Staff Machine Learning Engineer

Role details

Weekday - Staff Machine Learning Engineer Staff Machine Learning Engineer Bengaluru Technology, Information and Media – Technology, Information and Media / Full-time / On-site apply for this job 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 ₹80,00,000 - ₹99,00,000 a year 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. Preferred Qualifications Experience 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 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. apply for this job Jobs powered by