Associate Principal Engineer, Machine Learning
Job Description
Team: IT
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for an Associate Principal Engineer, Machine Learning based in India.
This role is a senior AI/ML architecture position focused on designing and delivering scalable, production-grade machine learning solutions across complex enterprise environments. You will work on end-to-end AI systems spanning data pipelines, model development, deployment, and monitoring, with strong emphasis on real-world impact. The position involves building advanced solutions across NLP, computer vision, and generative AI, including LLM-based systems and agentic architectures. You will collaborate closely with business and technical stakeholders to translate requirements into robust, scalable, and secure ML solutions. The environment is highly technical, innovation-driven, and cloud-centric, with strong focus on MLOps, automation, and responsible AI practices. This is a leadership-level engineering role where you will influence architecture decisions and shape the direction of AI solutions at scale.
Accountabilities:
- Design and architect end-to-end machine learning and AI solutions aligned with business and technical requirements
- Translate complex business use cases into scalable, production-ready ML system designs and technical architectures
- Lead design decisions across data pipelines, model training, deployment, and monitoring in cloud-based environments
- Define AI/ML architecture standards, guidelines, and best practices including NFRs such as scalability, security, and performance
- Develop and review architecture and design documentation, ensuring clarity for engineering implementation teams
- Evaluate and select optimal ML approaches, tools, frameworks, and technologies based on client requirements
- Design and guide development of AI/ML solutions across NLP, computer vision, and generative AI domains
- Build and oversee implementation of MLOps pipelines using tools such as MLflow, Kubeflow, Docker, and Kubernetes
- Design and deploy AI agents and multi-agent systems for autonomous or semi-autonomous decision-making
- Lead proof-of-concept initiatives to validate architectures, frameworks, and emerging AI technologies
- Ensure adherence to responsible AI principles, model governance, and ethical AI practices
- Troubleshoot complex system issues through root-cause analysis and technical deep-dives
- 9+ years of experience in machine learning, AI engineering, or data science roles with strong architectural exposure
- Proven experience delivering production-grade ML solutions across NLP, computer vision, or AI-driven systems
- Strong expertise in AI/ML architecture design on cloud and big data environments
- Advanced programming skills in Python, with experience using libraries such as Pandas, NumPy, and Scikit-learn
- Strong hands-on experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX
- Solid understanding of statistical methods and their application in real-world ML problems
- Experience working with SQL and large-scale data processing systems
- Strong knowledge of MLOps practices and tools such as MLflow, Kubeflow, Docker, and Kubernetes
- Experience designing and deploying AI agents and multi-agent systems
- Strong understanding of LLMs, foundation models, prompt engineering, and RAG-based architectures
- Experience with generative AI techniques including GANs and VAEs is highly desirable
- Strong analytical, problem-solving, and system design skills
- Excellent communication and stakeholder management abilities across technical and business teams
- Experience applying responsible AI principles and ethical AI frameworks
- Competitive compensation aligned with senior AI engineering roles
- Flexible and remote-friendly work environment
- Opportunity to work on cutting-edge AI, LLM, and agentic systems
- Exposure to large-scale enterprise AI transformation programs
- Continuous learning and professional development opportunities in advanced AI domains
- Collaborative, non-hierarchical engineering culture focused on innovation
- Opportunity to influence AI architecture decisions across complex global projects.
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Date Posted
07/02/2026
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