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Machine Learning Architect

Machine Learning Architect

SUPERSOURCING TECHNOLOGIES PRIVATE LIMITEDIndia
1 day ago
Job description

Position : Machine Learning (ML) Architect

Experience : 5+ Years

Employment Type : Full-Time / Permanent

Job Overview :

We are seeking a Machine Learning Architect to design and lead the end-to-end architecture of scalable ML systemscovering data ingestion, feature engineering, model training, deployment, and continuous monitoring. The ideal candidate will bring deep expertise in MLOps, deep learning, and cloud-native ML platforms, enabling high-performing and secure AI solutions that align with strategic business objectives.

Key Responsibilities :

  • Architect End-to-End ML Systems : Design scalable ML pipelines including data ingestion, preprocessing, model training, and inference workflows.
  • Implement MLOps Practices : Define CI / CD, automated retraining, version control, and model governance frameworks for efficient ML lifecycle management.
  • Deep Learning Architecture : Design and optimize deep learning solutions for complex data types, including audio, video, and multimodal inputs.
  • GenAI and LLM Integration : Architect and deploy Generative AI and Large Language Model (LLM)-based solutions using modern frameworks.
  • Cloud and Infrastructure : Lead deployment on AWS, Azure, or GCP using Kubernetes, Kubeflow, SageMaker, Vertex AI, or Azure ML.
  • Cross-Functional Collaboration : Partner with data scientists, ML engineers, data engineers, and DevOps teams to ensure seamless integration of ML systems.
  • Performance, Compliance, and Security : Ensure solutions meet organizational standards for security, scalability, and compliance.
  • Technology Evaluation : Continuously evaluate new ML frameworks, tools, and best practices to enhance architecture efficiency and innovation.

Required Qualifications :

  • Bachelors or Masters in Computer Science, Artificial Intelligence, Data Science, or a related field.
  • 5+ years of experience in designing and implementing ML / AI architectures and MLOps frameworks.
  • Proven expertise in Deep Learning (CNNs, RNNs, Transformers), Generative AI, and LLM-based architectures.
  • Proficiency in Python, TensorFlow, PyTorch, and MLFlow or equivalent tools.
  • Strong knowledge of cloud-native ML ecosystems (AWS SageMaker, Azure ML, GCP Vertex AI).
  • Solid understanding of data engineering, CI / CD pipelines, and container orchestration (Docker, Kubernetes).
  • Experience with monitoring and observability tools for ML systems (e.g., Prometheus, Grafana, EvidentlyAI).
  • Excellent problem-solving, communication, and leadership skills.

    • Preferred Skills :

  • Experience with distributed training frameworks such as Horovod or DeepSpeed.
  • Familiarity with vector databases (Pinecone, FAISS) and retrieval-augmented generation (RAG) systems.
  • Knowledge of data governance and ML compliance frameworks.
  • Hands-on experience in AI model optimization for edge or real-time environments.

    • Why Join Us :

  • Work on cutting-edge ML and AI innovations across multiple domains.
  • Collaborate with an exceptional team of data scientists and engineers.
  • Opportunity to shape the organizations AI and ML roadmap.
  • Competitive compensation with strong growth opportunities.

    • (ref : hirist.tech)

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