This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Principal Engineer, Machine Learning based in India.
This is an outstanding opportunity for an experienced machine learning leader to architect and deliver advanced AI solutions that solve complex business challenges at scale. You will work across the full AI lifecycle, transforming business requirements into robust, production-ready machine learning systems while guiding technical strategy and engineering best practices. Collaborating with cross-functional teams and stakeholders, you will drive innovation in Generative AI, large language models, and cloud-native AI platforms. The role offers significant ownership, technical leadership, and the opportunity to shape cutting-edge AI initiatives in a dynamic, engineering-focused environment.
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Principal Engineer, Machine Learning based in India.
This is an outstanding opportunity for an experienced machine learning leader to architect and deliver advanced AI solutions that solve complex business challenges at scale. You will work across the full AI lifecycle, transforming business requirements into robust, production-ready machine learning systems while guiding technical strategy and engineering best practices. Collaborating with cross-functional teams and stakeholders, you will drive innovation in Generative AI, large language models, and cloud-native AI platforms. The role offers significant ownership, technical leadership, and the opportunity to shape cutting-edge AI initiatives in a dynamic, engineering-focused environment.
Accountabilities:
- Translate business objectives and client requirements into scalable AI and machine learning architectures that align with both functional and non-functional requirements.
- Design, develop, and oversee the implementation of end-to-end AI/ML solutions leveraging cloud-native platforms, big data technologies, and modern machine learning frameworks.
- Lead architectural decisions, evaluate alternative technical approaches, and recommend optimal technologies, frameworks, and design patterns.
- Develop and review architecture documentation, technical designs, proof of concepts, and implementation strategies to guide engineering teams.
- Ensure solutions meet high standards of scalability, security, extensibility, reliability, performance, and operational excellence.
- Design, develop, and deploy AI agents, multi-agent systems, and Generative AI solutions using large language models, prompt engineering, and retrieval-augmented generation techniques.
- Support engineering teams by reviewing code, resolving complex technical issues through root cause analysis, and mentoring developers on AI/ML best practices.
- Promote responsible AI practices while driving innovation across machine learning, MLOps, and intelligent automation initiatives.
- Bachelor's or Master's degree in Computer Science, Information Technology, or a related field.
- 11+ years of professional experience, including significant expertise in machine learning, artificial intelligence, and data engineering.
- Proven success delivering AI solutions across NLP, computer vision, Generative AI, and advanced machine learning applications.
- Strong experience designing and implementing AI/ML architectures on cloud infrastructure and large-scale data platforms.
- Advanced proficiency in Python (or R), SQL, Pandas, NumPy, and modern software engineering practices.
- Extensive experience with TensorFlow, PyTorch, JAX, scikit-learn, or equivalent machine learning frameworks.
- Solid understanding of statistical analysis, machine learning algorithms, and real-world model deployment strategies.
- Hands-on experience with MLOps technologies such as MLflow, Kubeflow, Docker, Kubernetes, and automated model deployment pipelines.
- Experience building AI agents, multi-agent systems, prompt engineering workflows, foundation models, and large language model applications.
- Practical knowledge of Generative AI techniques including RAG, GANs, VAEs, and prompt optimization.
- Strong analytical thinking, problem-solving abilities, and architectural decision-making skills.
- Excellent communication, collaboration, and stakeholder management skills.
- Understanding of AI ethics, governance, and responsible AI principles.
- Opportunity to lead enterprise-scale AI and machine learning initiatives
- Exposure to cutting-edge technologies including Generative AI, LLMs, and intelligent agent systems
- Collaborative, innovation-driven engineering culture
- Global, cross-functional work environment
- Continuous learning and professional development opportunities
- Significant technical ownership and architectural leadership responsibilities
- Career growth within a fast-scaling digital product engineering organization
Requirements:
Benefits: