Machine Learning Engineering Lead

3 weeks ago

Industrial Area, India Webnyay Full time

We’re looking for an experienced Senior AI Engineer to join our leadership team and take ownership of building and scaling intelligent systems for document understanding, information retrieval, and large-scale text analysis. This role will combine hands-on coding with technical leadership, guiding a team of engineers in developing production-grade ML pipelines and scalable web applications.

As a Technical Lead, you will be responsible for architecting solutions, mentoring team members, ensuring code quality, and driving the integration of AI/ML models into robust backend systems. You will also bring in DevOps best practices to manage deployment, scalability, and performance of our systems.


Key Responsibilities:

  • Lead the design and development of ML-driven systems for document understanding, NLP, and information retrieval.
  • Architect and implement scalable backend services in Python and Django, integrating AI/ML pipelines with web applications.
  • Drive the entire ML lifecycle — data acquisition, preprocessing, experimentation, deployment, monitoring, and optimization.
  • Set up and maintain DevOps pipelines for CI/CD, model deployment, containerization (Docker/Kubernetes), and cloud infrastructure.
  • Mentor and manage a team of ML and software engineers, conducting code reviews, sharing best practices, and ensuring project delivery.
  • Collaborate with product and business teams to translate requirements into technical solutions.
  • Ensure scalability, security, and performance of deployed systems across millions of documents and users.

Required Skills:

  • Strong coding expertise in Python and frameworks like Django/FastAPI/Flask.
  • Proven experience designing, deploying, and scaling ML models in production.
  • Solid foundation in NLP and computer vision, with experience in embeddings, search/retrieval systems, and deep learning architectures.
  • Hands-on experience with DevOps: CI/CD pipelines, Docker, Kubernetes, and cloud platforms (GCP/AWS/Azure).
  • Strong understanding of relational and NoSQL databases;
    exposure to vector databases (e.G., FAISS, Milvus) preferred.
  • Familiarity with distributed systems and handling large datasets efficiently.
  • Excellent problem-solving skills, system design thinking, and ability to balance technical trade-offs.
  • Strong communication and leadership skills to mentor and guide a technical team.

Preferred Skills (Good to have):

  • Prior experience with document layout analysis or multi-modal ML models (vision + text).
  • Experience with libraries like LayoutParser, Detectron2, MMDetection, or LayoutLM.
  • Working knowledge of search and ranking models, semantic search, or vector search.
  • Experience in microservices architecture and API design.
  • Familiarity with MLOps frameworks and model monitoring tools.
  • Contributions to open-source projects or research publications in ML/AI.


Who Should Apply?

This role is ideal for an experienced engineer who enjoys being hands-on while also leading teams, shaping architecture, and delivering real-world AI solutions at scale. If you have a strong foundation in machine learning and backend systems, and want to play a pivotal role in scaling AI-driven platforms, we’d love to talk to you.

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