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Lead AI ML Engineer

📅 Nov 4, 2025
AI/ML SolutionsMachine LearningDeep LearningNatural Language Processing

📜 Description

  • Lead teams in building LLM-powered and Agentic AI applications with multi-agent workflows.
  • Oversee the complete ML lifecycle from data preparation to model deployment and optimization.
  • Implement MLOps practices for production AI, including CI/CD and model monitoring.
  • Communicate complex AI concepts to non-technical stakeholders and mentor engineering teams.

🛠️ Requirements

  • 8+ years of experience in designing, developing, and deploying AI/ML solutions, including Machine Learning, Deep Learning, NLP, and Computer Vision.
  • Strong hands-on experience with Generative AI, LLMs, Agentic AI, RAG, and MCP-based architectures.
  • Experience building LLM-powered and Agentic AI applications, including multi-agent workflows, tool calling, memory, orchestration, and autonomous decision-making.
  • Strong expertise in RAG, vector embeddings, semantic search, vector databases such as FAISS/Pinecone, and LLM frameworks including LangChain, LangGraph, LlamaIndex, and Hugging Face.
  • Proficiency in Python and ML/Deep Learning frameworks such as PyTorch, TensorFlow, Scikit-learn, along with Pandas and Spark.
  • Strong understanding of the complete ML lifecycle, including data preparation, feature engineering, model training, evaluation, tuning, deployment, and optimization.
  • Hands-on experience with MLOps and production AI, including MLflow, CI/CD, Docker/Kubernetes, model monitoring, performance tracking, and cloud platforms (AWS/Azure/GCP).
  • Proven experience taking AI solutions from POC/concept to scalable production environments and building reusable AI frameworks or platforms.
  • Experience leading AI/ML teams, mentoring engineers, defining technical architecture, and communicating complex AI concepts to non-technical stakeholders.
  • Contributions to open-source projects, research papers, patents, or technical blogs would be an added advantage.

Benefits

  • Machine Learning
  • Deep Learning
  • Computer Vision
Full job description
3Pillar is an AI transformation partner on a mission to help enterprises build the AI-native products and intelligent agents that will define the next era of business. With teams across North America, Europe, Latin America, and Asia, we work with the most ambitious companies in financial services, healthcare, media, and technology — helping them move faster, modernize boldly, and compete on their own terms. Our HelixAI platform and Helix Pods delivery model put our engineers at the center of real agentic transformation — doing work that is open, portable, and built to last. We are building the future of enterprise AI
What It's Like to Work at 3Pillar:
At 3Pillar, we create an environment where people can do their best work while maintaining a healthy work-life balance.
  • Flexibility & Well-being – Our remote-first approach gives you the flexibility to work where you perform best, while prioritizing your well-being and personal commitments.
  • Global Community – Collaborate with talented colleagues across the globe in a culture built on connection, support, and shared success.
  • Your Voice Matters – We foster open communication and multiple feedback channels, ensuring every employee has the opportunity to be heard and make an impact.
  • Growth & Development – Gain exposure to diverse clients, industries, and challenges that accelerate learning and career growth.

Our culture is guided by four core values: Collaboration, Outperform, Respect, and Evolve—the principles that shape how we work, grow, and succeed together.
Regards Rajan Paul(Linkedin Profile) 3Pillar Global

Minumum Qualification

  • 8+ years of experience in designing, developing, and deploying AI/ML solutions, including Machine Learning, Deep Learning, NLP, and Computer Vision.
  • Strong hands-on experience with Generative AI, LLMs, Agentic AI, RAG, and MCP-based architectures.
  • Experience building LLM-powered and Agentic AI applications, including multi-agent workflows, tool calling, memory, orchestration, and autonomous decision-making.
  • Strong expertise in RAG, vector embeddings, semantic search, vector databases such as FAISS/Pinecone, and LLM frameworks including LangChain, LangGraph, LlamaIndex, and Hugging Face.
  • Proficiency in Python and ML/Deep Learning frameworks such as PyTorch, TensorFlow, Scikit-learn, along with Pandas and Spark.
  • Strong understanding of the complete ML lifecycle, including data preparation, feature engineering, model training, evaluation, tuning, deployment, and optimization.
  • Hands-on experience with MLOps and production AI, including MLflow, CI/CD, Docker/Kubernetes, model monitoring, performance tracking, and cloud platforms (AWS/Azure/GCP).
  • Proven experience taking AI solutions from POC/concept to scalable production environments and building reusable AI frameworks or platforms.
  • Experience leading AI/ML teams, mentoring engineers, defining technical architecture, and communicating complex AI concepts to non-technical stakeholders.
  • Contributions to open-source projects, research papers, patents, or technical blogs would be an added advantage.
  • Additional Desired Experience

  • Led teams building GenAI, LLM, Agentic AI, or MCP-driven applications.
  • Experience with vector databases (FAISS, Pinecone) and Hugging Face ecosystem.
  • Built reusable AI frameworks, platforms, or internal tooling.
  • Contributions to open-source projects, research papers, or technical blogs.
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