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Lead AI/ML Engineer

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Job Title: Lead Artificial Intelligence / Machine Learning Engineer

Location: Baner, Pune (Hybrid)
Experience: 5+ Years
Shift Time: 2:00 PM – 11:00 PM (IST)
Notice Period: Immediate to 15 Days

About the Role:

We are seeking a Lead Artificial Intelligence / Machine Learning Engineer to design, develop, and deploy next-generation AI solutions that drive measurable business outcomes. This role involves leading a team of AI Engineers and Data Scientists, architecting intelligent systems, and implementing scalable AI/ML solutions using Python, NLP, Generative AI, and MLOps.

You will collaborate closely with cross-functional teams—including product managers, business stakeholders, and software engineers—to deliver end-to-end AI-driven products that enhance decision-making and efficiency.

Key Responsibilities, Leadership & Strategy:

  • Lead, mentor, and inspire a team of AI Engineers and Data Scientists to deliver high-impact AI solutions.
  • Drive innovation through research, experimentation, and implementation of cutting-edge AI/ML methodologies.
  • Ensure alignment of AI initiatives with organizational goals and technical standards.

AI / ML Development:

  • Design, develop, and deploy ML models using Python, Scikit-learn, TensorFlow, and PyTorch.
  • Build and optimize Natural Language Processing (NLP) and Large Language Model (LLM) applications for real-world use cases.
  • Implement Generative AI capabilities to enhance automation, personalization, and data-driven insights.

MLOps & Engineering:

  • Develop and maintain end-to-end ML pipelines, integrating with CI/CD and containerization tools (Docker).
  • Deploy, monitor, and scale models on cloud platforms (AWS, GCP, or Azure).
  • Collaborate with data and software engineers to ensure robust, production-ready architectures.

Cross-functional Collaboration:

  • Partner with product, engineering, and business teams to translate requirements into technical solutions.
  • Ensure documentation, coding standards, and reproducibility across all AI projects.

Mentorship & Growth:

  • Guide and coach junior engineers and data scientists.
  • Identify upskilling needs and create learning pathways to strengthen team capability.

Required Qualifications:

  • Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, AI, or related field.
  • 5+ years of hands-on experience in AI/ML or Data Science with real-world implementation.
  • Strong proficiency in Python and key libraries (NumPy, Pandas, Scikit-learn).
  • Proven experience with NLP, LLMs, or Computer Vision.
  • Expertise in ML frameworks such as PyTorch and TensorFlow.
  • Hands-on experience in MLOps, CI/CD, and Docker-based deployments.
  • Proficiency in Flask, FastAPI, or Django for model integration.
  • Experience with cloud services (AWS, GCP, or Azure).
  • Familiarity with SQL/NoSQL databases, Git, and version control.
  • Strong understanding of software engineering best practices.

Preferred Qualifications:

  • Experience with Big Data technologies (Apache Spark, Kafka, Kinesis).
  • Exposure to cloud ML platforms like AWS SageMaker or GCP Vertex AI.
  • Knowledge of data visualization tools such as Tableau or Power BI.
  • Background in GenAI prompt engineering, fine-tuning LLMs, or model optimization.

Why Join Us:

  • Opportunity to lead high-impact AI initiatives with real-world applications.
  • Collaborative, innovation-driven work culture.
  • Access to the latest AI/ML technologies and cloud infrastructure.
  • Competitive salary and growth-oriented environment

Job Types: Full-time, Permanent

Pay: ₹2,500,000.00 - ₹3,500,000.00 per year

Application Question(s):

  • Please share your total years of experience in Artificial Intelligence / Machine Learning.
  • How many years of hands-on experience do you have with Python for AI/ML projects?
  • What kind of NLP projects have you worked on (e.g., sentiment analysis, text classification, chatbots, summarization)?
  • Do you have practical experience with Large Language Models (LLMs)?

Work Location: In person

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