Lead Machine Learning Engineer

3 days ago

Karachi, Sindh, Pakistan Folio3 Software Full time 2,000,000 - 2,500,000 per year


Summary

Folio3 is looking for a Lead Machine Learning Engineer to drive innovation across AI initiatives from conceptualization to scalable deployment. The ideal candidate combines deep technical expertise with strong leadership, guiding a high-performing team in developing advanced ML and Agentic AI solutions that power next-generation enterprise applications.

Responsibilities

  • Lead the design, development, and deployment of end-to-end AI/ML systems, including model training, inference, and performance optimization.
  • Research and implement Agentic AI architectures, enabling autonomous decision-making and task orchestration across enterprise applications.
  • Evaluate, compare, and optimize Deep Learning models for Computer Vision, NLP, and Predictive Analytics use cases.
  • Architect and deploy scalable AI solutions on AWS, Azure, or GCP using MLOps best practices.
  • Build and maintain backend APIs for model inference and data services (Python, FastAPI, Flask).
  • Establish best practices for model versioning, experiment tracking, and monitoring using tools like ClearML, MLflow, or Weights & Biases.
  • Collaborate cross-functionally with data engineers, product managers, and business stakeholders to translate strategic goals into technical deliverables.
  • Mentor junior engineers and guide the ML team on design, research, and implementation strategies.
  • Stay ahead of emerging trends in Generative AI, LLMs, and Agentic AI systems and integrate them into Folio3's AI roadmap.

Requirements

  • 7+ years of professional experience in Machine Learning, Deep Learning, or Applied AI.
  • Proven experience in designing and deploying production-grade ML systems and AI-driven APIs.
  • Strong understanding of CNNs, RNNs, Transformers, and Reinforcement Learning techniques.
  • Expertise in EDA, Feature Engineering, and model interpretability.
  • Hands-on experience with PyTorch, TensorFlow, scikit-learn, XGBoost, PyCaret, or similar frameworks.
  • Proficiency in Python, FastAPI/Flask, and Linux-based environments.
  • Experience implementing MLOps pipelines for model lifecycle automation.
  • Knowledge of Agentic AI frameworks and multi-agent orchestration (LangChain, CrewAI, AutoGen, or similar).
  • Excellent leadership, communication, and problem-solving skills with the ability to mentor teams and manage complex projects.
  • Passionate about AI innovation, with a continuous learning mindset and strong research orientation.

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