Staff Machine Learning Engineer

This role is for one of our clients
Industry: Software Development
Seniority level: Mid-Senior level
Min Experience: 10+ years
Location: Bengaluru
JobType: full-time
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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 our AI roadmap and building intelligent products that impact thousands of businesses globally.
The ideal candidate will have 8+ 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.
Requirements
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
Machine Learning & Data Science
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:
Problem definition
Data acquisition and exploration
Feature engineering
Model development
Model evaluation and validation
Production deployment
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
Azure OpenAI
Anthropic Claude
Llama
Mistral
Gemini
Design and implement:
Advanced RAG architectures
Agentic AI systems
Multi-agent workflows
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.
Platform Engineering & MLOps
Architect scalable ML platforms and infrastructure.
Build and optimize end-to-end ML pipelines.
Drive MLOps best practices including:
CI/CD for ML
Model serving
Feature stores
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
Experience
Preferred Qualifications
10+ 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:
Large Language Models (LLMs)
Retrieval-Augmented Generation (RAG)
Agentic AI Systems
Reinforcement Learning concepts
AI Evaluation Frameworks
Hands-on experience with:
Docker
Kubernetes
AWS, Azure, or GCP
Vector Databases
API and Microservices Architecture
Expertise in:
MLOps
Model Deployment
Feature Stores
Experiment Tracking
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
Must-have Skills
Applied Machine Learning
Good-to-have Skills
Machine Learning, AI ENGINEERING

Work arrangement
No