Data Science, and AI Engineering.
• Proven track record of delivering production-grade AI/ML products at scale.
• Experience leading complex technical initiatives and influencing engineering direction.
• Experience mentoring engineers and driving technical excellence across teams.

Responsibilities

• Define and drive the technical vision for Machine Learning and Generative AI initiatives.
• Lead architecture reviews and establish best practices for scalable AI systems.
• Mentor and guide ML engineers and data scientists across teams.
• Influence product strategy through AI-driven innovation and technical thought leadership.
• Partner with Engineering leadership to build scalable, reliable, and secure AI platforms.
• Design, develop, and deploy large-scale ML solutions in production environments.
• Build advanced predictive models, recommendation systems, forecasting solutions, NLP applications, and deep learning systems.

Skills

Python

SQL

Spark

PyTorch

TensorFlow

Scikit-learn

RAG

Agentic AI

AI evaluation

Docker

Vector databases

APIs & microservices

MLOps

Observability

Tools

Docker

Vector Databases

APIs & Microservices

Job description

We are seeking a highly experienced Staff Machine Learning Engineer to lead the architecture, development, and scaling of enterprise-grade Machine Learning and Generative AI platforms.

As a senior technical leader, you will drive AI strategy, establish engineering best practices, mentor ML engineers, and collaborate cross-functionally with Product, Engineering, Data, and Business stakeholders to deliver measurable business outcomes. You will play a critical role in shaping Sequoia's AI roadmap and building intelligent products that impact thousands of businesses globally.

The ideal candidate will have 12+ years of experience building and deploying large-scale ML systems, deep expertise across the full ML lifecycle, and hands‑on experience delivering production‑grade Generative AI solutions at scale.

Key Responsibilities

Technical Leadership

• Define and drive the technical vision for Machine Learning and Generative AI initiatives.
• Lead architecture reviews and establish best practices for scalable AI systems.
• Mentor and guide ML engineers and data scientists across teams.
• Influence product strategy through AI-driven innovation and technical thought leadership.
• Partner with Engineering leadership to build scalable, reliable, and secure AI platforms.
• Design, develop, and deploy large-scale ML solutions in production environments.
• Build advanced predictive models, recommendation systems, forecasting solutions, NLP applications, and deep learning systems.
• Drive the complete machine learning lifecycle:
• Data acquisition and exploration
• Model evaluation and validation
• Monitoring, governance, and continuous improvement
• Develop frameworks and reusable components to accelerate ML development across teams.
• Establish model governance, explainability, fairness, and compliance standards.

Generative AI & LLM Applications

• Architect and deliver enterprise-scale GenAI solutions leveraging:
• OpenAI
• Anthropic Claude
• Mistral
• Gemini
• Design and implement:
• Advanced RAG architectures
• Agentic AI systems
• AI orchestration frameworks
• Prompt engineering and evaluation frameworks
• Fine-tuning and model adaptation pipelines
• Knowledge graph-assisted AI systems
• AI observability and evaluation frameworks
• Lead experimentation and adoption of emerging AI technologies to create competitive advantage.
• Architect scalable ML platforms and infrastructure.
• Build and optimize end-to-end ML pipelines.
• Drive MLOps best practices including:
• CI/CD for ML
• Experiment tracking
• Monitoring and observability
• Automated retraining pipelines
• Model governance and security
• Optimize system performance, scalability, reliability, and cost efficiency.

Cross-Functional Collaboration

• Partner with Product Managers, Engineering leaders, and Business stakeholders to identify high-impact AI opportunities.
• Translate business problems into scalable AI solutions.
• Define success metrics and measure business impact.
• Drive AI adoption and technical excellence across the organization.

Preferred Qualification Experience:

• 8+ years of experience in Machine Learning, Data Science, and AI Engineering.
• Proven track record of delivering production-grade AI/ML products at scale.
• Experience leading complex technical initiatives and influencing engineering direction.
• Experience mentoring engineers and driving technical excellence across teams.

Technical Skills:

• Strong expertise in Python, SQL, and distributed computing frameworks such as Spark.
• Deep knowledge of machine learning and deep learning frameworks:
• PyTorch
• TensorFlow
• Scikit-learn
• Strong expertise in:
• Retrieval-Augmented Generation (RAG)
• Agentic AI Systems
• AI Evaluation Frameworks
• Hands-on experience with:
• Docker
• Vector Databases
• API and Microservices Architecture
• MLOps
• Observability and Monitoring

Leadership Attributes

• Strong architectural and systems‑thinking mindset.
• Ability to influence without authority and drive cross-functional alignment.
• Exceptional communication and stakeholder management skills.
• Passion for mentoring, innovation, and continuous learning.