Pibit.AI- Lead ML engineer

Location: Bengaluru, India

Company: Pibit.ai

Experience: 5+ Years

Employment Type: Full-Time

About Pibit.ai

Pibit.ai is a cutting-edge AI and data-driven solutions company focused on building intelligent platforms for enterprises. We specialize in Machine Learning, Generative AI, MLOps, Computer Vision, and large-scale data engineering. Our mission is to help organizations unlock the full potential of AI by developing scalable, production-ready systems that make real impact.

Role Overview

We are seeking a highly skilled Lead Machine Learning Engineer to architect, design, and deploy advanced ML systems. You will act as a technical leader responsible for model development, experimentation, and end-to-end deployment while collaborating closely with data scientists, product teams, and engineering stakeholders. This role is ideal for someone who loves solving real-world problems using ML and is passionate about leading technical initiatives.

Key Responsibilities

Machine Learning & Model Development

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  Lead the design, development, and optimization of ML models, including classical ML, deep learning, NLP, and generative AI.

  
  


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  Build scalable ML pipelines for training, evaluation, and inference.

  
  


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  Drive experimentation with new models, architectures, and techniques.

  
  

End-to-End ML System Delivery

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  Own the complete lifecycle from data preprocessing to production deployment.

  
  


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  Deploy and monitor ML models using MLOps practices (CI/CD, model versioning, automation).

  
  


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  Optimize model performance, reliability, and latency.

  
  

Architecture & Technical Leadership

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  Define the ML architecture and best practices for the engineering team.

  
  


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  Mentor junior engineers and provide technical guidance across ML projects.

  
  


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  Collaborate with product managers and stakeholders to translate business problems into ML solutions.

  
  

Data Engineering Collaboration

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  Work with data teams to design robust data pipelines and feature stores.

  
  


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  Ensure high-quality datasets and model readiness for large-scale production systems.

  
  

Innovation & Research

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  Stay updated with the latest advancements in AI/ML, Generative AI, LLMs, and deep learning.

  
  


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  Evaluate and integrate new tools, ML frameworks, and cloud solutions.

  
  

Required Skills & Experience

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  5+ years of hands-on experience in Machine Learning, Deep Learning, or Data Science.

  
  


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  Strong proficiency with Python, TensorFlow / PyTorch, and ML libraries (scikit-learn, XGBoost, HuggingFace).

  
  


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  Experience building and deploying production-grade ML models.

  
  


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  Sound knowledge of MLOps tools: Docker, Kubernetes, MLflow, Airflow, Kubeflow, or similar.

  
  


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  Experience working with cloud platforms: AWS / GCP / Azure.

  
  


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  Strong understanding of data structures, algorithms, and software engineering best practices.

  
  


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  Experience with large datasets, data preprocessing, and feature engineering.

  
  


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  Ability to lead technical discussions and make architectural decisions

• Note:- (Recent experience is the most important factor)
  Overall Experience 5 Years
  Last 3 years of experience primarily focused on NLP + LLM
  Not heavily mixed with analytics, CV, or forecasting
  Minimum 2+ years of continuous LLM / GenAI experience in recent roles
  Experience working on multiple production systems, not just experiments
  Minimum 3 years of NLP experience
  Hands-on experience with text-based problems such as:
  Text extraction
  Semantic search
  Classification/summarization
  Embeddings/transformer models
  Experience working with unstructured text or documents, for example:
  PDFs, forms, CVs, tickets, emails
  OCR + NLP
  Document parsing/extraction