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  3. Associate Principal Enginee...

Associate Principal Engineer, Machine Learning

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Jobgether logo

Associate Principal Engineer, Machine Learning

Jobgether

Location

India

Experience

Senior

Posted

Jul 7, 2026

Apply by

August 6, 2026

Applicants

0

Early applicantFull-timeWork from Home

Sign in to apply on web or download the app for more options.

Job Description

**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 ## Requirements - 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 ## Benefits - 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. **How Jobgether works:** We use an **AI-powered matching process** to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! [Why Apply Through Jobgether?](https://jobgether.com/how-jobgether-works) **Data Privacy Notice:** By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time. #LI-CL1

Key Responsibilities

  • Design and architect end-to-end machine learning and AI solutions aligned with business requirements
  • Lead design decisions across data pipelines, model training, deployment, and monitoring in cloud environments
  • Define AI/ML architecture standards, guidelines, and best practices including scalability and security
  • Develop and review architecture and design documentation for engineering implementation
  • Evaluate and select optimal ML approaches, tools, frameworks, and technologies
  • Design and guide development of AI/ML solutions across NLP, computer vision, and generative AI domains
  • Build and oversee implementation of MLOps pipelines using MLflow, Kubeflow, Docker, and Kubernetes
  • Design and deploy AI agents and multi-agent systems for autonomous decision-making
  • Lead proof-of-concept initiatives to validate architectures 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

Skills Required

PythonPandasNumPyScikit-learnTensorFlowPyTorchJAXSQLMLflowKubeflowDockerKubernetesNLPComputer VisionGenerative AILLMsPrompt EngineeringRAGMLOpsStatistical MethodsSystem DesignAnalytical skillsProblem-solvingCommunicationStakeholder managementLeadershipGANsVAEs

Benefits

  • Competitive compensation
  • 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
  • Collaborative, non-hierarchical engineering culture

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Job Overview

Salary

—

Job Type

Full-time

Experience

Senior

Location

India

Application Deadline

August 6, 2026

Total Applicants

0

About Jobgether

Jobgether logo

Jobgether is a leading company in the Technology sector, known for innovation and employee-centric culture.

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