Principal Machine Learning Engineer in India at Jobgether

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Principal Machine Learning Engineer in India.

This role sits at the core of a high-impact AI/ML organization focused on building intelligent, cloud-native systems that optimize enterprise technology usage at scale. You will lead the design and productionization of advanced machine learning and GenAI solutions that drive cloud cost optimization, workload prediction, and infrastructure automation. Operating in a collaborative, matrixed environment, you will work closely with data, engineering, product, and DevOps teams to translate complex business needs into scalable ML architectures. The position combines hands-on technical depth with strategic leadership, requiring you to guide end-to-end ML initiatives from experimentation to production. You will also play a key role in shaping MLOps practices and driving adoption of modern AI paradigms, including LLMs and agentic systems. This is a highly influential role where your work directly impacts enterprise-scale efficiency and innovation.

In this role, you will be responsible for leading the development and deployment of end-to-end machine learning and GenAI solutions in a cloud-native environment. You will define ML roadmaps, translate business requirements into scalable architectures, and oversee execution across multiple technical teams. You will build production-grade models for workload prediction, optimization, and automation while ensuring operational excellence through strong MLOps practices. You will also integrate LLM-based and agentic AI systems into both internal platforms and customer-facing products, ensuring scalability and reliability in production environments.

• Lead end-to-end design, development, and deployment of ML, GenAI, and agentic AI solutions
• Define ML strategy, architecture, and roadmap aligned with business and product goals
• Build and deploy models for cloud workload forecasting, optimization, and intelligent automation
• Drive adoption of MLOps best practices for scalable and reliable ML systems
• Integrate LLMs and GenAI frameworks (e.g., OpenAI, Hugging Face, LangChain) into production systems
• Collaborate with product, engineering, and DevOps teams to manage dependencies and delivery timelines
• Communicate technical strategy, insights, and progress to both technical and non-technical stakeholders

This role requires extensive experience in machine learning engineering with strong technical depth in ML frameworks, cloud infrastructure, and production-scale deployments. You should bring proven leadership in delivering ML/AI systems in SaaS or cloud environments, along with hands-on expertise in modern GenAI technologies. Strong programming skills, system design ability, and experience in distributed collaboration are essential.

• 10+ years of experience in ML/AI, data engineering, or related fields
• Bachelor’s, Master’s, or PhD in Computer Science, AI, Machine Learning, or related discipline
• Proven experience delivering ML solutions into production at scale, preferably in SaaS/cloud environments
• Strong hands-on expertise in Python and ML frameworks (scikit-learn, TensorFlow, PyTorch)
• Experience with AWS and Terraform; familiarity with Databricks and Spark preferred
• Hands-on experience with GenAI, LLMs, and agentic AI frameworks (OpenAI, Hugging Face, LangChain, etc.)
• Strong ability to define architecture, lead technical direction, and coordinate cross-functional teams
• Excellent communication skills for both technical and executive-level stakeholders

• Opportunity to work on cutting-edge GenAI and large-scale ML systems
• Remote-friendly and flexible work environment
• Exposure to enterprise-grade cloud optimization and AI transformation initiatives
• Collaborative, global engineering culture with high-impact ownership
• Continuous learning and innovation in ML, MLOps, and AI engineering
• Competitive compensation aligned with experience and market standards